61 results about "Spectrum occupancy" patented technology

Systems, methods, and apparatuses are provided for coarse-sensing modules that are operative for providing initial determinations of spectrum occupancy. The coarse-sensing modules may include a wavelet waveform generator providing a plurality of wavelet pulses, and a multiplier that combines the wavelet pulses with an input signal to form a correlation signal. The coarse sensing modules may further include an integrator that receives the generated correlation signal from the multiplier, where the integrator determines correlation values from integrating the correlation signal, and a spectrum recognition module in communication with the integrator that determines an available spectrum segment based at least in part on the correlation values. In addition, the spectrum recognition module may determine an available spectrum segment by utilizing information from a spectrum usage database, where the spectrum usage database includes information associated with one or more known signal types.

The invention discloses a cognitive radio frequency spectrum perception method based on compressed sensing and a BP (back-propagation) neural network. The method of the invention comprises a training process and an actual detection process. The training process comprises: carrying out compression sampling whose rate is lower than a Nyquist sampling rate on an original signal of cognitive radio; carrying out 1-bit quantification processing on sampling data; taking the compression sampling data after the quantification processing as training input, taking an actual frequency band occupancy situation as training output, and training a BP neural network detector. The actual detection process comprises: carrying out the compression sampling on the original signal of the cognitive radio and carrying out the 1-bit quantification processing on the sampling data; inputting the compression sampling data after the quantification processing into the trained BP neural network detector so as to obtain the output, wherein the output is the frequency spectrum occupancy situation of the cognitive radio. The invention also discloses a cognitive radio frequency spectrum perception system which uses the above method. By using the method of the invention, algorithm complexity is low and real-time performance of the frequency spectrum detection can be greatly increased.

The invention provides a compressed spectrum sensing method based on autocorrelation matrix reconstitution and mainly solves the problem that an existing sensing algorithm is high in sampling speed and large computation overhead. The compressed spectrum sensing method comprises that a secondary user obtains an observation sequence of a frequency spectrum environment through compressed sensing and obtains an autocorrelation matrix estimated value of Nyquist sampling by utilizing autocorrelation vector quantity of a autocorrelation matrix reconstitution Nyquist sample sequence of the observation sequence; a multi-signal classification MUSIC algorithm is adopted to obtain an estimated value of occupied channel number according to a characteristic value of the autocorrelation matrix estimated value; a characteristic spectrum is constructed according to the characteristic value and the estimated value of the occupied channel number, spectral amplitude values corresponding to characteristics of channels are added to obtain a sum, and mark numbers of the occupied channels are judged. By means of the compressed spectrum sensing method, the sampling speed of a secondary user receiving machine can be reduced, algorithm complexity at the reconstitution end is low, and spectral amplitude occupying situation in a cognitive radio system can be judged quickly.

Systems, methods, and apparatuses are provided for coarse-sensing modules that are operative for providing initial determinations of spectrum occupancy. The coarse-sensing modules may include a wavelet waveform generator providing a plurality of wavelet pulses, and a multiplier that combines the wavelet pulses with an input signal to form a correlation signal. The coarse sensing modules may further include an integrator that receives the generated correlation signal from the multiplier, where the integrator determines correlation values from integrating the correlation signal, and a spectrum recognition module in communication with the integrator that determines an available spectrum segment based at least in part on the correlation values. In addition, the spectrum recognition module may determine an available spectrum segment by utilizing information from a spectrum usage database, where the spectrum usage database includes information associated with one or more known signal types.

Systems and methods for determining minimal spectrum occupancy in routing and wavelength / spectrum assignment (RWA / RSA) in an optical network include performing, for a new demand request, a set of binary operations using a binary representation for each wavelength or portion of spectrum over all links in the optical network; and selecting, based on the set of binary operations, i) a route and ii) one of a) a wavelength and b) one or more portions of spectrum for the new demand request.

