254 results about "Link adaptation" patented technology

A wireless communication method and system enabling dynamic multi-path data transmission and reception across heterogeneous radio access networks. The method includes selecting between sequential, concurrent, or redundant multipath transmission strategies based on real-time measurements of link quality parameters, including signal-to-interference-plus-noise ratio (SINR), reference signal received power (RSRP), delay, and spectrum availability. The system further enables adaptive transmission power control, modulation scheme selection, and carrier configuration based on physical layer feedback, minimizing interference and optimizing spectral efficiency. Peer-to-peer communication between terminals is supported without base station mediation, reducing RAN load. Multi-base station connectivity is enabled, allowing terminals to simultaneously transmit through multiple nodes and aggregate at the core network. The architecture supports real-time topology control, dynamic link adaptation, and transmission parameter adjustment based on physical-layer constraints.

The invention discloses an AI model training parameter dynamic optimization system, and relates to the technical field of artificial intelligence model training optimization. According to the scheme, by monitoring gradient norms in real time and fusing a frequency weighting mechanism, dynamic gradient self-adaptive cutting is achieved, the limitation of a fixed threshold value is broken through, and the model precision is guaranteed while the batch scale is expanded by 30%; a weight matrix is innovatively decomposed into a low-rank factor matrix, the internal storage is compressed to O (n + m), a strategy perception distillation technology is synchronously combined, a reward signal is dynamically generated by utilizing comparative learning to replace manual preference labeling, and collaborative optimization of parameter lightweight and knowledge migration is realized; aiming at a heterogeneous equipment environment, designing a computing power perception parameter group automatic division mechanism, and reducing communication redundancy by 40% by adopting asynchronous weighted aggregation; and constructing a data-parameter joint adjustment and optimization closed loop, and integrating a real-time data cleaning framework and a parameter normalization module to dynamically adjust the hyperparameters of the optimizer. According to the system, an efficient solution is provided for edge calculation and large model training by using a full-link adaptive architecture.

Systems, methods, and instrumentalities are described herein regarding power control and link adaptation for cross-division duplex (XDD). A wireless transmit / receive unit (WTRU) may receive a grant associated with transmission of an uplink (UL) signal. The grant may indicate a first set of resource blocks (RBs). The WTRU may determine a frequency gap (FG) between the first set of RBs and a reference RB. The WTRU may adjust one or more transmit (Tx) parameters based on the determined FG. When the determined FG is less than a pre-defined threshold, the WTRU may reduce one or more of a transmit power or a modulation coding scheme (MCS) level associated with transmission of the UL signal scheduled by the grant. The WTRU may transmit the UL signal using the adjusted one or more Tx parameters.

The invention provides a wireless resource scheduling method and device used in a scene in which a mobile phone is directly connected with a satellite, and relates to the technical field of satellite communication, and the method comprises the steps: constructing an electromagnetic map which represents the corresponding relation of a geographic position, a physical resource block and ground interference power in a satellite beam coverage area; link budgeting is carried out on the multiple user terminals in combination with the real-time orbit geometric parameters of the satellite and the electromagnetic map, and the signal to interference plus noise ratio of each user terminal on each physical resource block is predicted; based on the predicted signal to interference plus noise ratio, adopting a proportional fair marginal gain greedy algorithm to allocate an optimal continuous spectrum resource block for each user terminal; on the allocated spectrum resources, optimizing and reallocating the total transmitting power of the satellites by adopting a water injection algorithm; and a final spectrum-power joint scheduling scheme is generated, and subsequent link self-adaption and data transmission are guided. According to the invention, the spectrum efficiency, throughput and connection stability of the system are obviously improved.

