42 results about "Spectrum occupancy" patented technology

The invention relates to the technical field of the Internet of Things, in particular to an intelligent device communication method and system based on the Internet of Things. The method comprises the following steps: acquiring spectrum occupation data, electromagnetic interference mode data and terminal equipment energy state data of a plurality of communication channels in an industrial environment through a preset distributed spectrum sensing network; performing adaptive spectrum analysis processing on the spectrum occupancy data and the electromagnetic interference mode data to obtain channel quality evaluation data including interference source characteristics and channel attenuation characteristics; and according to the channel quality evaluation data and a pre-acquired historical channel performance memory bank, performing priority ranking on the available communication channels to obtain dynamic channel priority data based on time continuity. The spectrum resource allocation condition in the industrial environment is monitored in real time through the distributed spectrum sensing network, the current interference can be identified, and the interference can be pre-judged through an advanced prediction model.

The invention provides a ground satellite signal distributed cooperative processing method and system, and relates to the technical field of communication, and the method comprises the steps: extracting a user MAC address hash value, an emergency priority code and a spectrum occupancy matrix from a synchronous network, and generating a triple feature vector; transmitting the triple feature vectors through a double-layer Mesh network, selecting two reference target points with fixed geographic coordinates on the ground of the disaster area, obtaining three-dimensional coordinates of the reference target points, and constructing a space reference straight line; according to the real-time position data of each node, calculating a vertical projection distance from each node to the space reference straight line, and generating a node offset parameter; and dynamically generating a refraction correction coefficient of the signal propagation path based on a comparison result of the node offset parameter and a preset threshold value, and when the offset exceeds the threshold value, increasing a correction weight by adopting a piecewise linear interpolation method. According to the invention, high-reliability and low-delay emergency communication coverage can be realized.

The invention relates to a spectrum occupancy rate calculation method based on full-band spectrum data, and belongs to the field of radio signal spectrum analysis. According to the invention, based on full-band spectrum data at the same sampling time, frequency band division is carried out, and a full-band signal is divided into a plurality of sub-bands; calculating level thresholds of all sub-bands based on the full-band spectrum data at the primary sampling moment; and estimating the occupancy rate based on the frequency band spectrum data at different sampling moments within the measurement time. According to the method, a plurality of interval thresholds in each sub-band are obtained by means of the histogram, the between-class variance and the like, the method can be used for an abnormal electromagnetic signal monitoring scene, the abnormal signal alarm false alarm rate is further reduced, and the electromagnetic space safety supervision capability is improved.

The invention discloses a sub-Nyquist joint broadband spectrum sensing and automatic modulation classification method based on deep learning. The method comprises the following steps: generating a generation data set for joint broadband spectrum sensing and automatic modulation classification; the method comprises the following steps: modeling a cognitive wireless network combined broadband spectrum sensing and automatic modulation classification system, and carrying out multi-coset preprocessing and analog low-pass filtering on a signal received by a cognitive wireless end; constructing a broadband spectrum sensing and automatic modulation classification neural network and training a model; and the local client combines the off-line broadband spectrum sensing training model and the off-line automatic modulation classification training model to online predict the spectrum occupation condition of the broadband signal and the modulation type of each occupied sub-band signal. According to the method, organic fusion of spectrum detection and modulation identification is realized, the processing efficiency and the intelligent degree of the system are remarkably improved, and the method has good robustness and high accuracy and is particularly suitable for a joint identification task of a multi-user broadband communication signal in a dynamic electromagnetic environment.

A virtual fiber communication system includes a central cloud server that obtains telemetry information from network nodes of wireless backhaul mesh network. The telemetry information includes spectrum occupancy information and UE positioning information. The central cloud server obtains, via blockchain-based spectrum broker nodes, frequency spectrum availability metadata and custom-defined spectrum access parameters of spectrum owner nodes. The central cloud server detects spectrum availability variations across network nodes and determines different routing paths for the first type of UEs designated as premium users. Based on the detected spectrum availability variations across the network nodes and the determined different routing paths, control signals are generated and communicated to the network nodes to assign data streams onto rented or leased spectrum frequencies. One of the determined routing paths is selected for delivery of the data streams to the first type of UEs to meet the custom-defined spectrum access parameters.