The invention provides a clustering cooperative spectrum sensing method and system based on dual-threshold energy detection. The method comprises the steps: (101), dividing all sensing users in a sensing network into a plurality of clusters, and selecting a cluster head of each cluster; (102), sensing the local spectrum occupation situation by the sensing users distributed in each cluster locally in the mode of adopting the dual-threshold energy detection, and obtaining detection information; (103) fusing the detection information reported by the sensing users inside each cluster by the cluster head, and making a judgment on the sensing result of each cluster by the cluster head; (104), sending the judged sensing result to a data fusion center by each cluster head, and making a final judgment on the spectrum occupation situation by the data fusion center, wherein the step (102) further comprises the steps of (102-1) determining the number of the sensing users who participate in the cooperation and sense the spectrum occupation situation in each cluster; (102-2) selecting the sensing users corresponding to the number according to the determined number of the users who participate in the cooperation and sensing by each cluster, and sending the local judgment result or sensing information to the cluster head by each cluster.

One embodiment of the invention discloses a method for realizing compatible coexistence of a newly-built NGSO constellation communication system and an existing NGSO constellation communication system. The method comprises the following steps that a satellite of the newly-built NGSO constellation communication system performs control-level signaling interaction with a ground user station through afirst signaling beam, wherein the combined coverage range of the signaling beam of each satellite in the newly-built NGSO constellation communication system ensures that at least one re-coverage range is realized on the earth surface; a newly built NGSO constellation communication system satellite performs service communication with the ground user station through a first user beam, wherein a spot beam of each satellite is controlled to point to different wave positions in different time slots, the fixed wave position forms a first range, and the first range is consistent with the re-coveragerange; and the ground user station acquires current available spectrum resources, and sends position information and spectrum occupation information to the satellite covering the user station throughthe first signaling beam.

The invention relates to the field of wireless spectrum analysis, in particular to a wireless spectrum occupancy prediction method based on an LSTM network. According to the method, the ARIMA model and the Kalman filtering algorithm are combined to overcome the limitation of the ARIMA model, and the initial value of the Kalman filtering algorithm is determined by the ARIMA model and complements each other. Considering that the LSTM neural network has a very strong capturing capability on the nonlinear relationship,, an ARIMA, Kalman and LSTM combined prediction model is constructed, namely, alinear relationship existing in frequency band occupancy rate sequence data is extracted by utilizing an ARIMA and Kalman hybrid model, an unextracted nonlinear part in residual errors of the hybrid model is extracted by LSTM, and fitting information is superposed into the ARIMA and Kalman hybrid model. According to the method, the advantages of ARIMA, Kalman and LSTM networks are combined, the stationary sequence can be analyzed, the non-stationary sequence can also be analyzed, and meanwhile linear and nonlinear information can be well extracted.

In an embodiment of the invention, a system may include a specially configured computer having at least one processor and at least one storage device. The computer may be configured to calculate an estimate of radio propagation and signal strength using a first radio propagation model. The computer may recalculate the estimate of radio propagation and signal strength using one or more additional radio propagation models. The computer may store the recalculated estimate of radio propagation and signal strength in storage.

The invention relates to a clustering cooperative spectrum sensing method for a cognitive radio network, belonging to the technical field of cognitive radio. The method comprises steps of firstly, dividing all sensing users in the cognitive network into a plurality of clusters, and selecting a cluster head of each cluster; then, the sensing users in each cluster sensing the spectrum occupation condition of the local through energy detection, and the cluster head sending the sensed energy detection information to the cluster head for data fusion processing; after data fusion, the cluster head sending a judgment result to a fusion center for data fusion; and finally, the fusion center estimating the signal to noise ratio of each cluster head, comparing the signal to noise ratio with an average value of the signal to noise ratio of all clusters, and finally sensing, according to a comparison result, whether a master user occupies the spectrum. Theoretically, the method can effectively lower the effect of path loss and attenuation on performance detection, the topological structure is easy to manage, and the method is applicable to a large scale cognitive radio network with complicated channel environment.

