A wireless 5G/6G message can be demodulated by converting the as-received I-branch and Q-branch signals to the corresponding waveform amplitude and phase, using simple algorithms. Then, fault diagnosis and fault correction can be performed efficiently based on the waveform parameters.
A resource-efficient method for the base station to assist reduced-capability user devices in aligning their transmission and reception beams toward the base station. At a prescribed time, on a prescribed subcarrier, the base station transmits a series of beam scan signals, each beam scan signal comprising a single resource element, and each beam scan signal transmitted in a different direction. Each user device determines which of the beam scan signals is best received, and thereby determines its direction relative to the base station. Each user device then transmits a single-resource-element reply signal during a reply window, in which the reply signal is transmitted on a subcarrier assigned to that user device, and the timing of the reply signal indicates which beam scan signal provided the best reception. The base station can then receive all the reply signals, and by time-frequency analysis, determine the alignment direction of each user device.
H04B 7/06 - Systèmes de diversitéSystèmes à plusieurs antennes, c.-à-d. émission ou réception utilisant plusieurs antennes utilisant plusieurs antennes indépendantes espacées à la station d'émission
H04W 24/10 - Planification des comptes-rendus de mesures
H04W 72/044 - Affectation de ressources sans fil sur la base du type de ressources affectées
3.
Restricted Links for Ultra-Secure IoT Communications in 5G and 6G
The communication links for IoT and other reduced-capability devices are easy targets for cyber attacks in 5G and 6G networks. However, most such end devices are basic, low-cost sensors and actuators with very minimal communication requirements. Therefore, a class of restricted links is disclosed, configured to carry commands from a manager node or “hub device” to its end devices, and data back to the hub device, using pre-configured formats. The restricted links provide the communications that the end device needs, and no more. Restricted links leave little or no attack surface for intrusion, and thus prevent the spread of an attack from a compromised end device upward into the hub device. With restricted links acting as firewalls, even the most basic end devices can protect the larger network without the cost and burden of 3GPP cybersecurity software. Many other aspects are disclosed.
Message faults are a major contributor to latency in 5G and expected to be even more so in 6G due to pathloss, crowding, and the rapid cadence of high-volume traffic. Efficient means for correcting message faults are needed. Therefore, disclosed herein are methods for a receiver to compare two versions of a message, both faulted according to their embedded error-detection codes, and reconstruct the correct message-without a time-consuming grid search of possible modulation substitutions. In addition, the receiver can pass the message data, including modulation quality and signal quality, directly to an artificial intelligence model, which can (a) indicate which resource elements of the message (and/or the error-detection code) are faulted, and (b) reconstruct the most likely corrected version of the message, all in a small fraction of a retransmission time.
Vehicles in traffic can avoid collisions when the driver (or autonomous controller) knows where the other vehicles are located around it, that is, a real-time traffic map. A planning entity (one of the vehicles, or a roadside access point), can request that all the vehicles measure the angles of all the other vehicles in view, and at least one distance, and to forward that data along with its wireless address, to the planning entity. There, the various data sets are map-merged based on maximum likelihood, possibly with AI assistance, and thereby producing a map of traffic. Each vehicle can also be annotated with its wireless address, if supplied. This traffic map is then broadcast by the planning entity, enabling all the vehicles to recognize insipient hazards.
H04W 8/26 - Adressage ou numérotation de réseau pour support de mobilité
G01S 5/00 - Localisation par coordination de plusieurs déterminations de direction ou de ligne de positionLocalisation par coordination de plusieurs déterminations de distance
G01S 19/25 - Acquisition ou poursuite des signaux émis par le système faisant intervenir des données d'assistance reçues en provenance d'un élément coopérant, p. ex. un GPS assisté
G06K 19/06 - Supports d'enregistrement pour utilisation avec des machines et avec au moins une partie prévue pour supporter des marques numériques caractérisés par le genre de marque numérique, p. ex. forme, nature, code
G08G 1/01 - Détection du mouvement du trafic pour le comptage ou la commande
G08G 1/017 - Détection du mouvement du trafic pour le comptage ou la commande par identification des véhicules
G08G 1/04 - Détection du mouvement du trafic pour le comptage ou la commande utilisant des détecteurs optiques ou ultrasonores
G08G 1/056 - Détection du mouvement du trafic pour le comptage ou la commande avec des dispositions pour distinguer la direction de circulation
G08G 1/09 - Dispositions pour donner des instructions variables pour le trafic
G08G 1/137 - Systèmes de commande du trafic pour véhicules routiers indiquant la position de véhicules, p. ex. de véhicules à horaire déterminé à l'intérieur du véhicule l'indicateur étant sous la forme d'une carte
H04W 4/029 - Services de gestion ou de suivi basés sur la localisation
H04W 4/40 - Services spécialement adaptés à des environnements, à des situations ou à des fins spécifiques pour les véhicules, p. ex. communication véhicule-piétons
H04W 4/46 - Services spécialement adaptés à des environnements, à des situations ou à des fins spécifiques pour les véhicules, p. ex. communication véhicule-piétons pour la communication de véhicule à véhicule
H04W 4/90 - Services pour gérer les situations d’urgence ou dangereuses, p. ex. systèmes d’alerte aux séismes et aux tsunamis
6.
Automatic Collision-Avoidance and/or Harm-Minimization of Vehicle Collisions
A subject vehicle in traffic can detect a second vehicle using sensors that measure motions of the second vehicle, and thereby determine one or more future trajectories of the second vehicle, and thereby determine whether a collision between the subject and second vehicles is imminent. The subject vehicle can calculate one or more sequences of actions, each action comprising an acceleration, a deceleration, and/or a steering action of the subject vehicle. The subject vehicle can also calculate whether any of the one or more sequences of actions can avoid the imminent collision, and also calculate an expected harm of the imminent collision according to each of the one or more sequences of actions. The subject vehicle can then autonomously select and implement a particular sequence of actions that is calculated to avoid the imminent collision or to minimize the harm of the imminent collision.
B60W 30/09 - Entreprenant une action automatiquement pour éviter la collision, p. ex. en freinant ou tournant
B60Q 9/00 - Agencement ou adaptation des dispositifs de signalisation non prévus dans l'un des groupes principaux
B60W 10/04 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des ensembles de propulsion
B60W 10/18 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de freinage
B60W 10/184 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de freinage avec des freins de roues
B60W 10/20 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de direction
B60W 30/085 - Ajustant automatiquement la position du véhicule en préparation de la collision, p. ex. en freinant pour piquer du nez
B60W 30/095 - Prévision du trajet ou de la probabilité de collision
B60W 50/12 - Limitation de la possibilité de commande du conducteur en fonction de l'état du véhicule, p. ex. moyens de verrouillage des grandeurs d'entrées pour éviter un fonctionnement dangereux
B60W 50/14 - Moyens d'information du conducteur, pour l'avertir ou provoquer son intervention
B60W 50/16 - Signalisation tactile au conducteur, p. ex. vibration ou augmentation de la résistance sur le volant ou sur la pédale d'accélérateur
G05D 1/617 - Sécurité ou protection, p. ex. définition de zones de protection autour d’obstacles ou évitement de zones dangereuses
Message faulting is expected to be a major challenge in 5G—Advanced and especially 6G, due to increased pathloss and phase noise at FR2 frequencies, and exponential crowding of networks. Legacy methods for forward-correction or automatic retransmissions are unsuitable to the fast-paced demands of next-generation users. Therefore, disclosed herein is an AI-based receiver that interprets a corrupted message to determine the most likely meaning or intent, and thereby provides one or more candidate corrected messages along with a likelihood that each of the candidate corrected messages is indeed correct. The AI model may also be provided with data on the context or current activity of the receiver, data on the waveform of each message element, and other data available to the receiver, so that the AI model can further refine the likelihood values. By recovering corrupted messages in the receiver, a costly retransmission may be avoided, saving time and resource usage.
For improved reception of PDCCH (physical downlink control channel) messages in 5G and 6G, each message can be preceded by a special demarcation, and optionally followed by another (preferably different) demarcation. For even better reception, the two demarcations may be configured as short-form demodulation references that exhibit two predetermined modulation levels of the modulation scheme, such as the maximum and minimum amplitude or phase levels. For optimal reception, one or both demarcations may be surrounded by gaps, consisting of a single resource element with no transmission. Downlink messages with such multi-functional demarcations may greatly simplify the task of user devices in receiving their control messages from the base station.
H04L 5/00 - Dispositions destinées à permettre l'usage multiple de la voie de transmission
H04W 72/0446 - Ressources du domaine temporel, p. ex. créneaux ou trames
H04W 72/0453 - Ressources du domaine fréquentiel, p. ex. porteuses dans des AMDF [FDMA]
H04W 72/1273 - Jumelage du trafic à la planification, p. ex. affectation planifiée ou multiplexage de flux de flux de données en liaison descendante
H04W 72/23 - Canaux de commande ou signalisation pour la gestion des ressources dans le sens descendant de la liaison sans fil, c.-à-d. en direction du terminal
9.
AI-based vehicle cybersecurity with 5G/6G sub-network topology
Cybersecurity is a critical requirement for current and future vehicles, to protect against catastrophic cyber attacks. Vehicles today (including land vehicles, waterborne vehicles, and aircraft including such embodiments as airplanes, helicopters, and air taxis) are constructed with myriad separate sensors and actuators, which generally have only limited cyber protections—a worrying vulnerability. Therefore, procedures are disclosed for a vehicle-wide 5G/6G network in which each ECU (electronic control unit) is a separate user device. Each ECU is also the manager of a set of sensors and actuators, forming a local sub-network with tightly regulated wireless protocols. Each ECU and each end sensor/actuator may include an AI model to detect and defeat cyber attacks. Each sensor/actuator boots from ROM and executes from ROM, performs its specific tasks on demand, and then communicates the results solely with its ECU in a nested-star topology, thereby providing vehicle-wide cybersecurity on par with 3GPP standards.
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
B60R 16/023 - Circuits électriques ou circuits de fluides spécialement adaptés aux véhicules et non prévus ailleursAgencement des éléments des circuits électriques ou des circuits de fluides spécialement adapté aux véhicules et non prévu ailleurs électriques pour la transmission de signaux entre des parties ou des sous-systèmes du véhicule
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
10.
Enhanced 5G/6G Message Reliability with Guard-Space References
Phase noise is an unsolved, limiting factor for high frequency communications envisioned for 6G. Proposed herein are phase-tracking reference signals embedded in each guard-space of a message. The receiver can recalibrate the phase noise, and amplitude noise as well, with based on each guard-space reference signal, thereby providing extremely localized noise compensation including amplitude and phase distortions and including rapidly-varying frequency-dependent distortions characteristic of interference, on a symbol-by-symbol basis, at zero cost in message throughput and transmission power. The normal functions of a cyclic prefix in the guard-space can be provided by tailoring the guard-space reference signal, as detailed herein. Examples show how guard-space reference signals provide a fault-mitigating capability that is enabling to 6G mmWave objectives.
Message faulting is an expensive problem for 5G and especially for 6G due to increased pathloss and network faulting. Current message correction procedures rely on bulky FEC codes or automatic retransmission requests, further burdening the network. Disclosed are methods for a receiver to recognize a faulted message, identify the faulted message elements, and determine the corrected value for each fault, thereby recovering the correct message without a retransmission. Autonomous error correction within a receiver can be performed without network assistance or standards because the receiver has enough data, in the form of the received waveforms and the included error-detection code (usually just 16 bits) to find the corrected version internally. Reduced dependence on retransmissions and multiple code transmissions will alleviate network crowding while preserving the desired reliability and latency goals of the recipient.
Currently, if a wireless device transmits a message but it is not received properly, the device is required to wait a variable time before retransmitting the message, and that waiting time is increased after each unsuccessful attempt. This is to reduce network congestion at high traffic rates, but it also puts certain users at an unfair disadvantage. For example, a user that has tried repeatedly to communicate is forced to wait longer and longer intervals, while another user is permitted to communicate without delay on the same channel. Clearly, this is an unfair situation. Therefore, disclosed herein is an alternate protocol in which users are given increasing priority after each failed attempt, specifically by reducing the fixed waiting time and/or a random backoff delay, before the next attempt. Simulations show that this change substantially eliminates the unfairness.
H04W 74/0816 - Accès non planifié, p. ex. ALOHA utilisant une détection de porteuse, p. ex. accès multiple par détection de porteuse [CSMA] avec évitement de collision
H04L 1/1812 - Protocoles hybridesDemande de retransmission automatique hybride [HARQ]
13.
Feedback protocols for near-real-time 5G/6G transmission optimization
In 5G and expected 6G networks, beam control is a crucial requirement. Disclosed are methods for user devices to assist a base station in correctly aiming downlink beams toward each user device, and to compensate for Doppler-effect frequency offsets, and to properly adjust the transmission power for adequate reception without generating unnecessary background radiation, among many other transmission parameters to be adjusted in real-time. The feedback messages by be extremely brief, such as a single resource element appended to an acknowledgement message, and may be multiplexed with other beam adjustment requests in a predetermined code. Mobile user devices in an ad-hoc sidelink network can align their beams using such feedback procedures. In a similar way, base stations or core networks can exchange messages with each other (as in wireless backhaul) with frequent feedback-controlled adjustment of the beam parameters, for more efficient exchange of messages between cells.