The invention discloses an area terminal adaptive communication method and system based on link quality perception, and relates to the technical field of power area terminal communication by predicting link quality, comprising the following steps: predicting link quality according to multi-dimensional perception data to obtain link quality prediction data; determining a candidate link based on the service-link adaptation rule base, determining a target link according to the link quality prediction data of the candidate link, and performing data transmission through the target link; according to the real-time link quality data of the target link, whether switching is needed or not is judged in combination with the power grid operation state, and if switching is needed, the link priority is calculated to obtain an optimal link, and link switching is carried out; the method can adapt to a complex operation scene of a power grid, improves the link switching efficiency, improves the communication efficiency and communication reliability between the station area terminals, and solves the problem of low communication efficiency caused by poor environmental adaptability and relatively high switching time delay between a communication protocol and a module in an existing station area terminal communication technology.

Methods and systems are disclosed for enhancements to multicast beamforming to support PTM multicast service, concurrent multicast and unicast service, MBS, or group side-link service at the physical layer. A base station or multicast UEs of a wireless communication network may enhance reporting of the channel state information of a link between the base station and the UE and adaptation of the link for multicast beamforming. Enhancements to multicast beamforming may include techniques such as CQI table optimization and SSB-based early CQI reporting, consideration of UE preferences such as the preferred number of retransmissions and frequency-hopping preference for retransmission when designing a time-domain or frequency-domain retransmission scheme common to the multicast UEs, and multi-layer MIMO beamforming for 2-layer multicast transmissions over the horizontal and vertical polarizations and for concurrent multicast and unicast transmissions. The enhancements improve multicast service performance and efficiently allow a UE to gain access to multicast service.

The invention provides a giant constellation network laser communication link adaptive reconstruction method and system, and relates to the technical field of satellite communication, and the method comprises the steps: calculating link parameters through collecting satellite node positions and track information, generating a resource state matrix, executing interference analysis to determine an interference level, and generating a reconstruction priority list; and performing adaptive reconstruction on the target link by using deep reinforcement learning. Interference between satellites can be reduced, the network communication quality is improved, the energy utilization efficiency is optimized, and the communication reliability and stability of the constellation network are enhanced.

The invention relates to a method for performing a link adaptation in an uplink transmission between a user equipment, UE, and a network node in a telecommunication network, the method comprising:obtaining a first value of a Modulation and Coding Scheme, MCS, for a future transmission at transmission time interval k in the uplink transmission, the first value of MCS being determined on the basis of a Signal to Interference and Noise Ratio, SINR, estimated by the network node for the future transmission at transmission time interval k; andpredicting a second value of the MCS for the future transmission at transmission time k by using a Q-learning process having as input the first value of MCS, first data indicating whether the future transmission at transmission time k is a first transmission or a retransmission, and second data indicating whether a feedback acknowledgement, ACK / NACK, of a transmission that took place at transmission time interval k−1 is equal to ACK or NACK.

Disclosed are devices, methods, apparatuses, and computer readable media for fronthaul. An example apparatus for a scheduler may include at least one processor and at least one memory. The at least one memory may store instructions that, when executed by the at least one processor, may cause the apparatus at least to: monitor a feedback notifying a status of congestion in fronthaul; and perform at least one of the following: adjusting link adaptation, or adjusting radio resource allocations with a radio resource limit which restricts an amount of radio resources available per a time interval for a given cell or a group of cells.

The invention relates to the technical field of server hardware fault diagnosis, in particular to an intelligent fault diagnosis method and system for a server mainboard and a storage medium. The method comprises the following steps: configuring monitoring parameters in a bus link controller of a server mainboard, and setting an undisturbed sampling window as a training sequence time period and an idle symbol time period in a bus physical layer data transmission process; periodically reading a link adaptive equalization parameter, an error count value and symbol arrival time through a bus link controller register, and simultaneously collecting a temperature parameter and a voltage parameter at the current moment; and combining the link adaptive equalization parameter, the error count value, the symbol arrival time, the temperature parameter and the voltage parameter at the same sampling moment as a signal quality vector at the moment. According to the method, two data transmission-free windows of the training sequence time period and the idle symbol time period are identified and utilized, so that the monitoring operation and the service data are staggered, and the sampling operation is ensured not to interfere with normal data transmission.