The invention belongs to the technical field of cognitive radio, and particularly relates to a frequency spectrum prediction sensing method based on an RCS-GRU model. The method comprises the following steps: simulating a channel by adopting an M / M / N queuing theory model; combining and splicing the channel state sequences simulated in the step 1 into a matrix; establishing a convolutional neural network model based on residual CBAM, inputting the spliced channel state matrix set into the model, and extracting features of spectrum occupancy states among channels; inputting the extracted feature data set into a GRU model, mining the features of the channel state in the time sequence, performing spectrum prediction, and outputting the channel state of the next time slot; adopting an Adam optimization algorithm to set a variable learning rate optimization cross loss function to train an RCS-GRU network, and adding a dropout method in the training process; and evaluating the prediction performance of the RCS-GRU by adopting a relation curve of the false alarm prediction probability and the detection prediction probability and a root mean square error (RMSE).

A broadband weighted cooperative spectrum sensing algorithm for resisting intelligent SSDF attacks comprises: firstly, recognizing malicious users by analyzing the characteristics of the intelligent attacks of the malicious users and combining energy preprocessing and principal component analysis; secondly, the center node establishing a reputation model according to the historical and current spectrum judgment results of each neighbor node in the sliding time window, and updating the reputation value of the reputation model in real time; and finally, performing group sparse joint reconstruction based on a prior condition by utilizing the identified observation vector set, and accurately obtaining the spectrum occupation condition of each sub-channel. Simulation results show that comparedwith a traditional R-WCCSS algorithm, the spectrum detection probability of the algorithm under the intelligent SSDF attack is improved by 16.7%, the cooperative spectrum sensing performance of the cognitive network is remarkably improved, and efficient spectrum sharing is achieved.

Systems and methods for determining minimal spectrum occupancy in routing and wavelength / spectrum assignment (RWA / RSA) in an optical network include performing, for a new demand request, a set of binary operations using a binary representation for each wavelength or portion of spectrum over all links in the optical network; and selecting, based on the set of binary operations, i) a route and ii) one of a) a wavelength and b) one or more portions of spectrum for the new demand request.

The invention discloses a method for measuring a spectrum occupancy rate based on a signal moment characteristic. The spectrum occupancy rate is measured by a relation among a channel occupancy rate p of a signal, a relative mean value muR of two moment characteristic signals and a relative variance sigmaR<2> of the signals. Spectrum signals within a specified frequency range are continuously scanned and sampled in a measurement period; an mean value mu and a variance sigma<2> of the signals of each channel are iteratively computed in a time sequence; an mean value muN and a variance sigmaN<2> of the background noise of each channel in the spectrum are obtained; and then the spectrum occupancy rate p of the signals of each channel is obtained. The method overcomes the disadvantages that the prior art sets a threshold according to the experiences, can only measure the signals with a signal-to-noise ratio greater than 15dB, stores a large amount of data and computes in an off-line manner; the provided method is less affected by the signal-to-noise ratio, the strength of the signal and the background noise, sets the threshold without manual operation, achieves quick on-line computation, has small storage and automatically computes the spectrum occupancy rate. The method can be widely applied to the fields of radio monitoring, shared spectrum access and the like.

The invention discloses a ground noise fitting and eliminating method for satellite spectrum situation generation. The method comprises three parts of ground noise data fitting, ground noise elimination and situation prediction, the ground noise data fitting is to sort spectrum data to set a signal threshold, the spectrum data higher than the threshold are considered as signals, the spectrum data lower than the threshold are considered as ground noise, and the spectrum data lower than the threshold are considered as ground noise, therefore, ground noise data are separated, and polynomial fitting is performed on the separated ground noise; the ground noise elimination is realized by subtracting the ground noise data obtained according to a fitting function from original signal data; the situation prediction is to predict the spectrum occupancy state of the online spectrum data according to a model trained by the offline spectrum data. According to the method, the adaptive capacity of the satellite spectrum to noise ground fluctuation can be improved, so that the accuracy of spectrum situation prediction is improved.