H04B 7/06 - Systèmes de diversitéSystèmes à plusieurs antennes, c.-à-d. émission ou réception utilisant plusieurs antennes utilisant plusieurs antennes indépendantes espacées à la station d'émission
H04B 17/373 - Prédiction des paramètres de qualité d’un canal
H04B 17/382 - SurveillanceTests de canaux de propagation pour l’attribution de ressources, le contrôle d’accès ou le transfert
H04W 24/02 - Dispositions pour optimiser l'état de fonctionnement
H04W 24/06 - Réalisation de tests en trafic simulé
H04W 24/10 - Planification des comptes-rendus de mesures
H04W 52/24 - Commande de puissance d'émission [TPC Transmission power control] le TPC étant effectué selon des paramètres spécifiques utilisant le rapport signal sur parasite [SIR Signal to Interference Ratio] ou d'autres paramètres de trajet sans fil
H04W 72/542 - Critères d’affectation ou de planification des ressources sans fil sur la base de critères de qualité en utilisant la qualité mesurée ou perçue
H04W 74/0833 - Procédures d’accès aléatoire, p. ex. avec accès en 4 étapes
14.
Amplitude-phase exclusion zones for 5G/6G message fault detection
A wireless receiver in 5G and 6G can localize message faults by defining “exclusion regions” that do not include any of the predetermined allowed modulation states of a modulation scheme. Then, upon receiving a message, the receiver can measure (or calculate from the I and Q branch amplitudes) the received amplitude and phase of the waveform signal in each message element. If either the received amplitude or the received phase is within any of the exclusion regions, the receiver determines that message element is faulted. If the received amplitude and received phase are not within any of the exclusion regions, the message element is demodulated according to the closest modulation state. In addition, the receiver can increment an amplitude fault tally and a phase fault tally according to which parameter-amplitude or phase-is inside the exclusion regions, thereby greatly simplifying recovery of the message without a retransmission.
In 5G and especially 6G, message fault recovery is a critical requirement, due to interference in crowded networks. Therefore, modulation schemes are proposed in which a collided message can be recovered by analysis of the sum-signal resulting from the addition of two different signals. The collision generates a predictable signal which can be decomposed into the component signals, thereby enabling the original message to be recovered in some cases. To do so, the modulation scheme is restricted to a subset of allowed states, in which any sum of two states is not one of the allowed states. When the receiver detects one of the disallowed states, the receiver can allocate the value to one of the allowed states, or at least reduce the number of possible combinations, and thereby recover the message.
The college quarterback who displays outstanding talent of sufficient interest to National Football League teams can be effectively analyzed in intense granular detail using the present disclosure's video freeze-frame/AI-cross-correlation technology—and other Artificial Intelligence modalities. Very few cross-correlations can be intellectually accommodated at one time by humans—even by the very smartest and most talented human beings on the planet. The infinitely-possible simultaneous AI analyses, correlations, and cross-correlations of the gigantic number of physical, mental, and emotional attributes enables selection of a potential NFL quarterback (and that of other positions) with superior accuracy and much less guesswork than the current system fraught with uncertainly. Throwing a ‘catchable’ pass is essential—as is completing passes in the face of a ferocious defensive pass rush—or making alternative correct split-second decisions, such as ‘scrambling’ for a first-down when necessary. These are paramount requirements for a winning NFL quarterback. The National Football League quarterback must overcome ALL adversity and WIN—especially when the game is on the line. Having the winning quarterback is mandatory for NFL coaches and team owners paying the bills in their supreme quest for victory in the SUPER BOWL. Losing is NOT an option in the National Football League.
G06V 20/40 - ScènesÉléments spécifiques à la scène dans le contenu vidéo
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
G06V 40/20 - Mouvements ou comportement, p. ex. reconnaissance des gestes
17.
Vehicle localization by artificial intelligence and 5G/6G messaging
Modern collision-avoidance systems are capable of cooperating with other vehicles in an emergency, but only if the vehicle processors already know the locations and 5G/6G wireless addresses of the other at-risk vehicles. This is an unsolved problem. Therefore, methods are disclosed for a “planning” vehicle to solicit angle and distance measurements from each “cooperating” vehicle in proximity, and their wireless addresses. The planning vehicle can then process those measurements, determining the relative coordinates of each vehicle in view, and then broadcasting a results message with all the coordinates and, when known, wireless addresses. The vehicles can then quickly arrange coordinated evasions for collision avoidance. Optionally, an artificial intelligence model may process the angle and distance measurements, deriving the best-fit two-dimensional distribution. Optionally, the planning vehicle can determine its orientation and geographical coordinates, and then include the geographical coordinates of the other vehicles in the results message.
H04W 8/26 - Adressage ou numérotation de réseau pour support de mobilité
G01S 5/00 - Localisation par coordination de plusieurs déterminations de direction ou de ligne de positionLocalisation par coordination de plusieurs déterminations de distance
G01S 19/25 - Acquisition ou poursuite des signaux émis par le système faisant intervenir des données d'assistance reçues en provenance d'un élément coopérant, p. ex. un GPS assisté
G06K 19/06 - Supports d'enregistrement pour utilisation avec des machines et avec au moins une partie prévue pour supporter des marques numériques caractérisés par le genre de marque numérique, p. ex. forme, nature, code
G08G 1/01 - Détection du mouvement du trafic pour le comptage ou la commande
G08G 1/017 - Détection du mouvement du trafic pour le comptage ou la commande par identification des véhicules
G08G 1/04 - Détection du mouvement du trafic pour le comptage ou la commande utilisant des détecteurs optiques ou ultrasonores
G08G 1/056 - Détection du mouvement du trafic pour le comptage ou la commande avec des dispositions pour distinguer la direction de circulation
G08G 1/09 - Dispositions pour donner des instructions variables pour le trafic
G08G 1/137 - Systèmes de commande du trafic pour véhicules routiers indiquant la position de véhicules, p. ex. de véhicules à horaire déterminé à l'intérieur du véhicule l'indicateur étant sous la forme d'une carte
H04W 4/029 - Services de gestion ou de suivi basés sur la localisation
H04W 4/40 - Services spécialement adaptés à des environnements, à des situations ou à des fins spécifiques pour les véhicules, p. ex. communication véhicule-piétons
H04W 4/46 - Services spécialement adaptés à des environnements, à des situations ou à des fins spécifiques pour les véhicules, p. ex. communication véhicule-piétons pour la communication de véhicule à véhicule
H04W 4/90 - Services pour gérer les situations d’urgence ou dangereuses, p. ex. systèmes d’alerte aux séismes et aux tsunamis
18.
Real-time Fault Mitigation by Modulation Quality in 5G and 6G
Message faulting is an unsolved problem in 5G-Advanced and 6G, due to higher frequencies, higher pathloss, higher modulation orders, and higher numerology planned for the aggressive next-generation goals. Legacy modulation schemes are not ideal due to limited phase margins and complex noise effects that inhibit mitigation. Hence, the standard plan is to either include bulky redundant bits or simply request a retransmission upon any error. Disclosed herein are methods for the receiver to identify faulted message elements and correct them, without a retransmission, based on the modulation data alone. Two contrasting modulation schemes, 16QAM and multiplexed amplitude-phase modulation, are contrasted and, in some applications, combined to reveal the fault locations. With the enhanced reliability of real-time fault mitigation, and the reduced latency of avoiding the retransmission, the proposed methods can enable the ambitious next-generation goals.
An unsolved problem in 5G-Advanced and especially 6G is message fault mitigation without a costly retransmission. Methods are disclosed for the receiver to analyze each message element's received waveform signal to detect characteristic features of interference and noise, such as excessive amplitude or phase variation within the message element or excessive deviation from the predetermined modulation levels of the modulation scheme, and to provide that data to an AI model trained in message fault correction. The AI model can then identify the faulted message elements, and attempt to correct them according to the likely intent or meaning of the message based on the non-faulted message elements, and on the bit sequences of previously received non-faulted messages, and other criteria that the AI model may apply. By repairing the message upon receipt, the costs in time, transmission power, and background noise generation may be avoided. Next-generation users will enjoy the improved reception.
Beam alignment is a critical requirement in 5G-Advanced and 6G due to the high density of user devices anticipated in the coming years. However, prior-art beam alignment procedures are slow and costly in terms of resource usage. Therefore, disclosed herein are methods enabling a user device to determine the direction toward the base station rapidly at very low cost. The base station emits a tailored pulse with an angle-dependent phase, varying from a first phase at a first angle, to a second phase at a second angle, followed by a uniform-phase calibrator pulse. The user device can measure the as-received phase of the tailored pulse relative to the calibrator pulse, and thereby determine the user's direction relative to the base station. The user device can then inform the base station of the received phase, which is proportional to the angle. Both user and base station thereby obtain instant beam alignment.
G01S 3/72 - Systèmes à diversité spécialement adaptés à la radiogoniométrie
H04B 17/24 - SurveillanceTests de récepteurs avec rétroaction des mesures vers l’émetteur
G01S 3/04 - Radiogoniomètres pour déterminer la direction d'où proviennent des ondes infrasonores, sonores, ultrasonores ou électromagnétiques ou des émissions de particules sans caractéristiques de direction utilisant des ondes radio Détails
G01S 3/64 - Systèmes à faisceau large produisant au récepteur un signal enveloppe réellement sinusoïdal de l'onde porteuse du faisceau dont l'angle de phase dépend de l'angle entre la direction de l'émetteur par rapport au récepteur et une direction de référence issue du récepteur, p. ex. système cardioïde où l'angle de phase du signal est déterminé par la comparaison de phase avec un signal de référence alternatif synchronisé avec la variation de directivité
H04B 17/27 - SurveillanceTests de récepteurs pour localiser ou positionner l’émetteur
Optimization of transmission beams in 5G/6G requires feedback to the transmitting entity. Current beam alignment/optimization methods are so complex and resource-intensive, that users often delay re-alignment even when required by to changing conditions. Therefore, methods are provided for a transmitter to add two brief, single-resource-element test signals, with slightly different transmission parameters (such as direction), to the end each message. The receiver selects which test signal, or the message itself, that has the best signal, and informs the transmitter using a terse bit-level acknowledgement code. The reception beam must also be aligned, generally without feedback. The transmitter provides a series of identical signals, sequentially in time, while the receiver varies its reception beam parameters while measuring the signal level and optimizing its reception parameters. Both transmitter and receiver can thereby align their beams and optimize their beam parameters for the best communications, at negligible resource cost.
H04B 7/06 - Systèmes de diversitéSystèmes à plusieurs antennes, c.-à-d. émission ou réception utilisant plusieurs antennes utilisant plusieurs antennes indépendantes espacées à la station d'émission
H04B 17/373 - Prédiction des paramètres de qualité d’un canal
H04B 17/382 - SurveillanceTests de canaux de propagation pour l’attribution de ressources, le contrôle d’accès ou le transfert
H04W 24/02 - Dispositions pour optimiser l'état de fonctionnement
H04W 24/06 - Réalisation de tests en trafic simulé
H04W 24/10 - Planification des comptes-rendus de mesures
H04W 52/24 - Commande de puissance d'émission [TPC Transmission power control] le TPC étant effectué selon des paramètres spécifiques utilisant le rapport signal sur parasite [SIR Signal to Interference Ratio] ou d'autres paramètres de trajet sans fil
H04W 72/542 - Critères d’affectation ou de planification des ressources sans fil sur la base de critères de qualité en utilisant la qualité mesurée ou perçue
H04W 74/0833 - Procédures d’accès aléatoire, p. ex. avec accès en 4 étapes
22.
Reduced Delays for Previously-Delayed Users in 5G and 6G
Communications between user devices and base stations in 5G/6G, and in earlier generations, often permit gross unfairness in allocating transmission opportunities. A user device that has previously been denied permission to transmit is more likely to be denied again, whereas in a fair system the longest-delayed user device would be granted uplink permission soonest (QOS and priorities being equal). Therefore, herein is disclosed a base station protocol in which each user device's delay history is recorded and, when that user device again requests permission to transmit, that user device is granted sooner than the other users who have not been delayed, or not as long as the most-delayed user device. In versions, the user devices may report their accumulated delay times, or the base station may count the number of delay events each user device has experienced.
