8 results about "Spectrum occupancy" patented technology

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.

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.

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.

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 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.