Methods, devices, and system for Enhanced Wideband HF data transmission with adaptive interference avoidance and other improvements. Several embodiments describe a mesh network comprising a plurality of transmitting and receiving nodes in a congested band. The network senses the interference spectrum occupancies at a plurality of receiver nodes and synthesizes transmit waveforms at the transmit nodes so that the spectra of the transmit signals fit into the gaps of the interference spectra at the receiver nodes. The waveform is based on FDM, including OFDM, with adaptive tone suppression at the transmitter. The spectrum occupancy information at each node is continually shared in the background among all nodes using a low data rate, Fountain code with erasure sensing at the receivers, which guarantees robust delivery.

This invention provides an intelligent spectrum allocation method and system for adaptive signal-to-noise ratio (SNR) in C+L band optical networks, relating to the field of optical fiber communication technology. The method includes: initializing the C+L band elastic optical network and determining nodes, links, spectrum slots, and time slot resources; receiving service requests and clarifying the source node, destination node, time slot requirements, and capacity; calculating link weights based on transmission distance and spectrum occupancy, and selecting the optimal path; determining the modulation format based on path distance and calculating the required spectrum slots; allocating higher-order modulation to the C band and lower-order modulation to the L band; ensuring continuous spectrum slots and consistent links, otherwise the request fails; selecting the spectrum block with the highest OSNR for allocation, comparing the OSNR with a threshold, and determining whether the request is successful. This invention improves the transmission quality of service requests and enables more comprehensive and accurate resource allocation.

The invention relates to a frequency spectrum occupancy rate calculation method based on a dynamic double-threshold level, and belongs to the field of radio monitoring. The receiver monitors the power of a radio signal of a tested frequency band at a tested place for a long time; continuously acquiring environmental noise samples through a noise sampling channel, and continuously updating background noise features by adopting a sliding window real-time sampling technology; based on a noise baseline, introducing a hysteresis comparison principle, generating a high threshold and a low threshold, and calculating a dynamic double-threshold value; a hysteresis comparison thought is introduced, and a high-low double-threshold judgment mechanism is established; when the signal is between the double thresholds, secondary verification is started, a secondary verification program comprises time domain feature analysis on the signal so as to effectively distinguish weak signals from noise fluctuation, and the misjudgment probability is reduced; and performing statistics on energy of the target frequency band signal within a certain time, and performing signal identification and occupancy rate calculation based on the signal energy and double thresholds. According to the invention, the frequency spectrum occupancy rate measurement accuracy can be effectively improved.

The present application relates to a kind of spectrum occupation degree calculation method based on full-band spectrum data, belong to radio signal spectrum analysis field.The present application is based on the full-band spectrum data of same sampling time, and the full-band signal is divided into several sub-bands;Based on the full-band spectrum data of once sampling time, the level threshold of all sub-bands is calculated;Based on the spectrum data of different sampling time in measurement time, the occupation degree is estimated.The present application obtains multiple interval threshold values in each sub-band by histogram, interclass variance and other means, which can be used in abnormal electromagnetic signal monitoring scene, further reduces the false alarm rate of abnormal signal alarm, and improves electromagnetic space safety supervision ability.

The invention relates to a frequency spectrum prediction method based on a time sequence knowledge graph under a satellite-ground convergence network, and belongs to the field of wireless communication. The method comprises the following steps: S1, constructing a time sequence knowledge graph of the satellite-ground fusion network; s2, discretizing the time information to form a time interval set; s3, performing neighbor aggregation on nodes in the graph based on a structure attention mechanism to obtain structure-enhanced node embedding representation; s4, constructing a time hyperplane set, and calculating the weight of each time hyperplane based on a time attention mechanism; s5, performing weighted fusion on the plurality of time hyperplanes to generate a time attention weighted hyperplane; s6, projecting the structure enhanced node representation to a time attention weighted hyperplane to perform spectrum relation modeling; and S7, outputting a spectrum occupancy prediction result in the target time period. According to the method, the time sequence knowledge graph of the satellite-ground fusion network is constructed, and a structure attention mechanism and a time attention hyperplane mechanism are introduced, so that accurate prediction of the spectrum occupancy state is realized, a time interval with key influence on spectrum prediction can be highlighted, and the accuracy and reliability of spectrum prediction in the satellite-ground fusion network are improved; and technical support is provided for spectrum resource scheduling and sharing.