H04W 74/0816 - Accès non planifié, p. ex. ALOHA utilisant une détection de porteuse, p. ex. accès multiple par détection de porteuse [CSMA] avec évitement de collision
H04W 28/24 - Négociation de l'agrément du niveau de service [SLA Service Level Agreement]Négociation de la qualité de service [QoS Quality of Service]
H04W 72/0446 - Ressources du domaine temporel, p. ex. créneaux ou trames
H04W 72/541 - Critères d’affectation ou de planification des ressources sans fil sur la base de critères de qualité en utilisant le niveau d’interférence
In 5G-Advanced, and especially 6G, message faulting is expected to be a major impediment due to phase noise and increased pathloss attenuation, as well as network crowding. Therefore, new procedures are disclosed enabling the receiver to identify and correct message faults without a retransmission and without using bulky FEC (forward error correction) bits. For example, the receiver can measure the “distance” of each received message element from the nearest modulation state, and thereby quantify the modulation quality, or suspiciousness, of each message element. To correct the message, the worst-modulated ones can be altered first, generally selecting the next-closest states since small distortions are more likely than large distortions. The result: rapid message recovery, internal to the receiver processor, without adding to the message size or the latency.
H04L 1/1809 - Protocoles de retransmission sélective
H04L 1/20 - Dispositions pour détecter ou empêcher les erreurs dans l'information reçue en utilisant un détecteur de la qualité du signal
H04L 27/02 - Systèmes à courant porteur à modulation d'amplitude, p. ex. utilisant la manipulation par tout ou rienModulation à bande latérale unique ou à bande résiduelle
H04L 27/34 - Systèmes à courant porteur à modulation de phase et d'amplitude, p. ex. en quadrature d'amplitude
H04L 27/36 - Circuits de modulationCircuits émetteurs
In 5G-Advanced and especially 6G, a primary concern is the increase in message faulting due to higher pathloss and phase noise at FR2 frequencies. Current methods for dealing with faults include packing the message with bulky error-correction (FEC) bits which are often ineffective, or automatically requesting a costly retransmission. As a substantially better alternative, the receiver may identify the specific fault locations and attempt an immediate repair by testing the modulation quality of each message element. For example, for a QAM-modulated message, the receiver can measure the I and Q branch deviations relative to predetermined levels, and the message element(s) with largest deviations is/are likely faulted. Alternatively, if the message is advantageously modulated according to the waveform amplitude and phase, the receiver can determine the amplitude and phase deviations relative to predetermined values. An AI model can greatly assist in the fault localization and in finding the corrected values.
H04L 1/1809 - Protocoles de retransmission sélective
H04L 1/20 - Dispositions pour détecter ou empêcher les erreurs dans l'information reçue en utilisant un détecteur de la qualité du signal
H04L 27/02 - Systèmes à courant porteur à modulation d'amplitude, p. ex. utilisant la manipulation par tout ou rienModulation à bande latérale unique ou à bande résiduelle
H04L 27/34 - Systèmes à courant porteur à modulation de phase et d'amplitude, p. ex. en quadrature d'amplitude
H04L 27/36 - Circuits de modulationCircuits émetteurs
Access to FR2 (high frequency bands) is essential for anticipated high-demand networking in 5G-Advanced and 6G systems. Unfortunately, phase noise is an unavoidable barrier, greatly limiting message reliability. Therefore, a low-cost solution is provided in which the transmitter (either base station or user device) transmits a special phase-tracking reference signal consisting of zero amplitude in one branch, and a predetermined non-zero amplitude in the other branch. For example, in QAM, the I-branch may be powered according to the maximum branch amplitude of the modulation scheme, and the Q-branch may have zero amplitude as transmitted. The receiver, on the other hand, generally measures a non-zero amplitude in the received Q branch due to phase noise, which rotates the I and Q branches into each other. The receiver can then determine the phase rotation angle precisely by measuring the non-zero amplitude in the Q branch, negating phase noise at negligible cost.
Networks operating at high frequencies in 5G and 6G may reduce the incidence of phase faulting by declaring that, above a specified frequency, messages are to be modulated according to multiplexed amplitude-phase modulation, instead of the QAM modulation generally used at lower frequencies. Multiplexed amplitude-phase modulation can provide larger phase margins than QAM of the same order, by arranging the modulation phase levels to be equally spaced-apart which they are not in QAM. For example, with 4 amplitude and 4 phase levels (16 states), the various modulation states can be separated by 90 degrees of phase, whereas in 16QAM the minimum phase separation is only 36.9 degrees, a serious problem at higher frequencies where phase noise predominates. In addition, QAM cannot accommodate non-square modulation tables, which are readily provided by amplitude-phase modulation, further enhancing fault-mitigation options.
Wireless message faults are an increasing problem n 5G and especially 6G due to network crowding and pathloss attenuation at higher frequencies, among other emergent problems. Therefore, disclosed are methods to diagnose and repair faulted messages by the receiver. For example, an AI program can determine the signal quality of each message element according to the modulation quality, SNR, and other waveform measurements, and thereby identify just a portion of the message that contains all of the likely faults. That portion can then be retransmitted instead of the entire message, saving substantial time. In addition, the AI program can select which message elements of the two versions has the best signal quality, and prepare a merged message from those best-received signals.
A wireless receiver in 5G and 6G can localize message faults by defining an “acceptance region” surrounding each of the predetermined allowed modulation states of a modulation scheme. Then, upon receiving a message, the receiver can measure (or calculate from the I and Q branches) the received amplitude and phase of the waveform signal in each message element. If the received amplitude and phase are within one of the acceptance regions, the message element according to the allowed state in that acceptance region. If the received amplitude and phase are not within the acceptance region of any of the allowed states, that message element is faulted. In addition, the receiver can increment an amplitude fault tally and a phase fault tally according to which parameter—amplitude or phase—is outside the acceptance regions, thereby greatly simplifying recovery of the message without a retransmission.
Mobile user devices, seeing a base station, can usually detect multiple base stations and access points capable of supporting communications in 5G or 6G. However, some of these may be crowded or distant, while others may be close enough to provide excellent reception. To assist the mobile user device in selecting an optimal base station for signal quality, the user device can include a network database that lists the locations and frequencies (and other data) about available base stations and access points. The user device can then use an artificial intelligence (AI) model, or an algorithm derived from AI, to select the base station or access point likely to provide the best signal quality while in transit. This would be much faster and simpler than the current alternative, of blindly searching through all the detectable base station sequentially.
H04W 60/04 - Rattachement à un réseau, p. ex. enregistrementSuppression du rattachement à un réseau, p. ex. annulation de l'enregistrement utilisant des événements déclenchés
H04W 74/0833 - Procédures d’accès aléatoire, p. ex. avec accès en 4 étapes
30.
AI-Based Selection of Network and Initial Access in 5G/6G
An unsolved problem in 5G and 6G is how a mobile user device can select the most appropriate base station or access point for communication. Currently, the user device is forced to do a tedious and time-consuming blind search, and even then is not guaranteed to have found the best one. Therefore, to assist user devices (especially reduced-capability IoT devices) in network discovery, disclosed herein is a “hailing” message that the user device can broadcast, and determine from the base station reply messages which one is closest, or has the best signal, or other criterion. The base stations, upon detecting the hailing message, can use an AI model to determine whether they can accommodate another user device (optionally with coordination among multiple access points for load-leveling), and if so, can transmit a reply message after a delay related to the received power in the hailing message.
H04W 74/0816 - Accès non planifié, p. ex. ALOHA utilisant une détection de porteuse, p. ex. accès multiple par détection de porteuse [CSMA] avec évitement de collision
31.
Sub-network topology for cybersecure 5G and 6G communications
Cybersecurity is a critical requirement for 5G-Advanced and 6G, in part due to the large attack surface represented by the exponentially increasing number of reduced-capability devices needing wireless service but intensely cost-constrained by their applications. Therefore, disclosed is a network topology that enables an unlimited number of basic sensor/actuator “end devices” to communicate, securely, with a user device of a managed 3GPP-compliant network. The user device or “hub” device serves as both manager and gateway, and more importantly, as a firewall preventing attackers from penetrating the managed network through the end devices. In addition, the end devices can obtain iron-clad protection by booting and operating from ROM only, and transferring only pre-configured replies up to their hub device. The topology enables the hub and end devices to perform the edge work largely autonomously, while insulating the managed network from cyberattacks.
An enhanced modulation scheme for 5G and 6G is disclosed in which amplitude modulation includes a zero-power level, which is readily recognized by the receiver as a special demarcation. This can be used, for example, to unambiguously indicate the start and end of a message, such as a downlink control message, which receivers are generally stressed to detect. The zero-power level can be just one branch of a QAM symbol, or the entire symbol, in various embodiments. Advantageously, the enhanced modulation scheme increases the throughput due to the larger number of encoded states, yet requires no increase in transmission power. In some embodiments, the throughput is increased yet the transmission power is actually reduced, with no loss in SNR. Other aspects are disclosed.
A receiver may use a trained AI model to recover a faulted 5G/6G message by interpreting the meaning or intent of the message by correlating the message content with one of the “expected” message types. For example, the AI model may consider changes to the message, for consistency with an associated error-detection code, thereby producing a series of candidate messages. The AI model can then determine a likelihood that each of the candidate messages is correct, in the context of the receiver (such as an action or condition of the receiver, or a planned activity of the receiver) or is commonly received in that context. For example, the AI model can be trained to recognize the expected messages or message types, and thereby indicate which candidate message has the highest likelihood of being correct. The AI model may also consider waveform parameters to identify likely faults.
In 5G-Advanced and 6G, due to the higher frequencies involved, phase noise is expected to be a major source of faults. Disclosed herein is a small (single resource element) phase-tracking reference signal that also provides an updated amplitude calibration. The compact phase-tracking reference signal, in QAM, includes a first branch at a maximum amplitude and an orthogonal second branch at either the maximum amplitude or zero amplitude, as transmitted. The receiver can readily determine a phase rotation angle according to a ratio of the two branch amplitudes, and also an amplitude calibration according to the vector magnitude of the received branches, thereby negating both amplitude noise and phase noise.
A first vehicle in traffic can use machine learning and artificial intelligence to detect an imminent collision with a second vehicle or other object. A well-trained AI algorithm can select a sequence of actions (braking, swerving, or accelerating—depending on the specific kinetics) to avoid the collision if possible, and to reduce or minimize the harm if unavoidable. With proper training, the AI model may also infer the intent and future actions of the second vehicle, as well as potential interference of other traffic agents. A good algorithm can also infer the intent of the driver of the first vehicle, for example based on prior driving habits. The AI algorithm may be implemented in a processor on the subject vehicle, potentially in communication with another processor at a fixed site such as a local access point or a central supercomputer. With super-fast AI solutions, lives will be saved!
B62D 6/00 - Dispositions pour la commande automatique de la direction en fonction des conditions de conduite, qui sont détectées et pour lesquelles une réaction est appliquée, p. ex. circuits de commande
B60Q 9/00 - Agencement ou adaptation des dispositifs de signalisation non prévus dans l'un des groupes principaux
B60W 10/04 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des ensembles de propulsion
B60W 10/18 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de freinage
B60W 10/184 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de freinage avec des freins de roues
B60W 10/20 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de direction
B60W 30/085 - Ajustant automatiquement la position du véhicule en préparation de la collision, p. ex. en freinant pour piquer du nez
B60W 30/09 - Entreprenant une action automatiquement pour éviter la collision, p. ex. en freinant ou tournant
B60W 30/095 - Prévision du trajet ou de la probabilité de collision
B60W 50/12 - Limitation de la possibilité de commande du conducteur en fonction de l'état du véhicule, p. ex. moyens de verrouillage des grandeurs d'entrées pour éviter un fonctionnement dangereux
B60W 50/14 - Moyens d'information du conducteur, pour l'avertir ou provoquer son intervention
B60W 50/16 - Signalisation tactile au conducteur, p. ex. vibration ou augmentation de la résistance sur le volant ou sur la pédale d'accélérateur
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p. ex. utilisant des pilotes automatiques
G05D 1/617 - Sécurité ou protection, p. ex. définition de zones de protection autour d’obstacles ou évitement de zones dangereuses
For synchronizing user devices to the base station of a 5G or 6G network, the base station can transmit brief prepared signals at a pre-scheduled time and frequency. All of the user devices in the network can then synchronize simultaneously, using amplitude measurements with standard signal processing. The user devices can thereby avoid the complex and time-consuming measurements of prior art. This simplified synchronization procedure may be especially relevant for reduced-capability IoT devices. Examples are provided in which each user device can measure a ratio of amplitudes or energy values in sequential symbol-times as determined by the local user device clock, and compare to the expected ratio as determined by the base station clock. Any deviation in the ratio indicates a timing offset, which the user devices can then use to precisely synchronize the local clock.
A vehicle may include a number of collision warning indicators that also indicate a direction of the imminent collision. For example, the vehicle may include sonic beepers or flashing lights, positioned around the interior or exterior of the vehicle, and activated individually to indicate the direction of attack. If the collision is to the left, right, front, or back of the vehicle, the indicator in the same direction can be activated, thereby informing the driver of the imminent collision as well as the approach direction. Alternatively, the vehicle may include two or more haptic emitters, such as vibrating pads, positioned to the left and right of the driver's hands or seat. With knowledge of the direction of the threat, the driver may be able to avoid or mitigate the imminent collision, and the other passengers in the vehicle may be able to brace themselves to better survive the collision.
