2074results about "Adaptation strategy characterisation" patented technology

The invention provides an unstructured file parallel synchronization method and system, and relates to the technical field of file synchronization, and the method comprises the steps: carrying out the intelligent partitioning of a target file through a pre-training file partitioning model, and generating a double-layer cascade index number and a data hash value; and then, according to the data transmission priority model, transmitting the data sub-blocks to a target end database through a self-adaptive parallel transmission channel, and performing asynchronous verification. And finally, recombining the data sub-blocks based on the double-layer cascade index number and the data block association graph by utilizing a pre-training file recombining model, generating a synchronous target file, and submitting confirmation information to the block chain network. According to the method, the unstructured file synchronization efficiency can be improved, the data integrity and security are guaranteed, and the network transmission pressure and the storage cost are reduced.

A method for operating a user equipment (UE) in a wireless communication includes obtaining resource configuration information of an uplink signal; obtaining resource configuration information for two-step random access based on the resource configuration information of the uplink signal; determining resources for transmission for the two-step random access based on the resource configuration information for the two-step random access; and performing the transmission for the two-step random access, wherein the transmission for the two-step random access comprises transmitting a preamble on a random access occasion (RO) and transmitting data for the two-step random access on a physical uplink shared channel (PUSCH).

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.

A UE comprises: receiving an upper-layer parameter configuration related to CSI reporting; receiving scheduling information including resource allocation information for a PDSCH; receiving the PDSCH on the basis of the scheduling information; determining an uplink resource for the CSI reporting on the basis of the upper-layer parameter configuration and the scheduling information; and transmitting the CSI reporting in the uplink resource. The transmission of the CSI reporting in the uplink resource comprises transmitting, on the basis of a modulation and coding scheme (MCS) offset table including i) the PDSCH and ii) multiple entry values, one of the multiple entry values via the CSI reporting, wherein the multiple entry values comprise first values representing multiple MCS offsets and a second value which has failed to be mapped to an MCS offset and suspended.

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.

Embodiments provide for an apparatus, method and computer program product at least for training an artificial intelligence decoder using at least an input to a hypothetical artificial intelligence encoder; determining a training dataset comprising the input to the hypothetical artificial intelligence encoder and at least one of: unquantized projected channel state information feedback, or dequantized projected channel state information feedback; transmitting the training dataset to a user equipment; and determining reconstructed channel state information, using the trained artificial intelligence decoder.

The embodiment of the invention discloses a modulation and coding strategy indication method and a corresponding device. The present application is applied to a wireless local area network system that supports one or more of an IEEE 802.11 ax next generation Wi-Fi protocol (e.g., 802.11 be, Wi-Fi 7 or EHT), an IEEE 802.11 be next generation Wi-Fi protocol (e.g., 802.11 bn, Wi-Fi 8, UHR), a Wi-Fi AI, a millimeter wave (mmWave), an ultra wide band (UWB), and a sensing. The method comprises: generating a physical layer protocol data unit (PPDU), the PPDU comprising a first field and a second field, the first field being used for indicating a first modulation and coding policy (MCS) combination, and the second field being used for indicating the number of spatial streams corresponding to one or more MCSs in the first MCS combination; the PPDU is sent; the bit overhead can be saved.

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 relates to an ultra-high-speed large-flow Ethernet data generation system and method. The system comprises a software unit and an FPGA unit. The software unit is used for generating stream template data and issuing the stream template data to the FPGA unit; the stream template data comprises stream template configuration items and dynamic configuration parameters; the flow template configuration item comprises protocol header information, scheduling configuration information, frame length configuration information and load configuration information; the dynamic configuration parameters comprise dynamic jump configuration information, routing table configuration information and the like; and the FPGA unit is used for storing, reading and calculating the issued stream template data, realizing intra-frame jump value calculation, message and IP head checksum generation, Ethernet frame construction and transmission. Through combination of software and hardware methods, the demand quantity of hardware resources can be reduced, the consumption of logic resources of the FPGA unit can be reduced, the phenomena of high and low speed operation environments, network congestion and the like in the existing network can be simulated, and diversified simulation environments can be provided.

The invention discloses a cross-network convergence transmission method and device based on network coding, and relates to the technical field of communication. According to the application type, selecting a coding mode to code the original data packet to obtain a plurality of to-be-transmitted data packets; determining a scheduling scheme based on the network state; according to the data transmission method and device, the coding mode is selected according to the application type, cross-network fusion transmission can be completed based on network coding, and the time delay is reduced while the bandwidth of data transmission is improved.

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 present application belongs to the technical field of communications. Disclosed are a coding method and apparatus, a decoding method and apparatus, and a communication device. The coding method in the embodiments of the present application comprises: a first communication device respectively determining channel capacities of sub-channels corresponding to M bits of a first modulation symbol; the first communication device dividing the sub-channels corresponding to the M bits into T sub-channel groups according to the channel capacities of the sub-channels corresponding to the M bits; the first communication device dividing a codeword sequence having a length of N into T groups to obtain T codeword sub-sequences; the first communication device determining the reliability ranking among the T codeword sub-sequences according to column weights of the T codeword sub-sequences; and the first communication device respectively mapping bits of the T codeword sub-sequences onto the sub-channels of the T sub-channel groups according to the channel capacity ranking among the T sub-channel groups and the reliability ranking among the T codeword sub-sequences.