The system (400), apparatus (401.j), and method (100) of the present invention provide a way to expand and contract the available wireless channels opportunistically by optimally switching the OFDM carriers. The present invention employs a spectrum occupancy information element (200) and a local spectrum occupancy database (505) respectively for exchange of spectrum occupancy information with other devices and persistent storage of spectrum occupancy information, both of which enable seamless working of agile radios in such a way that their transmission capacity is greatly enhanced.

Provided is an ultra wide band radio-frequency signal generating method and device based on double driving modulators. Corresponding Gaussian pulse signals are adjusted on two phase modulators of the double driving modulators, and then relative time delay, signal amplitude and relative phase shifting between the two Gaussian pulse signals are respectively controlled, so that a transverse electric mode which passes through a polarization controller generates ultra wide band radio-frequency signals through the double driving modulators. According to the method and device, four different kinds of UWB pulse signals which comprise one-order UWB pulse signals, two-order UWB pulse signals, three-order UWB pulse signals and high-order UWB pulse signals can be generated. Meanwhile, the generated first three kinds of signals can meet the requirement of the frequency occupying range of UWB pulse signals given by FCC, accordingly, the complexity degree of a flexible UWB pulse signal generating device is greatly lowered, cost is low, and UWB pulse signals can be generated easily and flexibly.

A statistical method for dynamic spectrum occupancy measurement. The implementation steps are as follows: 1) with the sampling step f3, performing M (img file= '998175DEST_PATH_IMAGE001. TIF' wi= '19' he= '20' / ) for monitoring frequency band (img file= '991539DEST_PATH_IMAGE 002. TIF 'wi=' 19 'he=' 19 ' / ) sub-spectrum monitor sampling, The returned sample values are column vector snapshots (img file= '683552DEST_PATH_IMAGE003. TIF' wi= '139' he= '26' / ); 2) The receiver interference tolerance is (img file= '420563DEST_PATH_IMAGE004. TIF' wi= '26' he= '19' / ). For frequency points (img file= '881632DEST_PATH_IMAGE005. TIF' wi= '21' he= '23' / ), the field strength (img file= '311476DEST_PATH_IMAGE006. TI F 'wi=' 24 'he=' 24 ' / ) to compare and determine that interference tolerance value (img file =' 553102DEST_PATH_IMAGE004. TIF 'wi=' 26 'he=' 19 ' / ), Take (img file= '765908DEST_PATH_IMAGE007. TIF' wi= '47' he= '24' / ), If (img file= '409379DEST_PATH_IMAGE008. TIF' wi= '63' he= '24' / ), then(img file= '183694DEST_PATH_IMAGE009. TIF' wi= '44' he= '22' / ); 3) sample snapshots were divide into (img file = '912615DEST_PATH_IMAGE010. TIF' wi= '17' he= '18' / ) groups, Data matrices (img file= '991430DEST_PATH_IMAGE010. TIF' wi= '17' he= '18' / ) were obtained (img file= '427090DEST_PATH_IMAGE011. TI F 'wi=' 23 'he=' 20 ' / ), Select near (img file= '198737DEST_PATH_IMAGE005. TIF' wi= '21' he= '23' / ) (img file= '87059DEST_PATH_IMAGE012. TIF' w i= '33' he= '19' / ), is a (img file= '218832DEST_PATH_IMAGE010. TIF' wi= '17' he= '18' / ) data matrix (img file= '571315DEST_PATH_IMAGE013. TIF 'wi=' 22'he=' 25 ' / ); 4) Dynamically set the threshold level of the frequency point (img file= '451547DEST_PATH_IMAGE005. TIF' wi= '21' he= '23' / ) (img file= '889481DEST_PATH_IMAGE 014. TIF 'wi=' 35 'he=' 26' / ) and determine possession, take (img file=' 636331DEST_PATH_IMAGE015. TIF 'wi=' 50 'he=' 23 ' / ); If (img file= '108901DEST_PATH_IMAGE016. TIF' wi= '65' he= '26' / ), then (img file= '160034DEST_PATH_IMAGE017. TIF' wi= '46' he= '26' / ); (img file= '85264DEST_PATH_IMAGE018. TIF' wi= '20' he= '25' / ) is (img file= '745790DEST_PATH_IMAGE005. TIF' wi= ' 21 'he=' 23 ' / ) correspond to that field strengthvalues in the data matrix (img file =' 807287DEST_PATH_IMAGE013. TIF 'wi=' 22 'he=' 25 ' / ); 5) Statistical spectrum occupancy (img file= '91638DEST_PATH_IMAGE005. TIF' wi= '21' he= '23' / ) (img file= '441848DEST_PATH_IMAGE019. T IF 'wi=' 140 'he=' 37 ' / ). This method realizes the measurement and statistics of dynamic spectrum occupancy, reduces the monitoring time, improves the calculation precision, and can effectively reflect the occupancy of different frequency bands in real time.