Current methods for synchronizing user devices with the base station of a 5G/6G network require multiple exchanges with each user device, consuming limited resources. Disclosed herein are systems and methods for generating and then detecting precision-timing timestamp points. Importantly, the timestamp points can be used by all of the user devices simultaneously, instead of just one at a time. In a first embodiment, the timestamp includes three resource elements with a first modulation (amplitude or phase) in the first and third resource elements, and a different modulation in the middle one. In a second embodiment, the base station transmits a first signal in the first half of a single resource element, and a different signal modulation in the second half. In either case, the user devices can receive the signal, determine the time of interface between the modulation states, and thereby determine the symbol boundaries according to the base station.
A base station can cause a multitude of user devices in a network to be synchronized with the base station's clock using an ultra-lean low-complexity procedure in 5G or 6G. On a predetermined interval, the base station can transmit a timing signal in the guard-space of a predetermined resource element. The timing signal is a 180-degree phase reversal of the cyclic prefix centered in the guard-space. Each user device can receive the timing signal, determine how far the received timestamp point is from the middle of the guard-space (as viewed by the user device), and thereby determine a timing error between the user device clock and the base station clock, and correct the user device clock accordingly. In addition, the user device can average the timing adjustments over a number of instances, thereby determining a frequency offset if the average differs significantly from zero, and thereby adjust the clock frequency.
An autonomous or semi-autonomous vehicle can detect an imminent collision according to sensor data and responsively select an action or a sequence of actions to avoid the collision if avoidable, and to reduce or minimize the harm of the collision if unavoidable. An artificial intelligence model may be used to process the sensor data, detect the imminent collision, and select the collision avoidance action or actions, or the harm-reduction or harm-minimization action or actions. For example, when the collision is considered unavoidable, the vehicle may apply the brakes to reduce the vehicle's speed and therefore, the severity of the impact. When the collision is considered avoidable, the vehicle may automatically apply steering to avoid the potential collision, such as when the vehicle is departing a lane and may collide with a vehicle traveling in the same or opposite direction.
B60W 30/09 - Entreprenant une action automatiquement pour éviter la collision, p. ex. en freinant ou tournant
B60Q 9/00 - Agencement ou adaptation des dispositifs de signalisation non prévus dans l'un des groupes principaux
B60W 10/04 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des ensembles de propulsion
B60W 10/18 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de freinage
B60W 10/184 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de freinage avec des freins de roues
B60W 10/20 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de direction
B60W 30/085 - Ajustant automatiquement la position du véhicule en préparation de la collision, p. ex. en freinant pour piquer du nez
B60W 30/095 - Prévision du trajet ou de la probabilité de collision
B60W 50/12 - Limitation de la possibilité de commande du conducteur en fonction de l'état du véhicule, p. ex. moyens de verrouillage des grandeurs d'entrées pour éviter un fonctionnement dangereux
B60W 50/14 - Moyens d'information du conducteur, pour l'avertir ou provoquer son intervention
B60W 50/16 - Signalisation tactile au conducteur, p. ex. vibration ou augmentation de la résistance sur le volant ou sur la pédale d'accélérateur
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p. ex. utilisant des pilotes automatiques
Human drivers generally cannot plan a collision evasion maneuver in the brief interval before impact, other than simply slamming on the brakes and hoping for the best. Often the collision could have been avoided by swerving or other sequence of actions. Therefore, improved collision avoidance and mitigation procedures are disclosed, based on a well-trained artificial intelligence (AI) model that takes over the accelerator, brake, and steering in an emergency. With fast electronic reflexes and AI-based computational power, the AI model can find a more effective avoidance maneuver, or at least an action that would minimize the harm (for example, by swerving to miss the passenger compartment). The AI model can then implement the sequence instantly, without fear or hesitation. The result—fewer collisions and less fatality on our highways.
B60W 30/09 - Entreprenant une action automatiquement pour éviter la collision, p. ex. en freinant ou tournant
B60Q 9/00 - Agencement ou adaptation des dispositifs de signalisation non prévus dans l'un des groupes principaux
B60W 10/04 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des ensembles de propulsion
B60W 10/18 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de freinage
B60W 10/184 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de freinage avec des freins de roues
B60W 10/20 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de direction
B60W 30/085 - Ajustant automatiquement la position du véhicule en préparation de la collision, p. ex. en freinant pour piquer du nez
B60W 30/095 - Prévision du trajet ou de la probabilité de collision
B60W 50/12 - Limitation de la possibilité de commande du conducteur en fonction de l'état du véhicule, p. ex. moyens de verrouillage des grandeurs d'entrées pour éviter un fonctionnement dangereux
B60W 50/14 - Moyens d'information du conducteur, pour l'avertir ou provoquer son intervention
B60W 50/16 - Signalisation tactile au conducteur, p. ex. vibration ou augmentation de la résistance sur le volant ou sur la pédale d'accélérateur
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p. ex. utilisant des pilotes automatiques
G05D 1/617 - Sécurité ou protection, p. ex. définition de zones de protection autour d’obstacles ou évitement de zones dangereuses
Base stations and user devices in 5G and 6G networks can save enormous amounts of power, while minimizing background generation, by directing narrow transmission and reception beams toward each other. To optimize those beam directions, and their lateral beam widths, and the frequency and power transmitted, a small set of test signals can be appended to each message, and a feedback message selecting the best-received test signal can be appended to the acknowledgement. In this way, the base station can develop a custom set of beam parameters optimized for each user device, and each user device can maintain its uplink beam squarely toward the base station. Result: higher signal quality per watt transmitted, fewer faults and retransmissions, and improved network operations overall.
H04B 7/06 - Systèmes de diversitéSystèmes à plusieurs antennes, c.-à-d. émission ou réception utilisant plusieurs antennes utilisant plusieurs antennes indépendantes espacées à la station d'émission
H04B 17/373 - Prédiction des paramètres de qualité d’un canal
H04B 17/382 - SurveillanceTests de canaux de propagation pour l’attribution de ressources, le contrôle d’accès ou le transfert
H04W 24/02 - Dispositions pour optimiser l'état de fonctionnement
H04W 24/06 - Réalisation de tests en trafic simulé
H04W 24/10 - Planification des comptes-rendus de mesures
H04W 52/24 - Commande de puissance d'émission [TPC Transmission power control] le TPC étant effectué selon des paramètres spécifiques utilisant le rapport signal sur parasite [SIR Signal to Interference Ratio] ou d'autres paramètres de trajet sans fil
H04W 72/044 - Affectation de ressources sans fil sur la base du type de ressources affectées
H04W 72/542 - Critères d’affectation ou de planification des ressources sans fil sur la base de critères de qualité en utilisant la qualité mesurée ou perçue
H04W 74/0833 - Procédures d’accès aléatoire, p. ex. avec accès en 4 étapes
43.
Operating a vehicle according to an artificial intelligence model
Vehicles can be operated according to an artificial intelligence model contained in an on-board processor. The AI model can analyze sensor data, such as visible or infrared images of traffic, and determine when a collision is possible, whether it has become imminent, and whether the collision is avoidable or unavoidable using sequences of accelerations, braking, and steering. The AI model can also select the most appropriate sequence of actions from a large plurality of calculated sequences to avoid the collision if avoidable, and to minimize the harm if unavoidable. The AI model can also cause a processor to actuate linkages connected to the throttle (or electric power control), brakes (or regenerative braking), and steering to implement the selected sequence of actions. Thus the collision can be avoided or mitigated by an ADAS system or a fully autonomous vehicle.
B60W 30/09 - Entreprenant une action automatiquement pour éviter la collision, p. ex. en freinant ou tournant
B60Q 9/00 - Agencement ou adaptation des dispositifs de signalisation non prévus dans l'un des groupes principaux
B60W 10/04 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des ensembles de propulsion
B60W 10/18 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de freinage
B60W 10/184 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de freinage avec des freins de roues
B60W 10/20 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de direction
B60W 30/085 - Ajustant automatiquement la position du véhicule en préparation de la collision, p. ex. en freinant pour piquer du nez
B60W 30/095 - Prévision du trajet ou de la probabilité de collision
B60W 50/12 - Limitation de la possibilité de commande du conducteur en fonction de l'état du véhicule, p. ex. moyens de verrouillage des grandeurs d'entrées pour éviter un fonctionnement dangereux
B60W 50/14 - Moyens d'information du conducteur, pour l'avertir ou provoquer son intervention
B60W 50/16 - Signalisation tactile au conducteur, p. ex. vibration ou augmentation de la résistance sur le volant ou sur la pédale d'accélérateur
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p. ex. utilisant des pilotes automatiques
G05D 1/617 - Sécurité ou protection, p. ex. définition de zones de protection autour d’obstacles ou évitement de zones dangereuses
Disclosed is a “connectivity matrix” that wireless entities (vehicles, fixed assets, etc.) can display indicating the 5G/6G wireless address of the entity. Other wireless devices can then image the connectivity matrix, determine the wireless address, and then communicate in sidelink, on frequencies allocated for ad-hoc networking. Alternatively, the two entities can communicate through a local base station, on managed channels, using the displayed wireless address. The matrix can provide additional information, such as the frequency, bandwidth, and modulation scheme favored by the entity. Alternatively, the matrix can provide a key code maintained by a central authority, so that a second wireless entity can read the code and request the associated wireless address (and frequency, bandwidth, etc.) from the central authority. By either method, the two wireless entities can then communicate explicitly thereafter.
H04W 8/26 - Adressage ou numérotation de réseau pour support de mobilité
G01S 5/00 - Localisation par coordination de plusieurs déterminations de direction ou de ligne de positionLocalisation par coordination de plusieurs déterminations de distance
G01S 19/25 - Acquisition ou poursuite des signaux émis par le système faisant intervenir des données d'assistance reçues en provenance d'un élément coopérant, p. ex. un GPS assisté
G06K 19/06 - Supports d'enregistrement pour utilisation avec des machines et avec au moins une partie prévue pour supporter des marques numériques caractérisés par le genre de marque numérique, p. ex. forme, nature, code
G08G 1/01 - Détection du mouvement du trafic pour le comptage ou la commande
G08G 1/017 - Détection du mouvement du trafic pour le comptage ou la commande par identification des véhicules
G08G 1/04 - Détection du mouvement du trafic pour le comptage ou la commande utilisant des détecteurs optiques ou ultrasonores
G08G 1/056 - Détection du mouvement du trafic pour le comptage ou la commande avec des dispositions pour distinguer la direction de circulation
G08G 1/09 - Dispositions pour donner des instructions variables pour le trafic
G08G 1/137 - Systèmes de commande du trafic pour véhicules routiers indiquant la position de véhicules, p. ex. de véhicules à horaire déterminé à l'intérieur du véhicule l'indicateur étant sous la forme d'une carte
H04W 4/029 - Services de gestion ou de suivi basés sur la localisation
H04W 4/40 - Services spécialement adaptés à des environnements, à des situations ou à des fins spécifiques pour les véhicules, p. ex. communication véhicule-piétons
H04W 4/46 - Services spécialement adaptés à des environnements, à des situations ou à des fins spécifiques pour les véhicules, p. ex. communication véhicule-piétons pour la communication de véhicule à véhicule
H04W 4/90 - Services pour gérer les situations d’urgence ou dangereuses, p. ex. systèmes d’alerte aux séismes et aux tsunamis
45.
Eliminating unnecessary downlink control messages in 5G and 6G
For more efficient use of the limited bandwidth in 5G and 6G communications, and to enable longer battery life in remote user devices, the user device can request that unnecessary downlink control messages be withheld. Instead, a custom search-space can be assigned to the user device, such that all downlink data messages will begin in one of the resource elements of the custom search-space, thereby greatly simplifying the user device's task of detecting its incoming messages in a stream of unrelated transmissions. In addition, the user device can request that the user device's identification code, and optionally the length of the data message, be prepended to the data message, for further assistance to low-cost reduced-capability user devices that do not require low latency.
H04L 5/00 - Dispositions destinées à permettre l'usage multiple de la voie de transmission
H04W 72/0446 - Ressources du domaine temporel, p. ex. créneaux ou trames
H04W 72/0453 - Ressources du domaine fréquentiel, p. ex. porteuses dans des AMDF [FDMA]
H04W 72/1273 - Jumelage du trafic à la planification, p. ex. affectation planifiée ou multiplexage de flux de flux de données en liaison descendante
H04W 72/23 - Canaux de commande ou signalisation pour la gestion des ressources dans le sens descendant de la liaison sans fil, c.-à-d. en direction du terminal
46.
Rapid, automatic, AI-based collision avoidance and mitigation preliminary
Disclosed are systems and methods for autonomous vehicles and vehicles with automatic driver-assistance systems (ADAS) to automatically detect an imminent collision, determine whether the collision is avoidable or unavoidable, and plot a course minimizing the hazard using an artificial intelligence (AI) model. For example, a collision is avoidable if the vehicle can avoid it by steering, braking, and/or accelerating in a particular sequence. The AI model finds the best sequence for collision avoidance, and if that is not possible, it finds the best sequence for minimizing the harm. The harm is based on an estimated number of fatalities, injuries, and property damage predicted to be caused in the collision. The AI-based situation analysis and sequence selection are directly applicable to human-driven vehicles with an emergency-intervention ADAS system, as well as fully autonomous vehicles. With fast electronic reflexes and multi-sensor situation awareness, the AI model can save lives on the highway.