The present application relates to a kind of discrete shared frequency band spectrum sensing system and method, belong to wireless communication technical field.The system includes base station, edge computing device and several sensing terminals, multiple sensing terminals collect spectrum data and carry out spectrum sensing, and sensing result is sent to base station, and base station forwards sensing result to edge computing device and carries out multiple sensing result fusion processing, and edge computing device is fused after multiple sensing results by a pre-trained binary prediction model Prediction of subsequent multiple time steps of spectrum occupation, and spectrum prediction result is sent to base station, and base station filters idle spectrum frequency point according to spectrum prediction result and carries out communication with sensing terminal.The method is based on the system and carries out discrete shared frequency band sensing, can adapt to the signal coverage range of discrete frequency band, unknown communication system exists and needs real-time spectrum analysis.

The present disclosure relates to a spectrum occupancy prediction, which employs a first trainable module and a second trainable module. The first and the second trainable modules predict spectrum occupancy at a respective first and second communication devices based on past occupancies and / or occupancies in adjacent subband(s). The prediction from the first trainable module and the second trainable module is input to a trainable output (third) module, which then provides the spectrum occupancy prediction.

The invention discloses a multi-channel integrated radio frequency system and a dynamic digital channelization method. The system comprises a plurality of groups of radio frequency front ends and antenna units which are used for sampling signals of different working frequency bands; the digital channel processing unit is used for performing down-sampling and frequency deviation on the broadband signal to form a plurality of narrowband channels; the digital signal parallel processing unit is used for carrying out parallel processing on the digital signals of the plurality of narrowband channels; the spectrum sensing unit is used for performing real-time spectrum detection and channel interference detection and judging a spectrum occupation condition and a spectrum hole; the frequency spectrum decision-making unit is used for carrying out fusion detection judgment, judging the availability of a specific narrowband channel in the whole data link network communication system, and aggregating available channels to form a continuous or discontinuous available frequency spectrum; and the spectrum aggregation and channelization reconstruction unit is used for dividing a plurality of sub-bands, analyzing and filtering by adopting a comprehensive filter bank or a cosine modulation filter bank, and carrying out channel reconstruction. And the purpose of simultaneously resisting partial frequency band blocking interference and narrowband comb spectrum interference can be achieved.

The invention relates to a device, a method and a medium in a spectrum sharing system. There is provided an electronic device comprising processing circuitry configured to: receive a spectrum request from a spectrum request system; and sending heartbeat interval information to the spectrum request system, the heartbeat interval information indicating a heartbeat interval for the spectrum request system to send a heartbeat request, the heartbeat interval information being the shortest spectrum occupancy time predicted based on the spectrum usage data of the spectrum request system.

The present invention provides a metasurface direct modulation MIMO transmitter with out-of-band radiation suppression capability, comprising a digital baseband signal module, a digital-to-analog converter, a radio frequency local oscillator module, a mixer, a horn antenna, and an M×N unit metasurface. The present invention utilizes the digital baseband signal module to map M×N user signals into M×N independent control signals, independently controls the phases of the M×N metasurface units, and transmits information through the phases of the reflected or transmitted waves. The digital baseband signal module generates a periodic time-domain window function waveform that is synchronized with the control signal symbol period. After passing through the digital-to-analog converter, the waveform is mixed with the carrier of the radio frequency local oscillator module and then incident on the metasurface, achieving the purpose of suppressing the out-of-band radiation of the modulation symbol. The metasurface direct modulation MIMO transmitter of the present invention can effectively suppress the out-of-band radiation of the directly modulated symbol through the window function envelope, reduce the spectrum occupancy of the transmitter, and reduce interference to other communication systems.