The invention discloses an eddy current data compression transmission optimization method, relates to the technical field of data compression transmission, and solves the technical problems that a compression algorithm lacks scenario adaptation and data transmission lacks priority and link adaptation. Scene demand-algorithm characteristic accurate matching is achieved, compressed data overall reconstruction errors and defect area reconstruction errors are reduced, delay and compression ratio requirements of different scenes are met, data priorities are judged in a multi-dimensional mode, it is ensured that defect data acquisition resources are inclined, key information is prevented from being lost, and the method is suitable for large-scale popularization and application. A transmission protocol is optimized for a short / medium / long distance scene, the protocol adaptability and the transmission efficiency are improved, a transmission scene-link state-data priority three-dimensional linkage transmission strategy is constructed, the bandwidth occupation proportion is dynamically adjusted, core data are preferentially transmitted when links are congested, and resources are fully utilized when the links are idle.

The invention discloses an event flow assisted link self-adaption method and system oriented to the Internet of Vehicles, and belongs to the field of link self-adaption of the Internet of Vehicles, and the method comprises the steps: obtaining event flow data; inputting the event stream data into the trained depth estimation model to obtain the environment depth under the current time step; calculating the distance between the base station and the user equipment based on the event stream data and the environment depth under the current time step; and based on the distance between the base station and the user equipment, estimating a channel state and calculating a coding rate under the current time step so as to complete link self-adaption. According to the invention, dynamic sensing of the distance between the BS and the UE is realized by using the space-time correlation of the event stream, the time delay defect of a traditional feedback mechanism is overcome, the problem of inaccurate channel acquisition caused by traditional outdated feedback information is solved through visual information, the model calculation complexity is reduced, the coding rate performance is improved, and the spectrum efficiency is further improved.

The invention discloses a multi-node sensor communication link cooperative scheduling method and system based on star flash, and relates to the technical field of new-generation wireless communication and sensors. The method comprises the following steps: constructing a star flash sensor data reporting system; calculating a node valid data volume based on parameters such as sensor types and channel numbers; estimating transmission time and distributing time slots in combination with a star flash frame structure; transmission parameters are dynamically adjusted through a real-time link quality perception and prediction model, and a data priority and preemption mechanism is supported; issuing a scheduling strategy by using the JSON configuration file; and the nodes communicate according to configuration and realize fault self-diagnosis and self-healing. The system comprises a star flash management node, a sensor node and an embedded cooperative scheduling engine. According to the method, multi-node cooperative scheduling, link adaptive optimization and system autonomous recovery are realized, and the communication reliability, the channel utilization rate and the system robustness are remarkably improved.

The disclosure relates to a 5G or 6G communication system for supporting higher data rates. The disclosure provides a method performed by a base station of an NTN. The method includes: transmitting, to a terminal, a first PDSCH in first slots, wherein the first slots include at least one slot where the first PDSCH is scheduled without HARQ feedback; receiving, from the terminal, channel quality information and feedback information, wherein the feedback information includes HARQ feedback information and RLC status information associated with a transmission of the first PDSCH in the at least one slot; predicting a MCS and a repetition number for a second PDSCH, based on the information associated with the channel quality information and the feedback information; transmitting, to the terminal, information on the MCS and information on the repetition number; and transmitting, to the terminal, the second PDSCH in second slots.

The invention discloses an eVTOL aircraft ground control device based on a multi-link adaptation and response mechanism, and belongs to the technical field of eVTOL aircraft communication and control. The device comprises an instruction distribution module, a multi-link management module, a frame construction module and an error control module. The instruction distribution module is responsible for cooperating with eVTOL aircraft information to send a corresponding flight control instruction according to an actual condition; the multi-link management module evaluates a plurality of communication links (including a main link, a standby link and an emergency link) in real time and is used for sending different instructions; the frame construction module constructs an extended interactive data frame based on the MAVLink protocol, and the data frame comprises a plurality of control fields for control; the device also has an error control mechanism, and a closed-loop control system is completed through the mechanism. Through the method, the instruction reliability of the ground control station in a complex communication environment and the stability of an eVTOL aircraft system can be effectively improved.

