58 results about "Basis expansion" patented technology

The invention is a method for improved active sonar using a singular value decomposition filtering and a Volterra-Hermite Basis Expansion to model real active sonar measurements. The fitting model minimizes the sum of the squared errors between a measured channel response, z(t), and model response, y(t), which is a fitted Volterra Series solution. The model requires as input an excitation waveform, x(t), to which is fitted the model response, y(t). A contracted broadband cross-ambiguity function is used to correct the excitation waveform for Doppler and range effects. Once completed, the modeled response can be used to determine the linearity or non-linearity of the channel effects. Appropriate measures can be utilized to reduce these effects on the measured channel response.

The invention discloses an OFDM system channel estimation and signal detection method based on a basis expansion model, and belongs to the technical field of wireless and mobile communication. The OFDM system channel estimation and signal detection method specifically comprises the following steps of OFDM signal sending through a sending end, receiving end channel modeling, initialization, estimation of a basis expansion model coefficient, channel equalization and signal detection, iteration and output. In the receiving end channel modeling step, a receiving end frequency domain signal is subjected to interference and separation of useful information; on the assumption that the initialization step is not restricted by a cyclic prefix, the basis expansion model coefficient is estimated, and data symbols which are sent currently are obtained through detection; inter-symbol interference frequency response and the frequency response of a reconstituted part of a cyclic prefix are obtained in the iteration step, and therefore influence caused by inter-symbol interference is removed. By means of the estimation method, on one hand, channels with obvious time-varying characteristics can be estimated; on the other hand, the inter-symbol interference caused by multi-path time delay can be eliminated effectively, channel estimation and signal detection of an OFDM system in a double-selection channel are completed, and system performance is improved.

A method and system realize reliable wireless communications in non-coherent multiple-input multiple-output (MIMO) doubly-selective channels. The method uses Grassmannian space-time-frequency block codes and an iterative generalized likelihood ratio test (GLRT) with a multi-dimensional basis expansion model (BEM), decision reordering, and a fixed number of surviving candidates. The computational complexity of a non-coherent MIMO equalizer becomes linear as a function of a code length and a size of a modulation alphabet. The codebook, the alphabet size, the bit labeling, and the block power are optimized using worst-case channel statistics or instantaneous channel states. The method can use soft-information feedback from error correction codes, such as low-density-parity-check codes to improve performance.

A method and apparatus for analysis of molecular combinations featuring two or more molecular subsets is described. The method computes the shape complementarity of the system utilizing a basis expansion representing molecular shapes of the first and second molecular subsets in a coordinate system. The precomputed sets of translated expansion coefficients for the first molecular subset are first constructed via application of a translation operator to a reference set of expansion coefficients and then stored on a computer recordable medium for later retrieval. Then a shape complementarity score, representing a correlation of the first and second molecular subsets, is computed via suitable application of rotation operators to both the stored translated expansion coefficients of the first molecular subset, and the reference expansion coefficients for the second molecular subset, over the sequence of different sampled configurations for the molecular combination. The application of a translation operator prior to one or more rotation operator(s) has significant and beneficial implications for hardware-based implementations of the method, embodiments of which in the context of a hardware apparatus will also be described.

The invention provides an MIMO system channel estimation method and device in a 60GHz indoor scene, and relates to the field of communications. The method comprises the following steps: obtaining a first channel estimation value of each user equipment; carrying out two-dimensional discrete Fourier transform on the first channel estimation value to obtain a spatial pattern point set; grouping all user equipment according to the spatial pattern point set, using the same pilot frequency on the same group of users, and obtaining a second channel estimation value of each user equipment in each group to realize the MIMO system channel estimation in the 60GHz indoor scene. According to the MIMO system channel estimation method in the 60GHz indoor scene provided by the invention, the discrete Fourier transform is used as a spatial basis expansion model of orthogonal basis to parameterize a user equipment channel, thereby reducing the dimensionality of an unknown channel parameter, reducing training and feedback costs and easing pilot frequency pollution.

The invention discloses a method for obtaining parity check matrix of rate-compatible low-density parity-check codes, comprising the following steps of: selecting a mother code matrix and determining the size of a basic extension matrix; dividing the basic extension matrix into six sub-matrixes (see the formula at right side); according to a minimum ring maximum principle, respectively determiningthe value of each sub-matrix; subsequently combining each sub-matrix to form the basic extension matrix; finally correcting the obtained basic extension matrix by using a current extension factor z and extending the corrected basic extension matrix by using a matrix P with the size of z*z, thus obtaining a parity check matrix; and using the parity check matrix to carry out the LDPC coding to thedata to be coded. When the method and the coder are applied,on one hand, the rate compatibility can be realized; on the other hand, as the minimum and maximum principle is adopted to determine the value of each sub-matrix in each basic extension matrix, the decoding performance can be improved compared to the LDPC codes realizing rate-compatibility by a punching way.

