687results about "Adaptation strategy characterisation" patented technology

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.

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.

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.

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.

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 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.

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 discloses a low-delay lossless digital audio transmission method, a low-delay lossless digital audio transmission system and a storage medium, which relate to the technical field of digital audio transmission and are used for monitoring network environment data in real time and dynamically adjusting audio transmission parameters according to changes of network bandwidth Bw, network delay Dr, packet loss rate Pd and network jitter Wd. Comprising an audio transmission rate Rsv, a data packet size Spd and a redundancy coding ratio Rbf. The adaptive adjustment can ensure that the data transmission quantity is reduced and the packet loss probability is reduced when the network condition is poor, and meanwhile, the transmission efficiency is improved and the audio quality is optimized when the bandwidth condition is good. Compared with a traditional fixed transmission parameter method, lossless audio transmission can be achieved under different network conditions, and meanwhile unnecessary delay is reduced. According to the invention, intelligent compression of the audio data is realized, the data volume is reduced under the condition that the bandwidth is limited, the network burden is reduced, and the stability and integrity of audio transmission in a low-bandwidth environment are ensured.

The invention provides a dynamic coding and decoding negotiation method based on link state quality. The dynamic coding and decoding negotiation method comprises the following steps: grouping reference station RTCM data and determining the priority of the RTCM data according to the message ID of the RTCM data; based on the determined first strategy selection mode, the RTCM data is subjected to check code generation, character coding and encryption in sequence, and the strategy selection mode of the base station is synchronized to a strategy selection module of the moving station; after the moving station receives the data, decryption, character decoding and verification are sequentially carried out on the encrypted data based on the information synchronized by the strategy selection module; meanwhile, the moving station counts the packet loss rate and the verification failure rate of the RTCM data in real time; and adjusting the strategy selection mode of the next group of data according to the quality of the current link, the system load and the priority of the RTCM data until all grouped data are sent. According to the invention, a real-time closed loop is provided, and the link quality is evaluated more comprehensively.

The application discloses a kind of method for determining channel parameter, device, equipment and storage medium, the method includes: based on data sending end, the target transmission power of monitoring bandwidth is determined;The data sending end detects the state information of data receiving end, then the data sending end determines the bandwidth to be selected matched with the data receiving end, and obtains the target SNR of each the bandwidth to be selected;The data sending end obtains the reference MCS set of each the bandwidth to be selected based on the target SNR;The data sending end obtains the target throughput of each the bandwidth to be selected based on the reference MCS set;The data sending end determines the working throughput based on the target throughput of each the bandwidth to be selected, and determines working bandwidth and working rate based on the working throughput.The technical scheme of the application can determine the working bandwidth and corresponding working rate that obtain the maximum throughput.

The present disclosure relates to communication methods and communication apparatuses. One example method includes obtaining p groups to be transmitted on a first resource, where the p groups belong to N downlink channel state information CSI) reports, p is an integer greater than 1, and N is an integer greater than 1, and sending a part or all of the p groups on the first resource based on priorities of the p groups, where the priorities of the p groups are based on priorities of the N CSI reports, the priority of the CSI report is based on a type of the CSI report, and a type of at least one of the N CSI reports is an artificial intelligence (AI)-related type.

Systems, methods, apparatuses, and computer program products for semantic communication involving joint source and channel coding (JSCC) over current communication networks. One method may include receiving, by a first network entity, from a second network entity, a multi-level bit error rate (BER) interface configuration comprising at least one BER based upon the request for a communication session; generating, by the first network entity, an application source encoder and decoder configured to encode and decode, respectively, a plurality of levels corresponding to the at least one BER; and training, by the first network entity, the application source encoder and decoder according to the BER.

The invention discloses a wireless communication method, device and equipment and a readable storage medium, and belongs to the field of communication, and the method comprises the steps that first equipment obtains target output related information, the target output related information is output related information meeting a first channel condition and / or a first quality requirement, and the target output related information is output related information meeting the first channel condition and / or the first quality requirement; the first channel condition is a channel condition for transmitting a first information source, and the first quality requirement is a quality requirement of second equipment on the first information source; the first device performs coding processing on the first information source according to the target output related information to obtain first coding information; and the first device sends the first coding information to the second device.

The invention discloses a chirp interval modulation backscatter communication method and a chirp interval modulation backscatter communication system based on variable-length scrambling codes, which mainly solve the problems of high power consumption of backscatter labels and high system deployment cost in the prior art. According to the scheme, a sending end sends an environment LoRa signal; the backscattering label modulates information to be sent to an environment LoRa signal in a time interval modulation mode, and modulates a variable-length scrambling code to an anchor symbol; a receiving end performs frequency shift compensation on the backscattering signal by adopting a frequency shift compensation method, demodulates the backscattering signal by combining a sliding window with a variable-length scrambling code, intercepts a backscattering signal sample through the sliding window, and performs de-spreading and fast Fourier transform (FFT) on the signal in the window; the position of an anchor symbol is determined by detecting the maximum value of an FFT peak value, information sent by the backscattering label is recovered from the position of the anchor symbol, and data demodulation is completed. On the premise of keeping demodulation reliability, the power consumption of the tag is effectively reduced, the deployment cost of a backscatter communication system is reduced, and the method can be used for ultra-low power consumption Internet of Things communication.