The invention discloses an asymmetric baseband coding method. A rectangular pulse g0 (t) and a rectangular pulse g1 (t) indicate a binary digit 0 and a binary digit 1 respectively; the rectangular pulse g0 (t) comprises c narrow pulses with pulse widths tau; c tau can be infinitely small, so that coding waveforms are infinitely close to periodical waves; asymmetric degree can be controlled by selecting different modulation parameters, so that different spectrum masks are realized, and different channel or spectrum occupancy requirements are met. The invention further provides an asymmetric baseband transmitting-receiving device. A transmitting device comprises a coding module, a clock generator, a carrier modulation module, a filter module and a digital-to-analog converter, and a receiving device comprises an analog-to-digital converter, a filter module, a phase-locked loop, a clock module and a matching detection module. Equivalent or high-speed data transmission can be realized by the aid of less sideband energy, so that the use ratio of a frequency band is increased.

The invention discloses a method and a device for determining bandwidth usage amount, and relates to the technical field of communication. The method comprises the following steps: firstly, obtainingthe uplink and downlink frequency spectrum occupation number of a shared operator of a shared network; and then, determining the bandwidth usage amount of the shared operator according to the uplink and downlink frequency spectrum occupation number of the shared operator. The uplink and downlink frequency spectrum occupation number comprises the PRB occupation number of the PUSCH and the PRB occupation number of the PDSCH. Because the uplink and downlink frequency spectrum occupancy number is not easily influenced by factors such as channel quality and transmitting power, and the bandwidth usage amount of the shared operator through the uplink and downlink frequency spectrum occupancy number of the shared operator in the provided method is more accurate than the bandwidth usage amount of the shared operator through the throughput capacity of the shared operator in the existing method. Therefore, the bandwidth usage amount determination method and device provided by the invention can solve the problem that the bandwidth usage amount of the shared operator determined by the existing bandwidth usage amount determination method is inaccurate.

The invention discloses a frequency domain-based frequency spectrum data cleaning method in civil aviation very high frequency communication, and relates to the field of civil aviation radio signal processing, and the method comprises the steps: S1, carrying out the smooth processing of an original frequency spectrum signal, and obtaining a first frequency spectrum signal; s2, roughly judging whether noisy signals of all frequency points exist or not; s3, counting the maximum value position of each frequency point in the first frequency spectrum data in a frequency domain; s4, screening the spectrum data of the corresponding frequency points; s5, slicing and recombining all frequency point data and forming tensors; after data cleaning is carried out on the frequency spectrum data, frequency spectrum prediction data with higher quality can be obtained, so that the quality of a frequency spectrum data sample for subsequently training an intelligent frequency spectrum prediction neural network model is ensured, and the prediction capability of the intelligent frequency spectrum prediction neural network in a complex electromagnetic environment is improved; finally, the purpose of improving the accuracy and reliability of intelligent spectrum occupancy prediction is achieved, and important technical support is provided for improving the very high frequency voice communication frequency utilization rate of an airport terminal area and guaranteeing the aviation operation safety of the airport terminal area.

