1110results about "Adaptation strategy characterisation" patented technology

The invention provides a task load scheduling optimization method and system for distributed network nodes, and the method comprises the steps: determining a task transmission path between the distributed network nodes according to historical task congestion data and a real-time link load prediction result; adjusting a modulation coding strategy in a task transmission process according to the channel quality parameter on the task transmission path to obtain an adjusted modulation coding strategy; according to an energy consumption demand corresponding to the adjusted modulation coding strategy, combining load distribution of each communication link and each node on the task transmission path to generate a voltage frequency adjustment instruction corresponding to the distributed network node; performing collaborative optimization on the task transmission path, the channel quality parameter and the voltage frequency regulation instruction to generate a task load scheduling strategy; according to the invention, through collaborative optimization of dynamic path selection, adaptive modulation coding adjustment and precise energy consumption regulation, the transmission reliability, energy efficiency balance and system stability of the distributed network in a high dynamic environment are improved.

The present invention relates to the technical field of cross-modal image signal reconstruction. Disclosed is a cross-modal joint source-channel coding and decoding method adaptable to changeable scenarios. The method comprises: first designing a Transformer encoder-based cross-modal channel coding and decoding optimization solution, so as to achieve the performance improvement and robustness of a channel encoder and a channel decoder; then designing a cross-modal source coding and decoding optimization solution for haptic-to-image generation based on a latent diffusion model, so that under an image signal loss scenario, haptic information is used to guide image generation; and finally, incorporating transfer learning technology, so as to reduce additional training costs caused by a system facing changeable cross-modal communication scenarios such as a changeable channel signal-to-noise ratio and different transmission tasks. Under cross-modal changeable communication scenarios, the joint source-channel coding and decoding method provided in the present invention can solve the problems of the inability of a receiving end to well complete image reconstruction, and additional model training costs caused by changeable channel environments and scenarios.

Various embodiments relate to a next generation wireless communication system for supporting a higher data transfer rate and the like beyond the 4th generation (4G) wireless communication system. According to various embodiments, a method for transmitting / receiving a signal in a wireless communication system and an apparatus supporting same may be provided, and various other embodiments may also be provided.

The invention discloses a cloud network fusion data processing method and system, and particularly relates to the technical field of data processing. The method comprises the following steps: constructing a link semantic dynamic graph based on space-time correlation analysis by extracting dynamic semantic parameters of transmission links in a heterogeneous network; and meanwhile, performing multi-dimensional semantic analysis on the cloud data stream to generate a data stream semantic fingerprint. The method comprises the following steps: identifying a semantic conflict type through matching degree analysis, reversely analyzing a node switching sequence and bandwidth fluctuation characteristics of a transmission path for a fragmentation strategy mismatch scene, evaluating the matching degree of a link and data processing logic, and generating a semantic compatibility matrix based on a fragment recombination rule and aggregated context characteristics; and the matching degree and the compatibility matrix are input into a dynamic compensation model, a fragment recombination strategy and a priority remapping rule are generated, whether real-time reconstruction of a data processing engine is triggered or not is judged, dynamic adaptation of network transmission semantics and cloud computing logic is achieved, and the real-time performance of data processing and the resource scheduling efficiency in the heterogeneous environment are improved.

The invention relates to the technical field of data processing and communication, in particular to a multi-source heterogeneous data compression and transmission method and system for an intelligent fusion terminal, and the method comprises the steps: collecting multi-source heterogeneous data from different data sources through the intelligent fusion terminal, carrying out the data preprocessing of the collected multi-source heterogeneous data, and obtaining a data preprocessing result; comprising format unification and noise filtering; establishing a data feature analysis model, and performing feature extraction and classification on the preprocessed data; according to data feature extraction and classification results, dynamic weights are allocated to different types of data, and the data are divided into data blocks of different sizes according to the allocated dynamic weights and data features; for different types of data blocks, the priority of the data blocks is set, a proper compression algorithm is selected for compression, and the compressed data is transmitted through a network. The multi-source heterogeneous data is subjected to feature analysis and targeted compression processing, so that network bandwidth occupation and equipment energy consumption are reduced, and data transmission efficiency is improved.