The invention provides a 5G private network and public network fusion dynamic resource allocation method and system, and the method comprises the steps: employing the historical mean value of the same kind of workdays in the first seven days as a reference basis according to a cleaned spectrum occupation time slot sequence and a base station load sequence, analyzing the change trend of the two sequences in a current specific time period, and obtaining a spectrum occupation time slot sequence and a base station load sequence; determining a fluctuation interval exceeding a historical reference and a key sudden change time point through flow peak monitoring; and if the fluctuation interval exceeds a preset dynamic threshold value, intercepting a spectrum occupation sub-sequence and a base station load sub-sequence corresponding to a high-load time period from the change trend, and calculating and judging whether the resource distribution is not uniform or not through a resource occupation proportion to obtain a resource distribution imbalance state identifier.

The application provides a ground satellite signal distributed cooperative processing method and system, and relates to the technical field of communication.The method comprises the following steps: extracting a user MAC address hash value, an emergency priority code and a spectrum occupation matrix from a synchronization network to generate a triple feature vector; transmitting the triple feature vector through a double-layer Mesh network, selecting two reference target points with fixed geographic coordinates in a disaster area to obtain three-dimensional coordinates and construct a space reference straight line; calculating the perpendicular projection distance of each node to the space reference straight line according to real-time position data of each node to generate a node offset parameter; dynamically generating a refraction correction coefficient of a signal propagation path based on the comparison result of the node offset parameter and a preset threshold value; and when the offset exceeds the threshold value, using a piecewise linear interpolation method to increase the correction weight. The application can realize high-reliability and low-latency emergency communication coverage.

The present invention discloses a method for intelligent allocation of wireless spectrum and collaborative edge computing, which relates to the field of mobile edge computing and wireless communication technology, including collecting spectrum occupancy data and service load data; constructing a spectrum resource allocation matrix based on the spectrum occupancy data, and constructing an edge computing resource allocation matrix based on the service load data; inputting the spectrum resource allocation matrix and the edge computing resource allocation matrix into a trained deep reinforcement learning model, outputting a joint optimization strategy, and performing collaborative scheduling of spectrum resources and computing tasks through a two-way matching algorithm. The present invention realizes real-time monitoring and evaluation of network resource status by establishing a multi-dimensional resource data collection mechanism; realizes quantitative expression and association mapping of heterogeneous resource characteristics by constructing mathematical models of the spectrum resource allocation matrix and the edge computing resource allocation matrix; and adopts a deep reinforcement learning model for strategy optimization to overcome the limitations of traditional fixed rule algorithms.

The present application relates to the field of data fusion transmission technology, and provides a heterogeneous data fusion transmission method and system for airborne multi-mode satellite communications. Real-time communication parameters are obtained, including dynamic spectrum occupancy status, polarization direction differences, and concealed transmission requirement levels; dynamic frequency hopping control instructions are generated based on the time-varying characteristics of the dynamic spectrum occupancy status to drive carrier switching and retain the spectrum isolation area between adjacent carriers; orthogonal polarization diversity analysis is performed on the carrier switching results based on polarization direction differences to suppress cross-polarization interference and output multi-path baseband signals; modulation parameters are determined by calling the preset waveform parameter library according to the concealed requirement level, and the baseband signal is loaded onto the asymmetric phase subcarrier to generate a concealed modulation waveform; the frequency hopping instructions are integrated with the concealed modulation waveform to generate a coordinated modulation instruction, and the radio frequency unit is controlled to achieve anti-interference fusion transmission. The technical solution provided by the present application improves the anti-interference capability of fusion transmission of multi-mode satellite data in a dynamic spectrum environment.