The invention provides a frequency spectrum dynamic control method and system for an OFDMA backscatter network, and the method comprises the steps: 1, enabling a central control node to obtain networkfrequency spectrum occupation information, and reading the number of active nodes in a frequency spectrum and the total number of current sub-channels; 2, enabling the central control node to encodethe total quantity of the sub-channels, and broadcasting the wireless channels after modulation; 3, enabling a backscatter label to decode the broadcasted modulated wireless channel through a demodulation circuit to obtain a new sub-channel total amount, and taking the sub-channel total amount as a parameter to control the symbol rate in the backscatter communication process. According to the invention, the problem of frequency spectrum waste of a large-capacity OFDMA backscattering network under the condition of a small amount of equipment is solved; the method can also be used for adjustingthe data rate of the network, and the communication reliability can be improved by reducing the symbol rate or increasing the symbol length under the condition that the SNR of the network is poor.

The invention provides a spectrum feature visualization device and a spectrum feature visualization method, used for displaying time occupancy rates and space occupancy rates of comprehensive frequency and different industrial utilization frequency, and a maximum value, a minimum value and an average value of level / field intensity from different angles such as frequency domain, space and time by using charts. Measurement on the spectrum occupancy rate is performed by using a Poisson distribution mathematical model, the situation that the measured spectrum occupancy rate has a reasonable confidence interval can be ensured, furthermore, in the case of same confidence level and relative accuracy, the quantity of sampling points is much less than that of the sampling points in the prior art, particularly under the condition of high occupancy.

The invention discloses a method for processing spectrum occupancy. The method comprises the following steps: obtaining original data to be processed, and comparing the obtained original data with a threshold to obtain a judgment matrix; processing the data of each frequency point according to a preset time interval to obtain a one-dimensional array; and sequentially processing each frequency point in a frequency band, and combining a series of obtained one-dimensional arrays into a two-dimensional array. The invention further discloses software developed according to the method and based on LabVIEW, and the obtained two-dimensional array is displayed by an intensity graph. By adopting the method disclosed by the invention, a user can observe the change of a spectrum with time more stereoscopically and intuitively.

The invention discloses a method and a device for measuring frequency spectrum occupancy rate, wherein the method comprises the steps as follows: comparing the received signal field strength with a threshold level to obtain sequences of comparative results, performing analytical calculation for the sequences of the comparative results according to the distribution rule of a first-order Markov chain, and calculating value of the frequency spectrum occupancy rate as well as fiducial interval and relative precision of the value of the frequency spectrum occupancy rate. The device for measuring frequency spectrum occupancy rate disclosed by the invention comprises a radio frequency receiving module, a detection comparing module, an occupancy rate calculating module, a comparison feedback module and an output module. The method and device of the invention can be used for measuring the occupancy rate by performing dependent sampling under the condition of considering channel transmission correlation, and ensuring the fiducial interval and relative precision of the value of the frequency spectrum occupancy rate. The method of the invention is more reasonable than a method for calculating the frequency spectrum occupancy rate by adopting poisson's distribution mathematical model which samples independently in the prior art.

The invention discloses an electromagnetic environment complexity assessment method based on time-frequency space-energy modulation domain analysis. The method comprises the following steps: S1, performing index assessment on electromagnetic environment complexity through power density, signal duration of a complex electromagnetic environment, frequency coverage, space coverage, signal density and signal pattern; S2, completing characterization model modeling of the electromagnetic environment in four latitudes of time domain feature, space domain feature, frequency domain feature and energy domain feature through the evaluation indexes generated in the step S1; S3, respectively and correspondingly establishing a time occupancy index, an airspace coverage rate index, a frequency spectrum occupancy index and an energy domain average power density spectrum index according to the modeled time domain feature model, the modeled airspace feature model, the modeled frequency domain feature model and the modeled energy domain feature model, and analyzing occupancy rates of a time domain, an airspace and a frequency domain; and S4, performing numerical index quantification on the electromagnetic environment complexity through a complexity evaluation formula, and establishing an electromagnetic environment complexity grade according to a quantitative index.