The deep joint source channel coding method comprises the following steps: a sending end obtains a first semantic feature of a first image, and performs constellation mapping modulation on the first semantic feature to obtain a first initial constellation point; the sending end extracts semantic information of the first initial constellation point, generates a rotation angle corresponding to the semantic information, and rotates the first initial constellation point according to the rotation angle to obtain a first rotation constellation point; the sending end generates a real part interleaving matrix and an imaginary part interleaving matrix based on the first rotating constellation point and the real part and the imaginary part of the channel state information, resorts the real part and the imaginary part of the symbol sequence respectively and then recombines the real part and the imaginary part into a complex signal to obtain a first interleaving signal; the sending end transmits the first interleaved signal to a receiving end through a fading channel, and the receiving end receives a second interleaved signal; the receiving end performs semantic reconstruction decoding on the second interleaved signal to obtain a second image; or, the receiving end performs semantic classification decoding on the second interlaced signal to obtain a second image category.

The invention discloses an efficient photovoltaic inverter communication monitoring conversion method and system, and relates to the technical field of communication monitoring services. The efficient photovoltaic inverter communication monitoring conversion method comprises the following steps: S1, collecting and preprocessing link structure data and field feature data, and constructing a standardized communication transmission data set; s2, analyzing the transmission delay of each level of communication node, and dynamically adjusting a data packaging structure and a main / standby channel forwarding strategy; s3, evaluating the structure mismatching risk of the main channel and the redundant channel, and triggering a path switching and structure recombination process; and S4, integrating delay and mismatch risk analysis results, and dynamically optimizing a link rhythm distribution structure. The problems that delay and distortion are easily introduced due to the fact that inverter data transmission is packaged and decoded for multiple times in different levels of gateways, and an existing system lacks an end-to-end link performance collaborative awareness and optimization control mechanism from the edge side to a cloud platform are solved.

The invention provides a communication segmentation learning system and method for adaptive channel compression, and a medium, and relates to the technical field of segmentation learning and communication compression. The system comprises a plurality of clients, a server side and a channel compression device arranged between the clients and the server side, the channel compression device comprises a channel sensitivity modeling module, a rate distortion adaptive compression module and a cross-client fair coordination module. In a channel sensitivity modeling module, channel importance is dynamically evaluated through intermediate layer activation value fusion; differentiated quantization and compression strategies are designed on the basis of sensitivity scores in a rate-distortion self-adaptive compression module, so that key information is reserved while communication overhead is reduced; and meanwhile, the cross-client fair coordination module realizes balanced distribution of communication resources among multiple clients through a fairness regularization and dual optimization mechanism, so that the influence of excessive compression on global convergence is avoided. According to the method, the communication efficiency and the training stability of segmentation learning in a complex heterogeneous environment are remarkably improved.

The invention discloses an efficient storage and transmission method for monitoring data of a low-voltage power distribution network based on lossy / lossless hybrid compression, and relates to the technical field of data storage and transmission, comprising the following steps: completing data denoising correction at an edge node, and setting a plurality of compression strategies and layering mechanisms; judging whether the data is abnormal or not based on the mahalanobis distance, and selecting a proper compression mode through reconstruction error and bandwidth adaptation; the compressed data is subjected to importance labeling and FEC optimization and then sent to a receiving end, the receiving end evaluates the decoding quality and the packet loss rate, and finally a feedback result is used for online updating of the auto-encoder. According to the method, the differential FEC redundancy rate is allocated, so that the lossless fidelity of a key fault waveform and the high compression ratio of a common periodic signal are considered; and meanwhile, closed-loop self-adaption of compression discrimination, coding and model optimization is realized by utilizing online updating of the variable auto-encoder, so that the storage and transmission efficiency is improved, and the reliability and the real-time performance of the system in sudden failure and network fluctuation scenes are enhanced.

The invention relates to an intelligent water affair remote monitoring and control system based on the Internet of Things, in particular to the field of intelligent water affair remote monitoring and control, and the system comprises the steps: firstly, pre-training a long and short-term memory network model through a cloud, and generating a lightweight edge prediction model to reduce calculation and transmission loads; the data transmission module effectively reduces the occupation of transmission bandwidth based on a dynamic quantization threshold value of a residual error and a differential coding technology, meanwhile, the high precision of the data is kept, the verification feedback module monitors the accuracy of the transmission data in real time through confidence coefficient detection, and triggers model re-calibration when the confidence coefficient is reduced, so that the long-term stability of the system is ensured, and the reliability of the system is improved. The sampling optimization module dynamically adjusts the sampling frequency according to the confidence coefficient and the residual fluctuation characteristics, balance is achieved between bandwidth occupation and reconstruction precision by using the Lyapunov optimization theory, the real-time performance and accuracy of water affair monitoring are improved, and meanwhile bandwidth consumption and energy consumption are effectively reduced.