The invention relates to a frequency band adaptive switching method and device based on a star flash wireless microphone. The method comprises the following steps: extracting a spectrum occupancy rate feature, a signal-to-noise ratio feature and a multipath fading feature from a voice frame of a target microphone through short-time Fourier transform and a neural network; calculating a frequency band quality score based on the spectrum occupancy rate feature, the signal-to-noise ratio feature and the multipath fading feature; the Dueling DQN is trained on the basis of the state space and the reward function; controlling the physical layer of the target microphone to be seamlessly switched to the optimal frequency band through the trained Dueling DQN; estimating a real-time packet loss rate through a grouping spraying method based on channel response; on the basis of the real-time packet loss rate, forward error correction and coding are carried out on the voice frames according to grades through Polar codes; and the voice frame in the switching process is recovered through the satellite flash broadcast frame and the SC-List decoder. According to the method, dynamic balance of transmission fault-tolerant capability and efficiency is realized through a scoring function, reinforcement learning and dynamic coding rate adjustment of driving Polar codes.

The invention discloses a high-frequency signal real-time processing system, and relates to the technical field of signal processing, and the system comprises the following components: a data acquisition module which adopts an ultra-miniature structure, takes a high-performance chip as a core, has multichannel direct current coupling, high bandwidth, high sampling rate and precision, and has multiple triggering modes, by integrating an intelligent dynamic spectrum allocation algorithm, the system can monitor the spectrum occupancy condition in the frequency band of the high-frequency signal in real time, and intelligently and flexibly allocate the high-frequency signal to the most suitable frequency band for transmission and processing according to the signal characteristics, the service requirements and the electromagnetic environment condition, so that the utilization efficiency of spectrum resources is improved, and the system is suitable for popularization and application. Compared with the prior art, mutual interference between signals is avoided, the adaptability and flexibility of the system are enhanced, meanwhile, the powerful control and analysis functions of the upper computer processing module provide a convenient data processing means for a user, and the overall performance of the system and the user experience are further improved.

The invention discloses a charging pile dual-mode communication optimization method and device based on dynamic spectrum prediction. The method comprises the steps of obtaining time domain signals of a PLC channel and a wireless channel and performing spectrum analysis; predicting a spectrum occupancy state at a future moment according to a spectrum analysis result; calculating an interference power prediction value according to the prediction result of the spectrum occupancy state, and screening out a subcarrier frequency band meeting an interference tolerance preset condition according to the interference power prediction value; respectively collecting multi-dimensional state parameters, forming a state vector with the interference power predicted value of each frequency band, and obtaining the probability and state value of selecting different frequency bands for transmission based on a reinforcement learning algorithm so as to guide the selection of the optimal frequency band and transmission mode; and adjusting the resource allocation weight of each frequency band and the sending probability of each frequency band. According to the invention, the distribution and transmission probability of spectrum resources in the charging pile dual-mode communication system can be dynamically adjusted, and the anti-interference capability and the spectrum utilization rate of the charging pile communication system are improved.

Methods, devices, and system for Enhanced Wideband HF data transmission with adaptive interference avoidance and other improvements. Several embodiments describe a mesh network comprising a plurality of transmitting and receiving nodes in a congested band. The network senses the interference spectrum occupancies at a plurality of receiver nodes and synthesizes transmit waveforms at the transmit nodes so that the spectra of the transmit signals fit into the gaps of the interference spectra at the receiver nodes. The waveform is based on FDM, including OFDM, with adaptive tone suppression at the transmitter. The spectrum occupancy information at each node is continually shared in the background among all nodes using a low data rate, Fountain code with erasure sensing at the receivers, which guarantees robust delivery.

The invention relates to a spectrum occupancy prediction method fusing an auto-encoder and bidirectional LSTM-Attention, and belongs to the field of intelligent processing of radio signals. The method comprises the following steps: preprocessing a time sequence data set based on a sparse auto-encoder; designing a spectrum occupancy rate prediction model based on BiLSTM-Attention (BiLSTM-Attention); and predicting the frequency spectrum occupancy rate based on the iLSTM-Attention. According to the method, for the problems of data redundancy and relatively high noise when the model processes high-dimensional data, the stacked noise reduction auto-encoder is used for preprocessing the input data, so that the generalization ability of the model is improved. And then, a bidirectional LSTM network is adopted, so that past and future information can be utilized, the model can learn more fully and effectively, and the accuracy of spectrum occupancy prediction is improved.