The invention discloses a cross-domain information distribution method and system for multi-link cooperative networking, and relates to the technical field of network communication, and the method applied to an information sending end comprises the following steps: obtaining a link quality prediction result of each data transmission link based on the computing power level of an information receiving end and the link quality prediction result of each data transmission link; and dynamically selecting a main transmission path and at least one backup path of cross-domain information from all data transmission links. And based on the link quality of the main transmission path, performing fragmentation processing and coding processing on the to-be-distributed data to obtain a plurality of to-be-distributed data packets. And transmitting the to-be-distributed data packet to an information receiving end through the main transmission path and the backup path, so that the information receiving end decodes and recombines the to-be-distributed data packet. According to the method, the stability, the real-time performance and the resource utilization efficiency of cross-domain information distribution for multi-link cooperative networking are effectively improved, and the transmission performance of cross-domain data transmission is remarkably improved.

The invention provides a 2M non-framing double-path protection intelligent switching method and system based on redundancy check, and relates to the technical field of communication, and the method comprises the steps: obtaining double-path 2M non-framing code streams, carrying out the alignment processing, generating a check result through employing cyclic redundancy check, carrying out the statistics of error code feature vectors in a sliding time window, and constructing a link quality track. According to the method, the quality degradation early warning signal is extracted, the stage switching strategy is constructed based on the early warning signal, the switching time sequence is determined in combination with the neural network evaluator, link switching is executed, self-adaptive optimization of the switching strategy is achieved, and the intelligence and reliability of link switching are improved.

A forward error correction code switching method applied to a first device includes determining a target operational forward error correction code according to predetermined transmission channel quality and a target traffic requirements; and notifying a second device of the target operational forward error correction code to enable the second device to switch a current operational forward error correction code to the target operational forward error correction code, and decodes user traffic data according to the target operational forward error correction code.

A modulation and coding scheme indication method and a corresponding apparatus in a wireless local area network system that supports one or more of a next-generation Wi-Fi protocol of IEEE 802.11ax (for example, 802.11be, Wi-Fi 7, or EHT), a next-generation Wi-Fi protocol of IEEE 802.11be (for example, 802.11bn, Wi-Fi 8, or UHR), Wi-Fi AI, a millimeter wave (mm Wave), an ultra wideband (UWB), and sensing (sensing). A method includes: generating a physical layer protocol data unit PPDU, where the PPDU includes a first field and a second field, the first field indicates a first modulation and coding scheme MCS group, and the second field indicates a number of spatial streams corresponding to one or more MCSs in the first MCS group; and sending the PPDU. This can reduce bit overheads.

The invention relates to a digital semantic communication method combining learnable constellation mapping and channel adaptation, and belongs to the technical field of communication. According to the method, a semantic coding modulator is constructed, and the transition probability from an information source to a discrete constellation symbol is systematically learned, so that the problem that digital modulation cannot be differentiated is solved; a semantic coding process is dynamically adjusted based on a channel state information feedback mechanism of double attention, and an efficient matching relationship between semantic features and subcarriers is ensured. A neural network is designed to combine a multipath channel which cannot be trained but can be differentiated with an OFDM signal processing module, and end-to-end cross-layer joint optimization of the system is realized.

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.

A method for transporting data block includes: determining an initial transport block size (TBS) according to received current downlink control information (DCI); acquiring current first channel state information (CSI) and second channel state information (CSI) acquired last time; adjusting the initial TBS according to the first CSI and the second CSI to obtain an adjusted TBS; and sending, according to the adjusted TBS, uplink data corresponding to the current DCI to a base station.

Methods and apparatuses for radio communication. The method includes transmitting first information that characterizes at least one quality associated with a downlink channel received by a radio terminal and transmitting second information that characterizes a present or future environmental situation of a physical entity that is associated with the radio terminal.

The invention discloses a self-adaptive compression and lossless fast transmission method and system for high-frequency test data. The method comprises the following steps: extracting multi-dimensional dynamic feature vectors from high-frequency test data in real time and marking feature points; based on the features, the network bandwidth and the target compression ratio, dynamically selecting a compression algorithm combination and parameters through a pre-training decision model; performing data framing and typed preprocessing according to the algorithm combination; compression is executed through a multi-stage assembly line, and a correction link based on statistical characteristics is inserted between stages; constructing a three-dimensional transmission state matrix fusing priorities, links and quality scores, dynamically allocating links and adaptively adding forward error correction codes; and after error correction and decompression of a receiving end, realizing lossless verification through multi-dimensional comparison of feature point sequences of the reconstructed data and the original data. According to the method, the whole-course self-adaption of the compression strategy and the transmission scheduling is realized, and the lossless and reliable recovery of the data is ensured while the compression and transmission efficiency is improved.

The present invention concerns a method for carrying out a semantic communication within a semantic communication system (10) defining a semantic communication channel, the semantic communication system (10) comprising a sender (12) and a receiver (14) connected through a wireless channel (16), the method comprising the following phases: - semantic communication setting comprising determining multiple semantic functions to be embedded into a waveform; - semantic adaption of the waveform to embed the multiple semantic functions; - semantic transmission of the adapted waveform in a form of an electromagnetic signal.