A wireless device receives one or more configuration parameters for a two-step random access channel (RACH) procedure. The wireless device transmits, based on the configuration parameters, a message, for the two-step RACH, comprising a preamble and a transport block. The wireless device receives, during a discontinuous reception (DRX) active time of a DRX operation of the wireless device, a response to the message. The DRX active time may be based on a time window for receiving the response to the message. The time window may start at least one symbol after a transmission occasion of the transport block.

Methods, systems, and devices for wireless communications are described. A wireless device may perform a probabilistic shaping procedure using a shaping rate that is selected in accordance with a rule associated with a target spectral efficiency value, a modulation order, or both. Similarly, the wireless device may perform a channel coding procedure whose coding rate is selected in accordance with the rule. The rule may correspond to a relationship between the coding rate and the shaping rate. In some cases, the wireless device may select the shaping rate and the coding rate to be predefined values based on a target spectral efficiency value. In some examples, the wireless device may select the shaping rate and the coding rate based on a threshold coding rate, a quantity of punctured nodes used in the channel coding procedure, a quantity of layers corresponding to a multi-layer transmission, or any combination thereof.

A wireless telecommunications apparatus for use in a wireless telecommunications network, the wireless telecommunications apparatus comprising: communication circuitry configured to transmit or receive wireless signals; and control circuitry configured to: control the communication circuitry to receive a first wireless signal, the first wireless signal being comprised in Downlink Control Information, DCI, and indicating a waveform to be used by the wireless telecommunications apparatus when transmitting a second wireless signal; and control the communication Receive first signal (DCI) circuitry to transmit the second wireless signal using the indicated waveform.

The invention belongs to the technical field of information and communication, and relates to an active user detection and data decoding method of an asynchronous massive machine type communication system. Aiming at the problem that the detection and estimation performance is reduced due to unknown user time delay in asynchronous transmission, the method comprises the following steps: initial estimation and preprocessing: detecting initial active users and transmission time delay thereof through correlation peaks, and whitening received signals; the iterative joint detection and channel estimation module is used for iteratively updating channel information and data symbol information for multiple rounds based on a factor graph and a message passing algorithm; the data decoding module is used for decoding data based on a soft decision device; the detection and decoding performance is improved by transmitting external information among the modules; and the time delay parameter updating adopts a greedy search algorithm to obtain the optimal time delay. According to the method, the active user detection rate, the channel estimation precision and the data decoding accuracy under the condition that the receiving and transmitting ends are completely asynchronous are improved.

The invention relates to a dynamic environment adaptive semantic communication system and method, which are used for realizing the whole task-oriented semantic communication, the system comprises a transmitting terminal network, a codebook space, a wireless channel and a receiving terminal network, the transmitting terminal network comprises a feature extractor and a joint source channel encoder, namely a JSC encoder; the feature extractor is used for identifying and extracting features related to a specific task from the original input data; the JSC encoder is used for: mapping the continuous feature vector output by the feature extractor to a discrete symbol representation suitable for wireless transmission; the codebook space is used for mapping a continuous feature vector output by the feature extractor into a discrete codeword index through a vector quantization mechanism; the wireless channel is used for converting the discrete code word index into an electromagnetic signal capable of being physically transmitted and completing a transmission process of the electromagnetic signal in a noise and fading environment; according to the method, the comprehensive performance optimization of task-oriented semantic communication is realized.

The invention discloses a data reading method and system based on an RFID reader-writer, particularly relates to the technical field of radio frequency identification data acquisition, and is used for solving the problem that the communication reliability of an existing RFID system is reduced due to carrier frequency deviation and multipath interference in a high-speed mobile environment. A phase change characteristic and an error rate index are obtained through double-antenna receiving signal analysis, when the error rate exceeds a limit, spatial correlation and error rate distribution difference are jointly analyzed to determine a multipath interference level, and meanwhile, a relative motion state is detected and judged through a phase track curvature characteristic. And dynamically selecting an optimal modulation coding mode to read data again according to the calculated motion speed estimated value and the interference level, thereby realizing the optimal balance between the communication rate and the reliability in the mobile environment.

According to one aspect of the present disclosure, there is provided a terminal including a control unit that determines a Modulation and Coding Scheme (MCS) and a number of repetitions from an MCS field in an uplink grant for repetitive transmissions of an uplink data channel for retransmission in a random access procedure, and a transmission unit that repeatedly transmits the uplink data channel for retransmission in the random access procedure in accordance with the MCS and the number of repetitions.

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.