A communication method and device are applied to the technical field of communication, can be applied to a wireless local area network system of a next generation Wi-Fi protocol of IEEE 802.11 ax, such as 802.11 be, Wi-Fi 7 or EHT, and 802.11 series protocols such as 802.11 bn, Wi-Fi 8, UHR, Wi-Fi AI, millimeter wave (MMW) and the like, and can also be applied to a WPAN system supporting UWB, a sensing system and the like. A first communication device generates a PPDU and transmits the PPDU. The second communication device receives the PPDU and analyzes the PPDU. The PPDU comprises first indication information, the first indication information can be used for indicating a first modulation mode set and a coding rate, and the first modulation mode set is one of N modulation mode sets divided based on W modulation modes. The Q modulation modes in the first modulation mode set are used for modulating the PPDU.

Methods and apparatuses for transmitting and receiving information of different priorities. A method of operating a UE includes receiving a first PDCCH providing a first DCI format. The first DCI format schedules a reception of a PDSCH, includes an MCS field, and includes a priority indicator field. The method further includes determining an MCS table, from a first predetermined MCS table or a second predetermined MCS table, based on a value of the priority indicator field in the first DCI format; determining a modulation order and a code rate from the MCS table based on a value of the MCS field; receiving a TB in the PDSCH according to the modulation order and the code rate; and determining a priority of HARQ-ACK information in response to the TB reception based on the value of the priority indicator field in the first DCI format.

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.

Provided are a method by which a terminal transmits a physical uplink shared channel in a wireless communication system, and an apparatus. The terminal receives a logical channel MCS-related value for each of a plurality of logical channels and a physical channel MCS value for each of a plurality of PUSCHs. The terminal uses the logical channel MCS-related value and the physical channel MCS value so as to transmit each of the plurality of logical channels only through a PUSCH having a physical channel MCS value not exceeding a corresponding logical channel MCS value.

Techniques for adaptively adjusting retry limits and modulation and coding scheme (MCS) thresholds are provided. A first network device receives a traffic flow from a second network device via a wireless network. The first network devices analyzes the traffic flow to identify a network service associated with the traffic flow. The first network device examines one or more predefined network service policies to determine one or more characteristics of the network service. The first network device detects a network congestion within the wireless network. Responsive to detecting the network congestion, the first network device switches to a congestion management mode, which further comprises that the first network device determines one or more network transmission settings for the traffic flow based on the one or more characteristics, and communicates the one or more network transmission settings to the second network device.

The embodiment of the invention provides an air-sea cross-domain communication method and device. The method comprises the following steps: fusing a multi-system communication protocol into a cross-domain communication network protocol through a water surface wireless communication multi-band access technology, and carrying out adaptive networking; the method comprises the following steps: performing dictionary table mapping on original information sent by underwater subsurface buoy sensor equipment to obtain a translated character sequence, constructing a Huffman tree according to the occurrence frequency of each character in the translated character sequence, and generating a Huffman code corresponding to each character according to the Huffman tree; the method comprises the following steps: monitoring channel noise and a channel error rate of an underwater acoustic channel in real time, determining a real-time channel state, determining a channel coding parameter adjustment strategy matched with the real-time channel state through an adaptive algorithm, and dynamically adjusting a coding mode and coding parameters of the channel according to the channel coding parameter adjustment strategy. Uploading the Huffman code to a superior command center through a preset dual channel according to the dynamically adjusted coding mode and coding parameters; according to the invention, the air-sea cross-domain communication efficiency can be effectively improved.

Spectral efficiency aware predictive modulation and coding scheme table selection (e.g., using a computerized tool), is enabled. For example, a method can comprise, based on spectral efficiency key performance indicator data, determining, by network equipment comprising a processor, a predicted spectral efficiency applicable to a user equipment, based on fluctuation key performance indicator data, determining, by the network equipment, predicted spectral efficiency fluctuation applicable to the user equipment, based on the predicted spectral efficiency and the predicted spectral efficiency fluctuation, determining, by the network equipment, a predicted spectral efficiency range, and based on the predicted spectral efficiency range, selecting, by the network equipment, a modulation and coding scheme table, for the user equipment, determined to modify a spectral granularity within the predicted spectral efficiency range to satisfy a spectral granularity criterion within the predicted spectral efficiency range.

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 relates to the technical field of digital coding, in particular to a multi-bit control system based on digital coding, which comprises a network monitoring module, a coding adjustment module, a signal reconstruction module, a fault-tolerant control module and a signal processing module. According to the invention, by dynamically monitoring key network performance parameters such as bandwidth, delay and error rate, network state change is obtained in real time, and intelligent adjustment is carried out on the basis, so that the system can continuously optimize coding complexity and flexibly adjust signal compression ratio according to network conditions, and signals can be efficiently transmitted in a changeable network environment; when a signal is reconstructed, the system can adjust a decoding mode and correct errors based on real-time data feedback by comparing the difference between the reconstructed signal and a target signal, the decoding accuracy and the signal quality are remarkably improved, the power output of a control signal is optimized by means of execution signal data fed back in real time, and the signal stability is further enhanced.

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.