The invention provides a zero-trust-based dynamic data secure transmission and processing channel construction device and method, and the method comprises the steps: S1, collecting to-be-transmitted data, and classifying the data to obtain a data classification result; s2, based on the data classification result, the user identity information and the environmental risk information, a dynamic security policy is generated, and the dynamic security policy comprises an encryption algorithm selection rule, a trust evaluation threshold and a data operation authority policy; according to the invention, the fine-grained security policy is generated and continuously adjusted by dynamically sensing the data sensitivity and the real-time trust state, so that the full-link self-adaptive security protection from transmission to processing is realized; according to the method, the security multi-party calculation is seamlessly integrated in a high-sensitivity scene, so that the end-to-end security and privacy protection level of data in a cross-domain and multi-participant environment are remarkably improved while the data mobility is guaranteed, and the problem that a traditional static security mechanism is difficult to adapt to dynamic risks is effectively solved.

An enhanced link adaptation (eELA) method includes receiving, by a responding device from a requesting device, a physical layer protocol data unit (PPDU) including an eELA request message, determining, by the responding device, an eELA feedback message comprising unequal quadrature amplitude modulation (UEQM) information across a plurality of spatial streams based on at least the number of spatial streams derived from the eELA request message or the PPDU, and transmitting, from the responding device to the requesting device, the eELA feedback message. The UEQM information indicates an effective Signal-to-Noise Ratio (SNR) per spatial stream or a derivative of the effective SNR per spatial stream.

The disclosure relates to a 5G or 6G communication system for supporting a higher data transfer rate than a 4G communication system such as LTE. A method of a terminal in a wireless communication system includes receiving, from a base station, a reference signal to be used for measuring channel information for each of at least one slot, including a demodulation reference signal (DMRS) related to reception of a physical downlink shared channel (PDSCH), measuring channel information including an interference amount for each of the at least one slot, based on the reference signal, obtaining slot-related channel information, based on the measured channel information for each of the at least one slot, and transmitting the obtained slot-related channel information to the base station. In the method the slot-related channel information is used to determine a modulation and coding scheme (MCS) level for each of at least one slot group.

The invention belongs to the technical field of wireless communication, and discloses an NTN scene physical shared channel link self-adaption method, which comprises an uplink physical shared channel link self-adaption process and a downlink physical shared channel link self-adaption process. The invention provides a physical shared channel link self-adaption method suitable for an NTN scene. According to the method, the LOS path link budget and the channel measurement value are innovatively combined to carry out inner ring maintenance, meanwhile, the RLC state report is utilized to carry out outer ring maintenance, and the uplink and downlink physical shared channel transmission performance under the NTN scene is greatly improved. According to the method, link adaptive processes are respectively designed for an uplink and a downlink, a theoretical signal-to-noise ratio is estimated through an LOS path link budget formula, calibration is performed by using a channel measurement value, and an accurate inner ring value is generated. According to the innovation, the LOS path signal stability characteristic of the NTN scene is utilized, the problem of performance loss caused by the fact that an existing ground inner ring technology is too conservative in the NTN scene is solved, and the transmission performance is optimized by predicting the inner ring value at the scheduling moment.

The present disclosure provides techniques for dynamic resource management and link adaptation in wireless communication systems. An access point (AR) trains a machine learning (ML) model using a historical dataset. The AR collects real-time input data that indicate characteristics of a link established between the AR and a station (STA) for wireless communication. The AR applies the ML model to the real-time input data to predict one or more network demand values for the link. Based on the one or more predicted network demand values and the real-time input data, the AR determines one or more adjustments to transmission settings of the link. The AR applies the one or more adjustments to the wireless communication with the STA.