The invention discloses an underwater communication method and system based on adaptive data compression, which is applied to the field of underwater communication, and comprises the following steps: constructing a thermocline change curve of a target communication water area based on multi-source environment data of the target communication water area; an underwater communication path is constructed according to the position information of the data transmitting end and the data receiving end and the multi-source environment data, and attenuation characteristic change curves of the underwater communication path at different depths are simulated through a thermocline change curve so as to calculate a refraction loss value between the data transmitting end and the data receiving end. And determining a high-loss depth interval in the underwater communication path and setting relay nodes, carrying out differential compression parameter configuration on communication segments of the underwater communication path among the relay nodes, and carrying out compression transmission on underwater communication data of the target communication water area based on differential compression parameters. According to the method, the signal transmission problem under different depths and environment conditions can be better solved, and the data compression effect is optimized, so that the communication efficiency is remarkably improved.

This disclosure provides systems, methods and apparatuses for implementing full-duplex communications at an access point (AP) without configuring or modifying associated stations (STAs) to operate as full duplex devices. In some implementations, the AP may select at least one of one or more first STAs to transmit uplink (UL) data to the AP, determine a downlink (DL) signal-to-interference-plus-noise ratio (SINR) for each of one or more second STAs, select at least one of the one or more second STAs to pair with the selected at least one first STA for concurrent DL and UL communications with the AP based at least in part on the determined SINRs, and transmit DL data to the selected at least one second STA concurrently with receiving at least a portion of the UL data from the selected at least one first STA.

The invention discloses a data full-link dynamic anti-interference optimization transmission method. The method comprises the following steps: S1, constructing a data transmission system architecture comprising a sending end, a transmission link and a receiving end; the sending end detects environment disturbance characteristics in real time, and the receiving end collects receiving signals containing background noise and link distortion; s2, designing a self-adaptive waveform coding strategy at a sending end; s3, performing active channel compensation on a transmission link; channel characteristics are extracted, and channel interference is counteracted in real time through pre-distortion waveform adjustment; s4, deploying an intelligent noise reduction decoding algorithm at a receiving end; a depth feature separation network is constructed, and link residual interference is filtered out by analyzing the time-frequency domain difference between a target signal and a noise component. Through a three-level anti-interference mechanism of adaptive coding of the sending end, active compensation of a transmission link and intelligent noise reduction of the receiving end, the problem that the transmission reliability of signals is reduced due to environment disturbance, channel distortion and noise pollution in a complex environment is solved.

The invention provides a target-oriented video semantic communication system based on a visual model, and the system comprises a semantic extractor which is based on an SAM2 model and is used for processing an original video, generating a segmentation mask and extracting semantic information; the ViMama encoder is used for carrying out channel encoding on the output of the semantic extractor; the channel adaptation module is used for optimizing a coding sequence ViMama decoder based on the signal-to-noise ratio information of a physical channel, and is used for carrying out channel decoding to obtain a feature sequence; and the semantic reconstruction device is used for performing semantic reconstruction based on the feature sequence, recovering data and outputting a target video. According to the method, the problems of large redundant semantic information interference, insufficient deep semantic coding capability and poor communication robustness in a complex channel environment in a video are solved, efficient compression and robust transmission of video data are realized on the premise of ensuring semantic integrity, and the overall performance and adaptability of semantic communication are greatly improved.

This disclosure provides methods, components, devices and systems for signaling designs for unequal modulation and modulation and coding scheme (MCS) indication. Some aspects more specifically relate to user info field designs to support such an unequal modulation indication and / or an MCS indication, including designs for user info fields of multi-user (MU) physical layer (PHY) protocol data units (PPDUs) and of Trigger frames. In some examples, an access point (AP) may configure a user info field to include at least five bits for MCS signaling, which may enable the AP to uniquely identify an MCS from a set of greater than 16 MCSs. Additionally, or alternatively, the AP may configure a user info field to include a subfield indicative of a pattern of modulation schemes (such as an equal modulation or an unequal modulation) across a set of spatial streams allocated for communication between the AP and a station (STA).

Provided is a method of performing, by a user equipment (UE), wireless communication in a wireless communication system, the method including generating a first message and transmitting the generated first message. Here, a transmission format for transmitting the first message may be determined depending on whether transmission profile (Tx profile) information is transmitted from an upper layer of the UE.

