28 results about "Spectrum occupancy" patented technology

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.

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 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 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 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 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.

This invention discloses a method and system for radio resource allocation based on spectrum occupancy data prediction, belonging to the field of radio spectrum allocation technology. It includes constructing a three-dimensional radio strength analysis space; generating radio transmission mapping points with transmission strength and connectivity relationships based on historical terminal usage records; constructing multi-frame real-time radio space dynamic representations; generating simulated radio space dynamic representations containing potential conflicts by adding simulated transmission mapping points to the real dynamic representations; performing frequency band conflict analysis and differential labeling on the simulated dynamic representations, using these as training samples for model training; and inputting the current radio usage situation into the model in real time to predict the three-dimensional signal coverage conflict situation in the short term. This invention achieves accurate prediction and early avoidance of short-term spectrum conflicts driven by historical occupancy data, significantly improving spectrum reuse efficiency and communication reliability in high-dynamic, high-density scenarios.

The invention discloses a spectrum occupancy detection method, a related device, electronic equipment and a storage medium, and the method comprises the steps: obtaining a one-dimensional vector with the same length as the total number of frequency points based on the energy value of each frequency point in the power spectrum density of a to-be-detected wireless signal; remodeling based on the one-dimensional vector to obtain input features of image segmentation network support processing; processing the input features based on an image segmentation network to obtain a prediction mask; wherein the prediction mask is the same as the input feature in size; linear mapping is carried out based on a one-dimensional mask obtained through prediction mask remodeling, and a target mask is obtained; wherein the one-dimensional mask, the target mask and the total number of the frequency points are equal in length, and the target mask comprises a probability value that each frequency point is occupied; and determining the occupied frequency band interval based on the target mask. According to the scheme, the detection precision of spectrum occupancy can be improved, especially under the conditions of large energy dynamic range, low signal-to-noise ratio and non-stationary noise.

The application provides a complex electromagnetic environment dynamic construction and deduction system based on digital twinning, relates to the technical field of data processing, and comprises a digital twinning bottom model construction module, a state time sequence modeling module, a trigger interval determination module, an influence subgraph generation module, a local evolution update module and an overall fusion generation module; is used for establishing a digital twinning electromagnetic environment model, receiving equipment state data flow and forming a state change record, determining a target trigger interval, constructing an influence subgraph, locally updating a signal coupling relationship and a frequency spectrum occupation state of an affected equipment node, and fusing with an unchanged area result to generate an overall electromagnetic environment deduction result at a current time, thereby improving the accuracy of the system.

The application provides a complex electromagnetic environment dynamic construction and deduction system based on digital twinning, relates to the technical field of data processing, and comprises a digital twinning bottom model construction module, a state time sequence modeling module, a trigger interval determination module, an influence subgraph generation module, a local evolution update module and an overall fusion generation module; is used for establishing a digital twinning electromagnetic environment model, receiving equipment state data flow and forming a state change record, determining a target trigger interval, constructing an influence subgraph, locally updating a signal coupling relationship and a frequency spectrum occupation state of an affected equipment node, and fusing with an unchanged area result to generate an overall electromagnetic environment deduction result at a current time, thereby improving the accuracy of the system.

This invention discloses a dynamic spectrum allocation and multi-path collaborative transmission communication method and system for unmanned platforms. The method involves: first, real-time scanning of the operating frequency band, synchronously collecting signal strength and interference types of the target frequency band, generating a spectrum occupancy heatmap, and classifying interference signals; then, generating an availability probability map of each sub-channel within a future time window to predict the spatiotemporal distribution of interference sources; next, constructing a deep reinforcement learning (DRL) model to achieve dynamic allocation of transmission resources; finally, when the detected interference intensity exceeds a preset threshold, activating a multi-band, multi-path concurrent transmission and network coding mechanism, with the main path using a low-frequency band to ensure coverage, and the backup path using a high-frequency band to ensure rate. The receiving end processes the received data using a confidence-weighted fusion algorithm. The system includes a spectrum sensing module, a decision engine, and a multi-path transmission module. This invention improves communication efficiency and anti-interference performance, is highly adaptable, flexible in deployment, and has good scalability.

The invention provides an intelligent spectrum allocation and optimization method in a satellite communication system, relates to the technical field of satellite communication, and solves the problems of low utilization rate, serious interference and poor dynamic adaptability in traditional spectrum allocation. An intelligent spectrum allocation and optimization method in a satellite communication system comprises the following steps: S1, multi-dimensional spectrum state real-time sensing and modeling: acquiring satellite spectrum occupation, interference temperature, service requirements and position information, and constructing a space-time-frequency three-dimensional state tensor; and S2, intelligent allocation decision based on deep reinforcement learning: defining an allocation action space and a reward function, and generating an optimal spectrum allocation strategy by adopting an attention enhancement DQN network. According to the invention, the dynamic response is enhanced, the burst service distribution delay is less than 1s, the service blocking rate is reduced from 25% to 4%, and the emergency communication guarantee capability is obviously improved; and cross-layer collaborative optimization: realizing end-to-end joint optimization from spectrum allocation to power control in combination with satellite orbit parameters and service QoS (Quality of Service) requirements.

The invention relates to a spectrum sensing system based on cloud edge-end cooperation, which belongs to the technical field of artificial intelligence and comprises cloud side equipment, edge side equipment and end side equipment. Wherein the cloud side equipment is used for training a spectrum sensing teacher model, performing knowledge distillation on the trained spectrum sensing teacher model to obtain a spectrum sensing student model, and issuing the spectrum sensing student model to the edge side equipment for deployment; the end side equipment is used for acquiring real-time signal data and sending the real-time signal data to the edge side equipment; and the edge side equipment is used for deploying a spectrum sensing student model, receiving the real-time signal data sent by the end side equipment, reasoning the real-time signal data by using the spectrum sensing student model, and generating a spectrum occupancy state sensing result. According to the spectrum sensing system based on cloud side-end cooperation provided by the invention, both the real-time performance and the accuracy of spectrum sensing are realized.

The invention relates to a spectrum sensing method for a three-dimensional broadband spectrum sensing communication system, and belongs to the field of wireless communication. The method comprises the steps that two types of input serve as information sources, an initial convolutional layer module extracts time domain and amplitude features, and a double-prior encoder module obtains a comprehensive prior vector; the decoupling convolution layer realizes space, frequency and time feature separation and is fused with prior in a feature linear modulation module; key channel characteristics are highlighted through a multi-head self-attention mechanism module, and a global pooling layer module outputs an occupancy probability and a normalized signal-to-noise ratio respectively; and through final joint loss function optimization, broadband spectrum occupancy detection and signal-to-noise ratio prediction in a three-dimensional air-ground environment are realized at the same time. According to the method, the problems that the detection performance is reduced and the generalization ability is insufficient in a complex channel environment, a long-distance low signal-to-noise ratio condition and dynamic spectrum change are solved.