Systems and methods for intelligent re-drivers capable of link monitoring and link training in accordance with embodiments of the invention are illustrated. A re-driver in accordance with a first embodiment includes a programmable linear equalizer capable of equalizing a transmitted analog signal to generate an equalized signal, and a variable gain amplifier capable of amplifying the equalized signal to produce an amplified signal. The re-driver further includes a line driver capable of generating an output signal based upon the amplified signal, and digital link adaptation circuitry that is capable of sampling the amplified signal to produce a sampled signal, generating programming parameters for the programmable linear equalizer based upon the sampled signal, and programming the programmable linear equalizer.

The invention discloses a multi-network multi-granularity resource optimization method based on federal deep reinforcement learning, and belongs to the technical field of edge computing and artificial intelligence, and the method comprises the steps: a mobile device senses a local resource state, and maps the local resource state into a structured state vector through a multi-granularity resource mapping module; local FDRL training and global prompt vector generation are carried out; performing pruning optimization on the local FDRL training model, and realizing asynchronous uploading by the multiple heterogeneous hybrid network modules based on a heterogeneous link adaptation mechanism; performing global model aggregation, prompting distillation and joint optimization; and strategy return and iterative closed-loop restarting are carried out. According to the invention, a three-level and multi-granularity state modeling method is introduced to enhance the expression ability; an off-line track guiding mechanism is introduced to realize rapid convergence in a strategy cold start stage; generating acceleration strategy convergence by adopting experience-first sampling + prompt; the uploading overhead is reduced by pruning a local FDRL training model, and the transmission efficiency and robustness are improved by adopting a heterogeneous link adaptation mechanism.

The invention relates to the technical field of Internet of Things communication, in particular to a LoRa network dynamic link self-adaptive control method and system based on environment awareness, and the method comprises the steps that the system firstly presets initial communication parameters for a terminal and collects the data and link information of the terminal; based on the building and traffic data on the transmission path, an environmental perception model is constructed to quantify environmental impact factors, and a dynamic evaluation matrix is established in combination with performance indexes. Calculating the comprehensive performance index of the current link based on the matrix, and predicting the change of the signal-to-noise ratio to obtain a relative difference value; the system generates optimization suggestions of communication parameters by analyzing a performance index change trend and applying an adaptive algorithm, and predicts brought performance improvement. By balancing energy consumption and time delay cost required by performance improvement and adjustment, parameter adjustment is executed only when the income is greater than the overhead. And finally, completing the optimization of all terminals within the fixed network distribution time, and evaluating the overall performance of the network. According to the invention, the accuracy of dynamic link adaptive control of the LoRa network is improved.

Methods and apparatus for indicating unequal modulation (UEQM) parameters for spatial streams between antennae of multiple input, multiple output (MIMO) communication systems are provided. Embodiments enable UEQM by introducing a high-throughput control (HTC) extension field in the medium access control header of data frames. The HTC extension field can include modulation parameters for each of a plurality of spatial streams as well as link adaptation parameters for the communication system. In some embodiments, changes in modulation parameters between consecutive spatial streams are used to indicate the modulation parameters for each spatial stream. In some other embodiments, indices for common combinations of modulations are used to indicate the respective modulation parameters for each spatial stream. UEQM enabled by embodiments may provide an improved throughput and goodput to MIMO communication systems.

The invention relates to the technical field of power transmission lines, and discloses a power transmission line state multi-dimensional sensing method and system based on multi-source data fusion, and the method comprises the steps: dividing the fault evolution into a germination period, a development period and a critical period through a fault layering judgment mechanism, enabling each stage to be matched with a differential caching strategy, and achieving the collaborative optimization of fault data retention and resource utilization. Through a full-link value quantification model, three dimensions of fault state, time decay and data type, confidence gain, link adaptation and redundancy loss correction are fused, a unified priority standard is provided for caching, routing and transmission, and the transmission efficiency of a communication window is improved. A dual-mode reconstruction strategy is adopted, fault physical mechanism deduction and space-time correlation interpolation are combined, missing data are reliably complemented through fusion judgment and conflict analysis, it is ensured that a reconstruction result conforms to a physical rule, and a complete time sequence support is provided for fault traceability.