The invention discloses a text-enhanced multi-mode spectrum occupancy prediction system and a text-enhanced multi-mode spectrum occupancy prediction method, aiming at the problem of spectrum resource shortage caused by rapid popularization of wireless communication, and realizing accurate prediction of a spectrum occupancy state by fusing a spectrogram and text description information. Specifically, the system firstly utilizes a preprocessing module to carry out feature extraction on a spectrogram in a real frequency modulation data set, and adopts a hierarchical fusion strategy to carry out comprehensive processing on multi-modal information in combination with global text description including frequency band use conditions and historical trend information and local text description reflecting detail features of the spectrogram. Then, high-dimensional semantic features formed through the feature fusion module can be used for driving subsequent spectrum occupancy prediction, and the accuracy of complex spectrum pattern recognition is remarkably improved. Experimental results show that the proposed method has obvious advantages in an application scene of dynamic spectrum access, can effectively improve the spectrum resource utilization rate and prediction precision, and has relatively high practical value.

A hybrid DNN method for under-sampling signal classification belongs to the technical field of wireless communication signal processing and artificial intelligence. The method comprises the following steps: constructing data preprocessing and labels of under-sampling signals; constructing a convolutional encoder containing a multi-stage de-aliasing block to extract signal features; constructing a multi-layer perceptron of an explicit noise perception path to generate a context vector representing noise level; using stacked noise-gated Transformer layers to encode sequence S; through explicit noise context perception, using a gating mechanism to automatically suppress noise-dominant feature responses during feature extraction; using a query-based decoding mechanism for modulation recognition in view of the sparsity of sub-band occupation in a wideband spectrum; based on a double-task output head, parallel output of spectrum occupation detection results and modulation classification results; based on a dynamic weighting strategy, optimizing the double-task loss to obtain optimal model parameters, and then realizing accurate classification of under-sampling signals.

The embodiment of the invention provides a signal interference management method and device, management equipment, a program product and a medium, and is applied to the technical field of network communication. The method comprises the following steps: determining a data acquisition strategy corresponding to a target scene according to the type of the target scene; signal data of wireless network signals in the target scene are collected by adopting the data collection strategy, and the signal data comprise at least one of signal strength information, signal-to-noise ratio information and spectrum occupation information; inputting the signal data to a target network model to obtain a prediction result output by the target network model, the target network model being a Markov model trained based on historical signal data in the target scene; and adjusting network parameters of network equipment in the target scene according to the prediction result. By adopting the method, the problem that an existing interference management scheme is difficult to adapt to a rapidly changing network environment and is easy to misjudge can be solved.

This invention discloses a method and system for detecting abnormal signals in the electromagnetic spectrum, relating to the field of electromagnetic spectrum detection technology. The method constructs a spectrum dataset by performing continuous spectrum scanning and timing alignment on the target frequency band; it sets a sliding window and performs statistical analysis on the spectrum data to establish a noise floor benchmark characterizing the background noise level, and compensates for receiver gain drift by incorporating overall spectral energy changes within the window, forming a net boost spectrum representation relative to the noise floor; based on this, it connects and aggregates continuously enhancing time-frequency units in the spectrum to generate candidate events, extracts multi-dimensional features from the event level, and adaptively adjusts the decision threshold based on the spectrum occupancy status to comprehensively judge the candidate events, thereby achieving stable detection and reliable identification of abnormal signals in complex electromagnetic environments.

The invention relates to a double-path fusion spectrum detection method and device, equipment and a medium. The method comprises the following steps: respectively inputting a communication signal into a waveform reconstruction detection channel and a cyclostationary spectrum sensing channel, in the waveform reconstruction detection channel, carrying out signal reconstruction and reconstruction error calculation on the communication signal to obtain a judgment result so as to judge a spectrum occupation state, and in the cyclostationary spectrum sensing channel, carrying out signal reconstruction on the communication signal to obtain a spectrum occupation state; detection results are obtained through cyclic spectrum calculation and feature extraction of communication signals, so that signal features are detected, after the two detection results are fused, comparison is performed through an adaptive threshold, a spectrum detection result is output, and a more comprehensive signal feature analysis capability is provided.