B60W 30/08 - Anticipation ou prévention de collision probable ou imminente
B60Q 9/00 - Agencement ou adaptation des dispositifs de signalisation non prévus dans l'un des groupes principaux
B60W 10/04 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des ensembles de propulsion
B60W 10/18 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de freinage
B60W 10/184 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de freinage avec des freins de roues
B60W 10/20 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de direction
B60W 30/085 - Ajustant automatiquement la position du véhicule en préparation de la collision, p. ex. en freinant pour piquer du nez
B60W 30/09 - Entreprenant une action automatiquement pour éviter la collision, p. ex. en freinant ou tournant
B60W 30/095 - Prévision du trajet ou de la probabilité de collision
B60W 50/12 - Limitation de la possibilité de commande du conducteur en fonction de l'état du véhicule, p. ex. moyens de verrouillage des grandeurs d'entrées pour éviter un fonctionnement dangereux
B60W 50/14 - Moyens d'information du conducteur, pour l'avertir ou provoquer son intervention
B60W 50/16 - Signalisation tactile au conducteur, p. ex. vibration ou augmentation de la résistance sur le volant ou sur la pédale d'accélérateur
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p. ex. utilisant des pilotes automatiques
Corrupted messages in 5G and 6G are usually discarded, leading to a retransmission with its added costs, delays, and background generation. Therefore, disclosed herein are methods for a wireless receiver to determine which message elements are faulted, and in many cases to correct them, based on parameters of the waveform signal in each message element. Multiple parameters may be combined for better sensitivity to the fault condition. For example, the indicator parameters may be the modulation deviation of each message element, its amplitude or phase noise level, characteristic interference patterns between symbol-times, a polarization anomaly, a frequency offset, or combinations of these. After localizing the likely faulted message elements, the receiver may be able to recover the message by correcting the waveform signal or the demodulation value, thereby saving time and energy at near zero cost.
A network architecture is disclosed for intrinsic cybersecurity of low-cost, low-complexity IoT devices such as single-task sensors and actuators. The IoT devices are configured in a star topology sub-network, in which a number of IoT “end devices” communicate exclusively with a single “hub device” that manages the sub-network. The hub device is also connected to a larger network such as a 5G or 6G network. Each end device makes a measurement or operates an actuator on instructions from the hub device, and transmits data results back to the hub device, which then transmits the results (or a summary thereof) up to the base station of the larger network. Thus the larger network is relieved of responsibility for routine managing of the end devices, since the hub device does that. Also the larger network is protected from cyberattacks by configuring each end device to boot and execute from ROM, and other features described herein.
A method for modulating and demodulating 5G and 6G messages is disclosed, in which the message elements are configured with a large phase margin between adjacent modulation states, and are demodulated in a way that preserves the large phase margins. Phase noise, a major problem at high frequencies, scrambles adjacent modulation states, causing message faults. The disclosed modulation schemes and demodulation methods accommodate such phase noise without faulting, by providing a wide acceptance range for phase. Hence substantial phase noise can be accommodated without changing the demodulated state, thereby avoiding a message fault. The rate of message faults due to phase demodulation errors may be substantially decreased, and message faults at higher frequencies may be reduced, according to some embodiments. Strategies for minimizing amplitude faults are also disclosed.
5G and especially 6G are susceptible to phase faults due to rapid phase fluctuations, usually in the local oscillator of the user device. Low-cost IoT applications that 6G is intended to serve may be impractical unless phase noise mitigation can be applied on each uplink and downlink message. Accordingly, a single-branch phase-tracking reference is disclosed occupying just a single resource element, in which one quadrature branch is transmitted with a predetermined maximum modulation amplitude, and the other branch has zero amplitude. The receiver can then quantify the phase noise (or the phase rotation angle) according to a ratio of the as-received branch amplitudes, and mitigate a concurrent message by de-rotating each message element by the same phase angle, thereby restoring high reliability at high frequencies at negligible cost.
Noise and interference in 5G/6G messages can be corrected by including a predetermined reference signal in the guard space of each resource element of the message. Even highly variable noise and interference, fluctuating in time and in frequency, can be negated when the demodulation reference signals are positioned within each resource element of the message. In addition, if the guard-space reference signal varies excessively between resource elements, the associated message element can be flagged as likely faulted. Since the guard space is already included in the transmission, no additional resources or transmission power are required. Methods are also disclosed for retaining the signal processing features of prior-art guard space signals such as a cyclic prefix, at low to no cost.
Message faults are caused by network crowding and signal fading at high frequencies of 5G and 6G. Current error-detection and correction algorithms are computationally demanding, especially for new low-cost reduced-capability IoT devices. Disclosed are methods for (a) determining whether a message is faulted using a compact error-detection code, (b) localizing the most likely faulted message element(s) according to the waveform signal, and (c) determining the likely corrected version by back-calculating from the error-detection code. Other versions include testing various modulation substitutions for the most suspicious message elements, having the worst signal quality. The waveform parameters may include a deviation from an average amplitude, phase, frequency, or polarization, as well as an amount of amplitude variation and phase variation within the message element. Identification of the most likely faulted message elements may enable recovery of the message without a costly retransmission.
Message faulting is an increasing problem in 5G and future 6G due to network crowding, receiver motion, signal fading at higher frequencies, and greater phase-noise sensitivity. Disclosed herein are methods for analyzing waveform features of the received signal using artificial intelligence, and identifying the likely faulted message elements according to correlations of those waveform features. For example, after demodulating, the receiver can identify a subset of message elements that are all demodulated according to the same modulation level, and can measure a signal parameter for each message element in the subset. The processor can then average the deviations in the subset, and compare those message elements to the average for the subset. If one of the message elements shows an anomalously large deviation from the average, that message element is likely faulted.
Message faulting is a critical unsolved problem for 5G and 6G. Disclosed herein is a method for combining an AI-based analysis of the waveform data of each message element, plus the constraint of an associated error-detection code (such as a CRC or parity construct of the correct message) to localize and, in many cases, correct a limited number of faults per message, without a retransmission. For example, the waveform data may include a deviation of the amplitude or phase of a particular message element, relative to an average of the amplitudes or phases of the other message elements that have the same demodulation value. The outliers are thereby exposed as the most likely faulted message elements. In addition, using the error-detection code, the AI model can determine the most likely corrected message, thereby avoiding retransmission delays and power usage and other costs.
Most automatic driver-assistance systems, including allegedly autonomous driving systems, fail to react to certain hazard cues that human drivers instinctively notice. Chief among those cues is the sudden illumination of the brake lights in the vehicle ahead. Admittedly, it is difficult for software to discriminate between brake lights, turn signal lights, and running lights—but that is what safety requires. Disclosed herein are methods and systems for processors on vehicles to interpret sensor images, detect brake lights ahead, and take proper avoidance action such as braking and swerving. The proper strategy may be decided according to the relative speed of the two vehicles and their distance apart when the brake lights come on, among other factors. With such foresighted collision mitigation capability, autonomous and semi-autonomous vehicles may be able to save many lives due to unnecessary collisions in traffic.
B60W 10/184 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de freinage avec des freins de roues
B60W 30/085 - Ajustant automatiquement la position du véhicule en préparation de la collision, p. ex. en freinant pour piquer du nez
G05D 1/02 - Commande de la position ou du cap par référence à un système à deux dimensions
B60W 50/12 - Limitation de la possibilité de commande du conducteur en fonction de l'état du véhicule, p. ex. moyens de verrouillage des grandeurs d'entrées pour éviter un fonctionnement dangereux
B60W 50/14 - Moyens d'information du conducteur, pour l'avertir ou provoquer son intervention
B60W 10/18 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de freinage
B60W 50/16 - Signalisation tactile au conducteur, p. ex. vibration ou augmentation de la résistance sur le volant ou sur la pédale d'accélérateur
56.
Traffic collison avoidance or minimization by supercomputer assist in 5G/6G
Traffic collisions involving autonomous vehicles can be greatly reduced by timely initiation of evasive action. However, calculating a suitable sequence of actions capable of avoiding or minimizing the collision may require the speed of a supercomputer. Therefore, disclosed is a method for the autonomous vehicle to transmit an emergency message with sensor data to a nearby access point in 5G or 6G, and the access point can forward the data to a supercomputer trained in collision avoidance. The supercomputer, millions or billions of times faster than vehicle computers, explores many sequences of actions and selects the one most likely to avoid the collision or if unavoidable, the sequence of actions that results in the least harm. Again using an exclusive channel, the supercomputer and the access point can relay the selected sequence to the autonomous vehicle, for immediate collision avoidance or harm minimization.
B60W 10/04 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des ensembles de propulsion
B60W 10/18 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de freinage
B60W 10/20 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de direction
B60W 30/08 - Anticipation ou prévention de collision probable ou imminente
B60W 30/09 - Entreprenant une action automatiquement pour éviter la collision, p. ex. en freinant ou tournant
G06Q 50/26 - Services gouvernementaux ou services publics
H04W 4/44 - Services spécialement adaptés à des environnements, à des situations ou à des fins spécifiques pour les véhicules, p. ex. communication véhicule-piétons pour la communication entre véhicules et infrastructures, p. ex. véhicule à nuage ou véhicule à domicile
H04L 67/1097 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau pour le stockage distribué de données dans des réseaux, p. ex. dispositions de transport pour le système de fichiers réseau [NFS], réseaux de stockage [SAN] ou stockage en réseau [NAS]
H04W 84/04 - Réseaux à grande échelleRéseaux fortement hiérarchisés
57.
Procedures for efficiently defaulting QAM messages in 5G and 6G
Message faults are expected to be a major impediment to 5G and future 6G throughput. The disclosed procedures enable a wireless receiver to recover many types of message faults based on the demodulation quality of each message element, among other diagnostic tests, and then to recover the correct message either by calculation (based on an embedded error-detection code) or by substitution (based on a search of all other modulation states in place of the faulted message elements). The method also includes determining, according to the modulation quality, when there are too many faults to efficiently mitigate, in which case a retransmission of just the affected portion is requested. The receiver can then merge the two versions of the message, selecting the better-quality message element at each position, and thereby correct the faulted message versions.
H04L 1/1809 - Protocoles de retransmission sélective
H04L 1/20 - Dispositions pour détecter ou empêcher les erreurs dans l'information reçue en utilisant un détecteur de la qualité du signal
H04L 27/02 - Systèmes à courant porteur à modulation d'amplitude, p. ex. utilisant la manipulation par tout ou rienModulation à bande latérale unique ou à bande résiduelle
H04L 27/26 - Systèmes utilisant des codes à fréquences multiples
H04L 27/34 - Systèmes à courant porteur à modulation de phase et d'amplitude, p. ex. en quadrature d'amplitude
H04L 27/36 - Circuits de modulationCircuits émetteurs
58.
Deterministic low-complexity beam alignment for 5G and 6G users
5G and especially 6G are built around beamed transmissions and receptions, but aligning the beams toward the intended recipient is currently an expensive and complex process that reduced-capability devices may have difficulty performing. Therefore, an improved beam alignment process is disclosed, involving “triangle” beams. A triangle beam is a wide transmission beam that is arranged to be high-power at one side and low-power at the other side, tapering monotonically between the two angles. A user device can detect the triangle beam and measure the received amplitude or power level. By comparing to the amplitude of a previous transmission, the user device can determine its angle relative to the base station. The user device can then transmit directional beams toward the base station, and can also inform the base station of the angle so that they both can use well-directed transmission and reception beams. Many other aspects are disclosed.
H04B 7/06 - Systèmes de diversitéSystèmes à plusieurs antennes, c.-à-d. émission ou réception utilisant plusieurs antennes utilisant plusieurs antennes indépendantes espacées à la station d'émission
G01S 3/02 - Radiogoniomètres pour déterminer la direction d'où proviennent des ondes infrasonores, sonores, ultrasonores ou électromagnétiques ou des émissions de particules sans caractéristiques de direction utilisant des ondes radio
H04W 16/28 - Structures des cellules utilisant l'orientation du faisceau
Additional information can be packed into each message element of a 5G/6G message by varying the amplitude of the signal within the symbol-time of the message element. For example, the difference between the amplitude at the beginning and ending of the symbol-time may encode additional bits, thereby providing higher information density in each transmission. The amplitude variation may be abrupt, such as a sudden change from the first amplitude value to the second amplitude value in the middle of the symbol-time, or it may be a gradual linear ramp spanning the symbol-time. In either case, the modulation scheme may include amplitude variation levels as well as the amplitude levels themselves, thereby providing a larger modulation space and hence shorter messages. Effects on crosstalk and frequency offset due to the amplitude variation, and their mitigation, are also disclosed.