Methods and apparatuses are described herein for Extremely High Throughput (EHT) link adaptation (ELA). A station (STA) may receive a first physical layer protocol data unit (PPDU) including a first primary secondary (PS)160 subfield and a High Efficiency (HE) / EHT subfield. The HT / EHT subfield may indicate whether a second PPDU that will be transmitted by the STA is based on HE-related parameters or EHT-related parameters. The first PS160 subfield may indicate a primary 160 MHz channel or a secondary 160 MHz channel. The STA may transmit, based on the HE / EHT subfield, the second PPDU including a second PS160 subfield, an EHT-MCS subfield, and a number of spatial streams (NSS) subfield. The second PS160 subfield may indicates a 160 MHz channel determined based on the indication of the first PS160 subfield. An index of the EHT-MCS subfield and a value of the NSS subfield may be determined based measurement of the determined 160 MHz channel.

The invention belongs to the technical field of audio quality analysis, and discloses an algorithm-based audio quality analysis method and system, and the method comprises the steps: employing a lightweight CRNN model to fuse audio-video dual-mode features through the cooperation of a multi-problem joint detection module and a self-adaptive feature fusion extraction module, and carrying out the algorithm-based audio quality analysis. The five problems of abnormal volume, noise and the like are synchronously detected in combination with a multi-task learning framework, and a bottom-layer feature network is shared to avoid parameter conflicts; meanwhile, weighted binary cross entropy loss is introduced, and the detection rate of low-probability problems such as howling and sound interruption is enhanced; compared with a traditional sub-module scheme, the design eliminates the contradiction that noise suppression excessively weakens voice, the multi-problem detection accuracy is remarkably improved, the result consistency is greatly improved, and the accurate detection requirement for concurrency of multiple problems in a conference scene is met; and full-link adaptation is realized through a dynamic parameter adjustment mechanism: the difference perception feature learning expands the normal / abnormal frame feature difference, and the sensitivity of a low signal-to-noise ratio scene is improved.

A method performed by a first network node for configuring a second network node. The method includes transmitting to the second network node a first message for configuring the second network node with respect to the collection of at least first training data for use in producing (e.g., generating or updating) a first model, wherein the first message comprises first data collection configuration information that comprises (i. e., includes at least) one or more of: a first process identifier (e.g., link adaptation or power control) identifying a first process that uses the first model, a first model identifier identifying the first model, or a first model version identifier identifying a version of the first model.

The invention relates to a method for implementing a dynamic link for transmitting data over a communication channel, the method comprising: - obtaining a prediction of an interference on the communication channel, where the prediction is associated with a communication resource of the communication channel, the communication resource being a time resource, a frequency resource or a space resource; - obtaining a coherence characteristic of the interference on the communication channel; and - determining a communication parameter for use in the dynamic link for the communication resource, the determination being based on the prediction of the interference and / or on the coherence characteristic.

The invention discloses a method for carrying out link self-adaption in a retransmission system and a mobile environment, which is characterized by comprising the following steps of: constructing and initializing a reinforcement learning neural network; acquiring information, wherein the information comprises channel condition information and HARQ process information fed back by the current user; monitoring whether a channel environment is switched; constructing an observation state vector according to the information; inputting the observation state vector into a reinforcement learning neural network, and outputting an MCS corresponding to the current HARQ process; transmitting a data packet containing the MCS to the user and receiving feedback information of the user; judging whether the current HARQ process is ended or not according to the feedback information, if so, calculating a retransmission conversion throughput award of the current HARQ process, performing state, action and award alignment integration, storing the state, action and award into an experience pool, and then entering a subsequent step; and training the reinforcement learning neural network based on a gradient descent method according to the plurality of empirical data. The problem that a traditional algorithm cannot adapt to an actual 5G network and a complex and changeable environment is solved.