The invention discloses a self-adaptive coding modulation method and system for relieving sun-borne interference in an ultra-dense low-orbit satellite network, and aims to improve the reliability and the spectrum utilization rate of satellite network communication. The method specifically comprises the following steps: modeling satellite-ground and inter-satellite communication links of the ultra-dense low-orbit satellite network, and modeling and calculating time generated by the sun and interference to the low-orbit satellite network; the ground station estimates and predicts the satellite-ground channel state, and returns the predicted SNR to the satellite; and according to the SNR returned by the ground station and the SNR generated by the sun, a deep reinforcement learning method is adopted to select a coding modulation scheme to perform downlink data transmission, and whether a lower satellite is selected to perform data unloading and then transmit the data to the ground station is determined. Simulation results show that the bit error rate of the ultra-dense low-orbit satellite network can be effectively reduced, the spectrum utilization rate can be remarkably improved, real-time response and efficient resistance to sun interference can be achieved, the satellite calculation load can be reduced, the comprehensive performance of the system can be improved, and the method has high practical application value.

This document presents one or more advantageous approaches for Reinforcement Learning (RL) powered management of one or more transmission parameters, such as transmit power and diversity, for maximizing the application-layer reliability and availability of a Cyber-Physical System (CPS) with a minimized level of radio / power resource consumption. Example mathematical models are also disclosed and are useful for transforming high-level “intents” (e.g., KPIs that are applicable to industrial automation and control systems) into low-level orchestration objectives that drive the RL-based control. These objectives are subsequently employed in the definition of an RL-powered “orchestrator,” which may comprise an appropriately configured network node or other computing platform associated with the wireless communication network used to provide inter-device communications for a CPS comprising a population of devices. Further, the disclosure details example communication—e.g., observations and corresponding control signaling—between the orchestrator and the environment being managed.

A communication device (200A) includes a communication unit (21) and a control unit (25). The communication unit (21) performs wireless communication with a first communication device (100) that supports in-band full-duplex (IBFD) communication that transmits and receives wireless signals using at least a part of resources of the same frequency and the same time. The control unit (25) measures channel quality with a first communication device (100) at each level of quality of service requested for the wireless communication with the first communication device (100) on the basis of interference from a second communication device (200B) that performs wireless communication with the first communication device (100).

The invention discloses an optimization method and device of a satellite communication channel, terminal equipment and a storage medium, and belongs to the technical field of satellite communication, and the method comprises the steps: through a channel state prediction model, according to a first channel state parameter of the satellite communication channel at a current moment and second channel state parameters of a plurality of historical moments, carrying out the optimization of the satellite communication channel; and identifying the change trend of the satellite communication channel, and predicting the predicted channel state parameter of the satellite communication channel at the next moment. According to the first channel state parameter and the predicted channel state parameter, when it is judged that a fluctuation risk exists in a satellite communication channel, a target modulation coding scheme is generated; and finally, switching the modulation coding mechanism of the satellite communication system according to the target modulation coding scheme, thereby realizing real-time optimization of the satellite communication channel, and solving the problems that the modulation coding mechanism of the satellite communication system is lagged in adjustment and the satellite communication quality is difficult to guarantee.

The invention provides a low-delay high-performance image semantic-channel joint coding system, and relates to the technical field of communication and image processing, and the method comprises the steps that a sending end extracts semantic features through a neural analyzer, and divides the semantic features into a plurality of partitions through a quadtree structure; and coding each partition step by step by using a context-aware feature coding strategy, and finally mapping to a complex value channel symbol to be sent to a receiving end. And a receiving end reconstructs the semantic features through a corresponding decoding and synthesizing module and generates a reconstructed image, so that end-to-end efficient image transmission is realized. According to the method, a context-based partition coding mechanism and a quadtree partition module strategy are introduced into a coding structure, so that the method has higher context modeling capability and parallel processing capability, and the adaptive capability to an image structure and semantic content can be effectively improved; transmission delay can be reduced, and image reconstruction quality and channel interference resistance can be enhanced.

The invention relates to the technical field of wireless communication, and discloses a robust semantic communication method, device and equipment based on sparse vector coding, and the method comprises the steps: extracting continuous semantic features of original data through a semantic encoder model; discretizing the continuous semantic features into index bits through a vector quantization method by using a learnable feature dictionary; the index bit is mapped into a sparse vector by adopting sparse vector coding, and the sparse vector is sent after being expanded by a codebook; and a receiving end identifies the index through a multipath matching pursuit algorithm and reconstructs the original data. According to the method, a semantic feature extraction model, a vector quantization technology and sparse vector coding are fused, and gradient approximation, joint loss function optimization and a transmission parameter dynamic adjustment mechanism are designed, so that the problems of poor digital transmission compatibility and weak channel adaptability of traditional semantic communication are effectively solved; and the semantic transmission reliability and the system resource utilization efficiency under the dynamic channel condition are improved.