In traffic, vehicle safety generally depends on the relative separation between two vehicles, and not at all on their absolute geographical positions. Therefore, methods are disclosed for determining the relative separation differentially. Two vehicles simultaneously acquire the same satellite signals, reduce the signals to data, and then transmit the data, preferably with fast 5G or 6G, to one of the vehicles or to a roadside access point. A computer then analyzes the data based on differences between the two sets of signals, thereby determining the separation distance and angle between the two vehicles. Other vehicles within range can do the same. The relative locations of all the participating vehicles can then be broadcast, in the form of a table or a map, to all the vehicles in proximity. Improved position measurements can enable collision avoidance and harm minimization in traffic.
H04W 8/26 - Adressage ou numérotation de réseau pour support de mobilité
G06K 19/06 - Supports d'enregistrement pour utilisation avec des machines et avec au moins une partie prévue pour supporter des marques numériques caractérisés par le genre de marque numérique, p. ex. forme, nature, code
H04W 4/029 - Services de gestion ou de suivi basés sur la localisation
H04W 4/90 - Services pour gérer les situations d’urgence ou dangereuses, p. ex. systèmes d’alerte aux séismes et aux tsunamis
H04W 4/40 - Services spécialement adaptés à des environnements, à des situations ou à des fins spécifiques pour les véhicules, p. ex. communication véhicule-piétons
G01S 5/00 - Localisation par coordination de plusieurs déterminations de direction ou de ligne de positionLocalisation par coordination de plusieurs déterminations de distance
G01S 19/25 - Acquisition ou poursuite des signaux émis par le système faisant intervenir des données d'assistance reçues en provenance d'un élément coopérant, p. ex. un GPS assisté
H04W 4/46 - Services spécialement adaptés à des environnements, à des situations ou à des fins spécifiques pour les véhicules, p. ex. communication véhicule-piétons pour la communication de véhicule à véhicule
G08G 1/01 - Détection du mouvement du trafic pour le comptage ou la commande
G08G 1/017 - Détection du mouvement du trafic pour le comptage ou la commande par identification des véhicules
G08G 1/04 - Détection du mouvement du trafic pour le comptage ou la commande utilisant des détecteurs optiques ou ultrasonores
G08G 1/056 - Détection du mouvement du trafic pour le comptage ou la commande avec des dispositions pour distinguer la direction de circulation
G08G 1/09 - Dispositions pour donner des instructions variables pour le trafic
G08G 1/137 - Systèmes de commande du trafic pour véhicules routiers indiquant la position de véhicules, p. ex. de véhicules à horaire déterminé à l'intérieur du véhicule l'indicateur étant sous la forme d'une carte
Message faults are expected to become a major problem for next-generation 5G/6G networks, due to signal fading, high backgrounds, and high density of users. Disclosed are methods to modulate and demodulate messages to optimize noise margins, greatly enhancing reliability at negligible cost, according to some embodiments. A transmitter can modulate a message using amplitude-phase modulation, yet a receiver can conveniently receive and process the signals according to separate in-phase (I) and quad-phase (Q) branches, that is, according to QAM. The receiver can then convert the I and Q values to the original waveform amplitude and phase mathematically, and then demodulate those values using predetermined amplitude and phase levels as provided by a proximate demodulation reference. By converting the as-received QAM values to the as-transmitted amplitude-phase values, the receiver can thereby avoid many noise vulnerabilities inherent in QAM-modulated messages, and thereby obtain the full noise margins provided by amplitude-phase modulation.
In busy 5G and 6G networks, precise timing and synchronization are key to maintaining throughput with low fault rates. Disclosed are systems and methods for adjusting each user device's clock for proper reception, including downlink propagation delays, uplink propagation delays, round-trip propagation delays, and Doppler shifts, individually for each user device, and including any uplink/downlink asymmetries. The clock adjustment and timing advance of each user device is based on a predetermined transmission schedule for timing signals, broadcast by the base station. The Doppler shift is measured by the base station, according to uplink timing signals, and communicated to the user device in a single final timing signal. The single final timing signal is either frequency-shifted by the measured Doppler shift, or delayed proportional to the Doppler shift, either of which indicates, to the user device, how to apply the correct timing to future uplink messages.
Due to the rapid cadence of messages in 5G and expected 6G networks, and rapid variations in the background and interference profile, real-time management decision-making is increasingly impractical for even experienced network operators. Therefore, means are disclosed for AI-based systems to provide support and assistance, including when appropriate to adjust network operational parameters autonomously. After suitable training, processors in a base station, or more preferably a core network facility managing multiple cells, can respond more quickly and more accurately than humans to rapid random changes in demand, interference, intrusion, and emergencies. Disclosed also are means for user devices to keep the base station and the AI management model informed of signal quality upon each uplink message (such as acknowledgements) using vary brief, multiplexed feedback messages responsive to downlink test signals.
H04B 7/06 - Systèmes de diversitéSystèmes à plusieurs antennes, c.-à-d. émission ou réception utilisant plusieurs antennes utilisant plusieurs antennes indépendantes espacées à la station d'émission
H04B 17/373 - Prédiction des paramètres de qualité d’un canal
H04B 17/382 - SurveillanceTests de canaux de propagation pour l’attribution de ressources, le contrôle d’accès ou le transfert
H04W 24/02 - Dispositions pour optimiser l'état de fonctionnement
H04W 24/06 - Réalisation de tests en trafic simulé
H04W 24/10 - Planification des comptes-rendus de mesures
H04W 52/24 - Commande de puissance d'émission [TPC Transmission power control] le TPC étant effectué selon des paramètres spécifiques utilisant le rapport signal sur parasite [SIR Signal to Interference Ratio] ou d'autres paramètres de trajet sans fil
H04W 72/044 - Affectation de ressources sans fil sur la base du type de ressources affectées
H04W 72/542 - Critères d’affectation ou de planification des ressources sans fil sur la base de critères de qualité en utilisant la qualité mesurée ou perçue
H04W 74/0833 - Procédures d’accès aléatoire, p. ex. avec accès en 4 étapes
64.
Precision synchronization using amplitude measurements in 5G and 6G
Prior art includes complex clock synchronization in 5G and 6G based on precision time measurements and multiple message exchanges. Disclosed is a simpler synchronization procedure suitable for reduced-capability receivers as well as high-performance users. The base station can transmit a brief signal on a specific subcarrier, surrounded fore and aft by silent periods, and the receiver can measure the signals in the silent periods to detect intrusion of the signal into one or the other silent periods, thereby indicating a timing offset. Alternatively, the base station can transmit a brief signal spanning an interface between subsequent symbol-times, and the receiver can measure the energy received in the two symbol-times, thereby detecting an offset. In either case, and other versions disclosed, the receiver can calculate the size and direction of the clock offset by amplitude measurements, and apply a correction without further communications between the user device and the base station.
In a 5G or 6G wireless network, the base station can assist user devices in aligning their beams toward the base station, and can align downlink beams toward each of the user devices, by exchanging brief test signals followed by brief encoded feedback messages. The test signals may be transmitted in different directions, or with different beam widths, or with other transmission parameters, thereby enabling the user device to select the best version and reply accordingly. In addition, the user device can determine, from information in a message accompanying the test signals, a direction or angle of each test signal, and thereby determine the correct direction toward the base station by adding 180 degrees, without further experimentation. For compact messaging, a zero-power state may be included in the modulation scheme, thereby providing an efficient format for selecting which beam or which direction is best received.
H04B 7/06 - Systèmes de diversitéSystèmes à plusieurs antennes, c.-à-d. émission ou réception utilisant plusieurs antennes utilisant plusieurs antennes indépendantes espacées à la station d'émission
H04W 24/06 - Réalisation de tests en trafic simulé
H04W 24/10 - Planification des comptes-rendus de mesures
H04W 52/24 - Commande de puissance d'émission [TPC Transmission power control] le TPC étant effectué selon des paramètres spécifiques utilisant le rapport signal sur parasite [SIR Signal to Interference Ratio] ou d'autres paramètres de trajet sans fil
66.
Robot cooperation by simultaneous infrared and 5G/6G wireless signals
Cooperation among robots is a necessary feature of advanced manufacturing and many other applications. The invention relates to systems and methods for robots to identify each other using simultaneous infrared pulses and wireless messages in 5G or 6G. The wireless message can indicate the wireless address of the transmitting robot, and the infrared signal can indicate which robot, among many, is transmitting the wireless message. Thus the other robots can compare the arrival direction of the infrared signal with an optical image, and thereby localize the transmitting robot. The robots can then begin cooperative actions thereafter. The procedures are suitable for mobile robots in a self-driving and self-managing scenario, fixed and mobile robots cooperating to accomplish a task, and robots intermingled with humans. Multiple operating modes are illustrated across a wide range of industries and use cases.
Timing is crucial for next-generation networks at 5G and 6G high frequencies. Disclosed are very brief timing signals, and low-complexity procedures for processing them, to obtain a precision time-base lock between a base station and its user devices. In contrast to conventional modulation, the disclosed timing signals feature a change in modulation centrally positioned in a timing resource element. Since the time boundaries of the resource element at the receiver are determined by the receiver's clock, while the actual time of the timing signal is determined by the base station's clock, a displacement of the received timing signal from the midpoint of the resource element indicates a clock offset between the user device and the base station. In addition, by measuring the interval between successive timing signals, the user device can correct its clock rate, and thereby bring the subcarrier frequencies into agreement with the base station.
To assist a user device of a 5G or 6G network in finding its downlink messages, the base station can attach a leading and trailing demarcation to the message. The user device can recognize the demarcations, extract the data between them, and thereby receive the message without computation-intensive searching. Advantageously, the user device can request that the base station not transmit DCI (downlink control information) messages to the user device, since the user device can readily find its messages according to the demarcations. In various embodiments, the demarcations can indicate the address or identity of the intended recipient, the length of the message, the type of the message, and other information to assist the user device. In addition, for even easier detection of the demarcations, the base station can insert a gap of no transmission before and/or after each demarcation. Such demarcations may enable low-cost reduced-capability user devices.
H04W 72/21 - Canaux de commande ou signalisation pour la gestion des ressources dans le sens ascendant de la liaison sans fil, c.-à-d. en direction du réseau
H04L 5/00 - Dispositions destinées à permettre l'usage multiple de la voie de transmission
H04W 72/0446 - Ressources du domaine temporel, p. ex. créneaux ou trames
H04W 72/0453 - Ressources du domaine fréquentiel, p. ex. porteuses dans des AMDF [FDMA]
H04W 72/1273 - Jumelage du trafic à la planification, p. ex. affectation planifiée ou multiplexage de flux de flux de données en liaison descendante
H04W 72/23 - Canaux de commande ou signalisation pour la gestion des ressources dans le sens descendant de la liaison sans fil, c.-à-d. en direction du terminal
H04W 72/231 - Canaux de commande ou signalisation pour la gestion des ressources dans le sens descendant de la liaison sans fil, c.-à-d. en direction du terminal les données de commande provenant des couches au-dessus de la couche physique, p. ex. signalisation RRC ou MAC-CE
69.
Low-complexity beam alignment by directional phase in 5G and 6G
Beamforming is a critical element of 5G and especially 6G, but currently requires a series of time-consuming and resource-consuming messages. Disclosed are procedures by which base stations can transmit a phased beam pulse, having a phase that varies with angle, so that each user device can measure the received phase of the pulse and thereby determine its angle relative to the base station. Each user can then sequentially inform the base station of its orientation relative to the base station, or can append that information to another message such as an initial access message or an acknowledgement, for example. The user device and the base station can then exchange messages in narrow beams aimed at each other according to the alignment angle. Also disclosed are procedures to economically generate the wide-angle phased beam by combining overlapping beams of various phases.
G01S 3/72 - Systèmes à diversité spécialement adaptés à la radiogoniométrie
H04B 17/24 - SurveillanceTests de récepteurs avec rétroaction des mesures vers l’émetteur
G01S 3/04 - Radiogoniomètres pour déterminer la direction d'où proviennent des ondes infrasonores, sonores, ultrasonores ou électromagnétiques ou des émissions de particules sans caractéristiques de direction utilisant des ondes radio Détails
G01S 3/64 - Systèmes à faisceau large produisant au récepteur un signal enveloppe réellement sinusoïdal de l'onde porteuse du faisceau dont l'angle de phase dépend de l'angle entre la direction de l'émetteur par rapport au récepteur et une direction de référence issue du récepteur, p. ex. système cardioïde où l'angle de phase du signal est déterminé par la comparaison de phase avec un signal de référence alternatif synchronisé avec la variation de directivité
H04B 17/27 - SurveillanceTests de récepteurs pour localiser ou positionner l’émetteur
70.
Resource-efficient low-complexity beamforming feedback in 5G/6G
Feedback messages are essential for controlling transmission beams between network devices in 5G and 6G. Disclosed are brief signals and procedures for a user device to provide feedback to a base station on beam direction, transmission power, beam width, and other transmission parameters. The resource cost is so low, the base station can provide alignment test signals with each downlink message, and the user device can provide feedback selecting a best-received test signal as part of each uplink message, such as an acknowledgement. With such near-real-time beam fine-tuning, base stations and user devices can maintain the tight directional communications required for next-generation communications, without burdening the network with cumbersome feedback messages of prior art. Numerous other aspects are disclosed.