The present invention provides a spectrum sharing method and apparatus. The method comprises: a second base station detecting first spectrum occupancy information sent by a first base station; and then, the second base station scheduling data by means of a first spectrum when the second base station does not receive the first spectrum occupancy information sent by the first base station, or the second base station receives the first spectrum occupancy information sent by the first base station and determines that a first occupancy priority sent by the first base station is lower than a second occupancy priority of the second base station. It is achieved that different base stations schedule data on a same spectrum, and interference generated when the different base stations use the same spectrum is decreased, thereby improving the spectrum utilization efficiency and a system throughput.

The invention relates to the field of wireless spectrum analysis, in particular to an LSTM network-based wireless spectrum occupancy prediction method. The invention combines the ARIMA model and the Kalman filter algorithm to overcome the limitations of the ARIMA model, and the initial value of the Kalman filter algorithm is determined by the ARIMA model, which complements each other. Considering that the LSTM neural network has a strong ability to capture nonlinear relationships, the present invention will construct a combined prediction model of ARIMA, Kalman and LSTM, that is, use the ARIMA and Kalman hybrid model to extract the linear relationship existing in the frequency band occupancy sequence data, and the LSTM will The unextracted nonlinear part of the remaining residual of the mixed model is extracted, and the fitting information is superimposed into the ARIMA and Kalman mixed model. Therefore, the present invention combines the advantages of ARIMA, Kalman and LSTM networks, can analyze both stationary sequences and non-stationary sequences, and can also extract linear and nonlinear information well.

The invention provides a clustering cooperative spectrum sensing method and system based on dual-threshold energy detection. The method comprises the steps: (101), dividing all sensing users in a sensing network into a plurality of clusters, and selecting a cluster head of each cluster; (102), sensing the local spectrum occupation situation by the sensing users distributed in each cluster locally in the mode of adopting the dual-threshold energy detection, and obtaining detection information; (103) fusing the detection information reported by the sensing users inside each cluster by the cluster head, and making a judgment on the sensing result of each cluster by the cluster head; (104), sending the judged sensing result to a data fusion center by each cluster head, and making a final judgment on the spectrum occupation situation by the data fusion center, wherein the step (102) further comprises the steps of (102-1) determining the number of the sensing users who participate in the cooperation and sense the spectrum occupation situation in each cluster; (102-2) selecting the sensing users corresponding to the number according to the determined number of the users who participate in the cooperation and sensing by each cluster, and sending the local judgment result or sensing information to the cluster head by each cluster.

The invention discloses a method for measuring a spectrum occupancy rate based on a signal moment characteristic. The spectrum occupancy rate is measured by a relation among a channel occupancy rate p of a signal, a relative mean value muR of two moment characteristic signals and a relative variance sigmaR<2> of the signals. Spectrum signals within a specified frequency range are continuously scanned and sampled in a measurement period; an mean value mu and a variance sigma<2> of the signals of each channel are iteratively computed in a time sequence; an mean value muN and a variance sigmaN<2> of the background noise of each channel in the spectrum are obtained; and then the spectrum occupancy rate p of the signals of each channel is obtained. The method overcomes the disadvantages that the prior art sets a threshold according to the experiences, can only measure the signals with a signal-to-noise ratio greater than 15dB, stores a large amount of data and computes in an off-line manner; the provided method is less affected by the signal-to-noise ratio, the strength of the signal and the background noise, sets the threshold without manual operation, achieves quick on-line computation, has small storage and automatically computes the spectrum occupancy rate. The method can be widely applied to the fields of radio monitoring, shared spectrum access and the like.