H04B 7/06 - Systèmes de diversitéSystèmes à plusieurs antennes, c.-à-d. émission ou réception utilisant plusieurs antennes utilisant plusieurs antennes indépendantes espacées à la station d'émission
H04B 17/373 - Prédiction des paramètres de qualité d’un canal
H04B 17/382 - SurveillanceTests de canaux de propagation pour l’attribution de ressources, le contrôle d’accès ou le transfert
H04W 24/10 - Planification des comptes-rendus de mesures
H04W 52/24 - Commande de puissance d'émission [TPC Transmission power control] le TPC étant effectué selon des paramètres spécifiques utilisant le rapport signal sur parasite [SIR Signal to Interference Ratio] ou d'autres paramètres de trajet sans fil
H04W 72/044 - Affectation de ressources sans fil sur la base du type de ressources affectées
71.
Resource-efficient polling method for delivering messages to 5G/6G users
Many wireless receivers in 5G and 6G are expected to use DRX (discontinuous reception) to save power. What is lacking is an efficient procedure to inform the DRX users that they have an incoming message on hold at the base station. Therefore, a procedure is disclosed for the base station to assign each user device to a section and a position within that section. Then the base station can periodically broadcast a polling message including only those sections that have at least one waiting with a message on hold. In addition, each user device is assigned a single bit at a calculated position in the polling message, so that each DRX user can determine when it has a message on hold. In addition, the base station can assign an equally compact and efficient reply region for each ready user to request its message, thereby saving time and resources.
Message faults are expected to be an increasing problem in 5G and 6G, due to signal fading at high frequencies, heavy background interference, and high user densities. Retransmissions are expensive in time, power, and the additional background they generate. Prior art includes “soft-combining” among multiple copies, an especially ineffective fault mitigation procedure when SNR is low. Nevertheless, the waveform signals of even badly faulted message elements are rich with information about the correct value. Therefore, procedures are disclosed herein for determining which message elements of a corrupted message, or its associated error-detection code, are faulted, by measuring characteristic parameters of the signal waveform of each message element, and correlating those parameters with the associated error-detection code. In many cases, the corrupted message may be corrected without a retransmission, according to some embodiments.
AI-based fault detection, localization, and correction can improve message reliability in 5G and 6G communications by enabling the rapid recovery of faulted messages without wasting precious time and power on an unnecessary retransmission. The waveform of a received message is rich with information implicating the faulted message elements and, in many cases, suggesting the corrected value. In examples, message recovery can be based on the amplitude of the received waveform, its phase, any pathological variations in noise or in frequency or in polarization, and on inter-symbol transition regions, to list just a few waveform fault indicators revealing the fault locations. In addition, the AI model, or an algorithm derived from it, can discern the intent or meaning of a message, as well as its form and format, the bitwise content, the sequence of characters, and other error flags indicating which parts of the message are faulted.
As transmitters proliferate, and the transmission frequency steadily increases in 5G and especially 6G, the rate of message faults will likely increase unacceptably. Disclosed are methods for wireless receivers to detect, localize, and correct message faults using a combination of signal quality, modulation quality, and an embedded error-detection code. The error-detection code can indicate when the message is corrupted, while the signal quality and modulation quality can indicate which message elements are faulted, or can provide a likelihood that each message element is faulted. The message can then be corrected, using a combination of the error-correction code, the signal quality, and the modulation quality. In embodiments, the correction can be calculated directly from the error-detection code, or determined by altering each likely faulted message element to each of the other modulation states and testing with the error-detection code. By either method, network resources are saved and reliability is increased.
Reliability, in 5G and emerging 6G, is a continuing challenge due to signal fading, heavy interference, and phase noise, among others. The disclosed procedures show how to locate the most likely faulted message elements according to a deviant modulation, excessive amplitude or phase instability, and inconsistency between successive transmissions of the message. In addition, the receiver can rectify the message either by altering the faulted message elements to other modulation states, or by selectively merging two versions of the message according to signal quality. In either case, reliability is improved, range is extended, and time is saved.
Network throughput can be increased and the message failure rate can be reduced in 5G and 6G communications by use of AI-based fault mitigation: that ism detection, localization, and correction of faulted message elements in real-time. A receiver provides the demodulated message, along with amplitude and phase measurements of each message element, directly to a properly trained artificial intelligence model. The model determines the most-likely faulted message elements, and in some cases can indicate the most probable correct value of the faulted message elements. The AI model can also determine the fault probability of each message element. The expected message content (such as value ranges and predetermined format) can also be provided to the AI model, for further corruption sensitivity. By correcting faulted messages in less time than required for a retransmission, the system can save time, reduce backgrounds, and greatly reduce dropped messages.
Reliable communications is a central goal of 5G and 6G. However, due to signal fading at high frequencies and interference due to crowding, message faults continue to be a problem. Disclosed are methods for base station and user devices to adjust the modulation scheme according to the types of faults received, including amplitude faults (incorrectly demodulated amplitude levels) and phase faults (incorrectly demodulated phase levels), among others. The base station can select a more suitable modulation scheme based on the types of faults observed by user devices, such as modulation schemes with more or fewer amplitude levels and phase levels. In some versions, the number of amplitude levels is different from the number of phase levels, to combat specific fault problems.
A major goal of 5G and especially 6G is reliable, low-latency communication. Unfortunately, higher density networks result in increasing interference, and higher frequency bands inevitably have signal fading problems, leading to frequency message faults. To restore high-speed, high-reliability messaging, methods are disclosed for evaluating the signal quality of each message element of a received message so that any faulting can be localized to the message elements with the lowest signal quality. Numerous contributions to signal quality are disclosed, including modulation, amplitude and phase stability, polarization and inter-symbol irregularities, expected message format and meaning, and common or unexpected bit sequences. Many further aspects are included.
5G and 6G wireless networks can use artificial intelligence models to optimize performance by measuring the rate of message faults, and in particular the rate of various types of faults. For example, the amplitude faults include a modulation amplitude distorted by a small or large amplitude change, and whether the faults cluster in the high or low amplitude modulation portions of a constellation chart, among many other inputs related to network operations. The artificial intelligence model can be configured to predict the subsequent network performance according to each modulation scheme available to the network, thereby enabling the network to select a more effective modulation scheme. Alternatively, the artificial intelligence model can select the preferred modulation scheme and recommend the change to the network operators, or it can implement the change automatically if enabled to do so.
Inter-vehicle signaling is essential for cooperative collision mitigation. Disclosed are systems and methods for autonomous or semi-autonomous vehicles to identify each other, localize each other, and then cooperate in avoiding a collision if avoidable, and minimizing the harm of the collision if not avoidable. Examples include simultaneous wireless and infrared signals that enable other vehicles to specifically identify each cooperating vehicle, so that an evasion strategy can be developed. Additionally, the signaling can include, in the wireless messages or the infrared signals, or both, the wireless address of the transmitting vehicle, thereby enabling unicast communication and greatly improved coordination thereafter. This system will save lives.
G01S 5/00 - Localisation par coordination de plusieurs déterminations de direction ou de ligne de positionLocalisation par coordination de plusieurs déterminations de distance
G07C 5/00 - Enregistrement ou indication du fonctionnement de véhicules
H04W 4/46 - Services spécialement adaptés à des environnements, à des situations ou à des fins spécifiques pour les véhicules, p. ex. communication véhicule-piétons pour la communication de véhicule à véhicule
81.
Demodulation using two modulation schemes in 5G and 6G
Amplitude noise, phase noise, and interference can be mitigated in 5G and 6G by exploiting advantages of two different modulation schemes. A message may be modulated according to a first modulation scheme, such as multiplexed amplitude and phase modulation, and then received (including noise and interference) according to a second modulation scheme, such as QAM (quadrature amplitude modulation). In addition, a compact demodulation reference can be transmitted wherein a first resource element exhibits a particular phase along with a maximum and a minimum branch amplitude, and a second resource element is blank. The receiver calibrates the amplitude levels according to the demodulation reference, calculates the phase noise according to a ratio of the two branch amplitudes, and measures the interference according to the unpowered (blank) second resource element. The receiver can then demodulate the message according to the second modulation scheme, while correcting for phase noise, fading, and interference.
An ultra-lean, low-complexity 5G/6G procedure for adjusting transmission beam parameters for optimal reception by a particular user device. The transmitter can append multiple brief test signals to each message, using a different transmission parameter for each test signal. The receiver can reply (optionally in an acknowledgement) indicating which test signal was best received. The transmitter can then use the selected value of the transmission parameter for the next message, thereby successively approaching the optimal value. Each adjustment step can be a predetermined increment value, which is added or subtracted from the previous value depending on which test signal was selected by the receiver. As conditions change (or as the user device moves), the beam parameter can be updated again upon each downlink transmission, thereby tracking the user device's preferred transmission value in realtime.
A 5G/6G network can include a modulation scheme for uplink and downlink messaging using a special zero-power modulation level, in addition to the regular amplitude modulation levels of, for example, QAM. The receiver can demodulate each message element by comparing the amplitude to the various amplitude levels, including the zero-power level, and thereby increase the bits per message element, and hence the communication throughput, at no increase in transmitted power. In addition, the zero-power states can reveal intrusive noise and interference in the proximate message, enabling correction before the demodulation. The zero-power amplitude may be added to conventional modulation schemes, such as an additional zero-power amplitude level in QAM, PSK, and amplitude-phase modulation schemes, thereby providing greater versatility at little or no cost and no additional transmission power.
Synchronization between a base station and user devices is crucial for high-frequency 5G and especially 6G communications. Disclosed is a fast, compact timing signal comprising an abrupt change in a downlink signal modulation, centrally positioned in a predetermined symbol-time. Each user device can receive the downlink timing signal, digitize the received signal, and determine a specific time at which the modulation switches. The user device can then determine whether the specific time is at a midpoint of the predetermined symbol-time, and if not, can determine a timing offset according to the difference. Since the user device's symbol-time boundaries are determined by the user device's clock, whereas the timing signal is determined by the base station, the timing offset generally indicates a setting error of the user device's clock, in which case the user device can reset its clock to agree with the base station clock.
Message reliability is a key requirement of 5G/6G communications. In many challenging network environments, two successive retransmissions of a message can both be corrupted, greatly reducing reliability. Therefore, methods are disclosed for identifying faulted message elements according to a metric that includes the waveform or SNR of the message element, its modulation quality, and a consistency check between the received versions. The receiver can then assemble a merged message version by selecting the higher quality version of each message element from the two (or more) corrupted versions, and thereby avoid requesting yet another retransmission. In addition, the receiver can monitor the background level and, if it is above a predetermined limit, can request that the receiver store the message for a predetermined time, or until the background level subsides below the limit.
H04L 1/1809 - Protocoles de retransmission sélective
H04L 1/20 - Dispositions pour détecter ou empêcher les erreurs dans l'information reçue en utilisant un détecteur de la qualité du signal
H04L 27/02 - Systèmes à courant porteur à modulation d'amplitude, p. ex. utilisant la manipulation par tout ou rienModulation à bande latérale unique ou à bande résiduelle
H04L 27/34 - Systèmes à courant porteur à modulation de phase et d'amplitude, p. ex. en quadrature d'amplitude
H04L 27/36 - Circuits de modulationCircuits émetteurs
Artificial Intelligence (AI) is well-suited to mitigate message faults by combining analog and digital information in 5G and 6G communications. The analog information includes everything measureable about the waveform signal as-received, and the digital information includes the error-detection code accompanying the message. For example, the AI model can localize the most likely faulted message elements according to amplitude fluctuations or phase deviations or other signaling irregularity, and can then use the error-detection code to calculate the corrected values of the faulted message elements. The AI model can also check the error-detection code itself for faults and consistency, as well as a demodulation reference that was used to demodulate the message, thereby avoiding a defective mitigation if either of those is faulted. The AI model can provide output including the most likely corrected version of the message, as well as a comparison with other possible versions, if any.
In a traffic emergency, there is no time for a human to integrate multiple sensor data streams and devise a plan for avoiding a collision. Only the electronic reflexes of a trained automatic system can provide evasive action in time. Disclosed is an artificial intelligence (AI) model trained to recognize an imminent collision based on sensor data, rapidly devise and test a large number of possible sequences of actions, some drawn from a library of previously-successful strategies and others invented by the AI model. If any sequence can avoid the collision, the AI model implements that sequence immediately. If none of the sequences can avoid the collision, the AI model calculates the harm caused by each sequence and picks the one that causes the least harm (fatalities, injuries, etc.) for implementation. AI is needed to find a possible solution in time to implement it and thereby mitigate the imminent collision.
B60W 10/184 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de freinage avec des freins de roues
B60W 30/085 - Ajustant automatiquement la position du véhicule en préparation de la collision, p. ex. en freinant pour piquer du nez
B60W 50/12 - Limitation de la possibilité de commande du conducteur en fonction de l'état du véhicule, p. ex. moyens de verrouillage des grandeurs d'entrées pour éviter un fonctionnement dangereux
B60W 50/14 - Moyens d'information du conducteur, pour l'avertir ou provoquer son intervention
G05D 1/02 - Commande de la position ou du cap par référence à un système à deux dimensions
B60W 10/18 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de freinage
B60W 50/16 - Signalisation tactile au conducteur, p. ex. vibration ou augmentation de la résistance sur le volant ou sur la pédale d'accélérateur
A central challenge in next-generation 5G/6G networks is achieving high message reliability despite very dense usage and unavoidable signal fading at high frequencies. To provide enhanced fault detection, localization, and mitigation, the disclosed procedures can enable an AI model (or an algorithm derived from it) to discriminate between faulted and unfaulted message elements according to signal quality, modulation parameters, and other inputs. The AI model can estimate the likelihood that each message element is faulted, and predict the most probable corrected value, among other outputs. The AI model can also consider the quality of a demodulation reference used to demodulate the message, and the quality of the associated error-detection code. The AI model can also consider previously received messages to the same receiver, or messages of a similar type. Fault mitigation by the receiver can save substantial time and resources by avoiding a retransmission. Many other aspects are disclosed.
H04L 1/1809 - Protocoles de retransmission sélective
H04L 1/20 - Dispositions pour détecter ou empêcher les erreurs dans l'information reçue en utilisant un détecteur de la qualité du signal
H04L 27/02 - Systèmes à courant porteur à modulation d'amplitude, p. ex. utilisant la manipulation par tout ou rienModulation à bande latérale unique ou à bande résiduelle
H04L 27/26 - Systèmes utilisant des codes à fréquences multiples
H04L 27/34 - Systèmes à courant porteur à modulation de phase et d'amplitude, p. ex. en quadrature d'amplitude
H04L 27/36 - Circuits de modulationCircuits émetteurs
In 5G and 6G, efficient communication relies on narrow communication beams directed between the transmitter and the intended recipient. However, the optimal beam direction changes whenever the user moves, as in traffic. The user device can inform the base station of the user's initial location, speed, and direction of travel, so the base station can calculate the appropriate beam direction versus time. However, if the mobile user device changes in speed or direction, this may result in an erroneous calculation by the base station. The directional error may be insignificant if the directional error is much less than the beam width. The mobile user device can calculate the directional error based on the change in speed or direction, and when the directional error becomes comparable to the beam width of the base station, the user can transmit a message to the base station indicating the new location, speed, and direction.
H04L 1/00 - Dispositions pour détecter ou empêcher les erreurs dans l'information reçue
H04W 72/02 - Sélection de ressources sans fil par un utilisateur ou un terminal
H04W 72/0453 - Ressources du domaine fréquentiel, p. ex. porteuses dans des AMDF [FDMA]
H04W 52/28 - Commande de puissance d'émission [TPC Transmission power control] le TPC étant effectué selon des paramètres spécifiques utilisant le profil utilisateur, p. ex. la vitesse, la priorité ou l'état du réseau, p. ex. en attente, libre ou absence de transmission
H04W 64/00 - Localisation d'utilisateurs ou de terminaux pour la gestion du réseau, p. ex. gestion de la mobilité
G01S 5/00 - Localisation par coordination de plusieurs déterminations de direction ou de ligne de positionLocalisation par coordination de plusieurs déterminations de distance
H04W 16/28 - Structures des cellules utilisant l'orientation du faisceau
H04W 52/08 - Commande de puissance en boucle fermée
H04W 52/22 - Commande de puissance d'émission [TPC Transmission power control] le TPC étant effectué selon des paramètres spécifiques tenant compte des informations ou des instructions antérieures
H04W 72/044 - Affectation de ressources sans fil sur la base du type de ressources affectées
H04W 72/51 - Critères d’affectation ou de planification des ressources sans fil sur la base des propriétés du terminal ou du dispositif
90.
Artificial intelligence for fault localization and mitigation in 5G/6G
A key requirement for 5G and 6G networking is reliability. Message faults are inevitable, and therefore procedures are needed to identify each fault location in a message and, if possible, to rectify it. Disclosed herein are artificial intelligence AI models and procedures for mitigating faults in wireless messages by (a) evaluating the signal quality of each message element according to waveform features and modulation deviations, (b) evaluating the fault probability of each message element by seeking correlations, which may be subtle, among the various waveform measurements including polarization and frequency offset, and (c) correcting the faults according to the message type, apparent format, intent or meaning, typical previous messages of a similar type, correlations of bit patterns and symbol sequences, error-detection codes if present, and other content-based indicators uncovered during model development. Automatic, real-time fault localization and correction may save substantial time and resources while substantially enhancing messaging reliability.
H02J 3/14 - Circuits pour réseaux principaux ou de distribution, à courant alternatif pour règler la tension dans des réseaux à courant alternatif par changement d'une caractéristique de la charge du réseau par interruption, ou mise en circuit, des charges du réseau, p. ex. charge équilibrée progressivement
H04L 1/20 - Dispositions pour détecter ou empêcher les erreurs dans l'information reçue en utilisant un détecteur de la qualité du signal
91.
Signal quality input for error-detection codes in 5G and 6G
Wireless messages in 5G and 6G include error-detection codes appended or embedded in the message, such as Polar, LDPC, Turbo, and CRC codes. Analog fault tests based on the waveform signal of each message element can enhance the fault localization and mitigation, in many cases. Unexpected amplitude or phase variations, ambiguous modulation values, and polarization irregularities in or between message elements can localize the likely faulted message element(s). Turbo, Polar, and certain LDPC versions employ soft-decision decoding natively, and therefore can include the waveform results as extrinsic information. Other codes, such as basic parity, CRC, and basic LDPC, use hard-decision processes, but when combined with waveform diagnostics, can localize and mitigate faults. In life-threatening situations, rapid mitigation of a faulted message may save lives. The error-detection code, combined with waveform data, can rescue faulted messages in real-time, thereby improving latency, efficiency, and reliability of wireless communications.
High-frequency communications in 5G and especially 6G will require precise synchronization of user devices with the base station, including periodically setting the user device clock time and clock rate to mitigate oscillator drift. The base station can assist user devices by periodically providing a timing signal containing a mid-symbol timestamp point, which is a signal that includes an abrupt change in phase or amplitude centered in the symbol-time. A receiver can analyze the timing signal and determine precisely the time of arrival of the timestamp point, and correct the receiver's clock to ensure that uplink messages will then arrive at the base station synchronized with the base station's resource grid. In addition, the base station can provide two timing signals in which the mid-symbol timestamp points are separated by a predetermined separation, thereby assisting the user devices in adjusting their clock rates.
A searchable, portable network database of base station information can greatly simplify discovery, selection, and registration of user devices on a preferred cell in 5G or 6G. In addition, based on location, the user device can select the base station that is likely to provide the best signal. The network database can provide all of the static system information of the SSB message, which enables prospective user devices to receive downlink messages without searching for the SSB. In addition, the network database can provide all of the static system information contained in the SIB1 message, which enables prospective user devices to transmit uplink messages without searching for the SIB1. Initial synchronization can be obtained by receiving any broadcast from the base station, or by receiving timing signals from a navigation satellite, among other ways. The user device can thereby avoid most or all of the arduous prior-art cell discovery steps.
H04W 60/04 - Rattachement à un réseau, p. ex. enregistrementSuppression du rattachement à un réseau, p. ex. annulation de l'enregistrement utilisant des événements déclenchés
H04W 74/0833 - Procédures d’accès aléatoire, p. ex. avec accès en 4 étapes
94.
Waveform indicators for fault localization in 5G and 6G messages
Message faults are an increasing problem for 5G and expected 6G networks, due to growth, crowding, and signal fading problems. Disclosed are procedures for determining which particular message element of a corrupted message is faulted, and optionally the most likely correction. A receiver can identify the faulted message element by measuring the fluctuations, in phase and amplitude, of the waveform of each message element, as well as the modulation quality, frequency offset, and other signal measurements. Faulted message elements are likely to have higher fluctuations, higher modulation deviations, and higher signal irregularities, than the unfaulted ones. Mitigation can then be applied to the faulted message elements, thereby recovering the correct message and avoiding a costly retransmission delay. AI models may enhance the fault detection sensitivity by exploiting correlations between the various waveform measurement parameters, and then may predict the corrected value of the faulted message elements.
A compact demodulation reference is disclosed for compatibility with reduced-capability user devices, and for enhanced throughput for high-performance user devices of 5G and 6G in high-density environments. The demodulation reference, in some embodiments, occupies only one resource element, yet provides sufficient information to enable a receiver to calculate all of the amplitude or phase modulation levels of the modulation scheme. For example, if the modulation scheme is 16QAM, the demodulation reference can include an I branch with the highest amplitude level of the modulation scheme and an orthogonal Q branch with the lowest amplitude level. Further examples apply to a multiplexed amplitude-phase modulation scheme. In each case, the receiver can calculate the remaining amplitude (or phase) modulation levels, and thereby demodulate a proximate message. Further examples show how to reveal faulted message elements by comparing demodulation with QAM and amplitude-phase demodulation, and how to optimize noise margins.
High-frequency communications in 5G and especially 6G will require precise synchronization of user devices with the base station, including setting the user device clock time and clock rate. The base station can assist user devices by periodically providing a guard-space timestamp point, at which a phase or amplitude of the timing signal abruptly changes in the middle of the guard-space of a particular resource element or a particular OFDM symbol. A receiver can determine precisely the time of arrival of the timestamp point, and correct its clock setting to agree with the time of the timestamp point. The receiver can then provide uplink messages aligned with the base station's clock, by adding a previously determined timing advance to each uplink transmission. In addition, the user device can measure two guard-space timing signals with a predetermined separation, thereby adjusting the clock rate.
A base station can maintain a transmission beam toward a user device, even in changing conditions, by realtime incremental feedback in 5G and 6G. The incremental feedback is a compact one-of-three request, from the user device, indicating a higher, keep-same, or lower adjustment of a transmission parameter such as the power or beam angle. The base station then adds or subtracts a predetermined increment to that transmission parameter, thereby improving reception with each downlink message. Such incremental adjustment continues with each message to the user device, until the optimum value is reached, at which time the user device selects the keep-same choice. For efficient optimization, the base station can vary the increment size, for example escalating to larger sizes upon repeated same-sign requests, and then de-escalating to smaller increments for fine-tuning and beam optimization. Many other aspects are disclosed.
A base station and a user device can cooperate to align their transmission and reception beams for optimal communication in 5G and 6G. At a pre-arranged time (or upon a special “start” signal), the base station can transmit a series of beam scan signals in various directions, each beam scan signal occupying a single resource element. The beam scan signals can be transmitted time-spanning or frequency-spanning. A user device can determine which of the beam scan signals provided the best received signal quality or amplitude or power. The user device can then indicate the favored beam direction by transmitting a reply signal in a single resource element having the same frequency and a predetermined time delay after that beam scan signal. The base station can determine the optimal beam direction toward the user device according to the time and frequency of the reply signal. Many other aspects are disclosed.
H04B 7/06 - Systèmes de diversitéSystèmes à plusieurs antennes, c.-à-d. émission ou réception utilisant plusieurs antennes utilisant plusieurs antennes indépendantes espacées à la station d'émission
H04W 24/10 - Planification des comptes-rendus de mesures
H04W 72/044 - Affectation de ressources sans fil sur la base du type de ressources affectées
99.
Multiplexed code for ACK/SR/power/beam feedback in 5G and 6G
Disclosed are procedures and examples of feedback messages that enable a user device to request transmission adjustments in 5G and 6G. The feedback message may indicate a selected beam direction, a power adjustment request, a grant request, and an acknowledgement, among other things. For example, a downlink message may include several beam test signals, each transmitted in a different direction, and the user device can indicate, in the feedback message, which test signal was best received. Thus the feedback enables the base station to adjust its beam toward the user device upon each message. In addition, the user device can determine the amplitude or signal quality received in the favored test signal, and can then include an incremental power adjustment request in the feedback message. In addition, the user device can request a retransmission and/or an uplink grant, and can optionally provide a BSR as well, in some embodiments.
H04W 24/06 - Réalisation de tests en trafic simulé
H04W 52/24 - Commande de puissance d'émission [TPC Transmission power control] le TPC étant effectué selon des paramètres spécifiques utilisant le rapport signal sur parasite [SIR Signal to Interference Ratio] ou d'autres paramètres de trajet sans fil
100.
Lean deterministic beam/power feedback during 5G/6G initial access
For efficient communication in 5G and 6G, transmission beams are to be aligned with each user device as soon as possible during the initial access procedure. Prior-art procedures for downlink beam alignment consume large amounts of power and resources. Therefore, low-complexity formats and procedures are disclosed for a new user device to indicate its angular position relative to the base station upon entering the network. In one embodiment, the SSB message is broadcast isotropically, along with test signals which are transmitted in different directions. The user device indicates which test signal is best received, thereby indicating its angular direction. In a second embodiment, the test signals and feedback messages are appended to various entry messages after initial contact. Using either method, the base station and user device can then aim their beams toward the other, for enhanced signal quality thereafter.
brevets