The invention discloses an OFDM (orthogonal frequency division multiplexing) channel estimation method based on a symmetrical basis expansion model for a quick time-varying channel, and provides an estimation method for the quick time-varying channel. Under complex channel environments of high speed, medium speed, low speed and the like, existing channel estimation methods based on the basis expansion model have poor robust feature. Channel estimation based on the symmetrical basis expansion model is provided. A pilot frequency symbol Y(p) is extracted from a frequency domain receipt signal Y(k). According to the pilot frequency symbol Y(p), a basis coefficient vector corresponding to channel multipath time-domain impact response is estimated by the symmetrical basis expansion channel model. According to the coefficient vector, a time-domain channel matrix is calculated, so that the channel impact response is acquired, and channel estimation is completed. The method is low in complexity, and is a novel high-precision estimation method for the quick time-varying channel. The method can be used in various communication systems adopting OFDM to modulate so as to estimate the channel, and can also be used in a code division multiple access (CDMA) system and a time division multiple access (TDMA) system so as to estimate the channel.

The invention belongs to the field of wireless communication and relates to an iterative method based on channel estimation errors and data detection errors. The method includes that pilot frequency is inserted according to a comb mode during data sending, and data are sent on different antennae; the data are sent to receiving antennae through a wireless channel, and the channel is subjected to modeling at a receiving end by a basis expansion model (BEM); channel BEM coefficient is subjected to modeling by an autorregressive (AR) model; a filter is subjected to initialization and a time updating equation is calculated; filter noise removal is performed and channel estimation is performed; an estimated value of a channel matrix is calculated; a covariance matrix of the channel estimation errors is calculated to perform successive interference cancellation (SIC) data detection. By means of the iterative method based on the channel estimation errors and the data detection errors, a channel estimation and joint detection algorithm is provided, error information in channel estimation and data detection is fully utilized, the accuracy of channel estimation is improved, and correction of data detection is enhanced.

The invention is a method for improved active sonar using a singular value decomposition filtering and a Volterra-Hermite Basis Expansion to model real active sonar measurements. The fitting model minimizes the sum of the squared errors between a measured channel response, z(t), and model response, y(t), which is a fitted Volterra Series solution. The model requires as input an excitation waveform, x(t), to which is fitted the model response, y(t). A contracted broadband cross-ambiguity function is used to correct the excitation waveform for Doppler and range effects. Once completed, the modeled response can be used to determine the linearity or non-linearity of the channel effects. Appropriate measures can be utilized to reduce these effects on the measured channel response.

The invention discloses a multi-symbol joint channel estimation method in high speed mobile environment, wherein the method is based on an OFDM wireless communication system, and a channel estimation method based on pilot frequency is used. The multi-symbol joint channel estimation method in high speed mobile environment comprises the following steps of: 1) modelling for a time frequency double selective channel through a complex exponential-basis expansion model; 2) calculating the number J of joint estimation OFDM symbols, meeting that the channel corresponding to J continuous OFDM symbols has joint sparse property; 3) for the J continuous OFDM symbols, designing a sparse pilot frequency mode, and deriving a channel estimation model; 4) obtaining optimal pilot frequency position distribution through a discrete random optimization algorithm; 5) reconstructing a sparse coefficient through a block synchronization orthogonal matching pursuit (BSOMP); 6) recovering a channel tapping coefficient according to a coefficient reconstructed by a BSOMP algorithm; 7) performing piecewise linear smoothing for the channel tapping coefficient obtained through estimation. The multi-symbol joint channel estimation method in high speed mobile environment can effectively resist time frequency double selective fading, and can improve channel estimation accuracy and spectrum efficiency.

A method of equalizing a signal received over transmission channel defined by BEM coefficients of a basis expansion model of its channel taps, comprising the step of approximately solving the relation (I) for x[n] by an iterative method, n being the index of time, y[n] being the received signal, x[n] being the equalized signal, Bm[n] being the mth basis function of the basis expansion model, M being the model order of the basis expansion model, and blm, being the BEM coefficient of the mth of the basis function of the / th channel tap, and w[n] being optional noise.y[n]=∑m=0MBm[n]·(∑l=0L-1blmx[n-l])+w[n](I)

The invention discloses a multi-antenna transportation communication network system and a signal detection method. The multi-antenna transportation communication network system comprises a transmitting end and a receiving end. A spatial multiplexing technique of a multiple-input multiple-output system is adopted for the transmitting end, and a plurality of transmitting antennas are mounted on vehicular nodes or roadside nodes, so that transportation communication signals can be transmitted by the aid of MIMO (multiple-input multiple-output) channels; according the receiving end, a plurality of receiving antennas are mounted on the vehicular nodes or roadside nodes for receiving signals, and the signals which are received on the various antennas are combined with one another, so that the signals can be jointly detected. The signal detection method includes modeling transportation communication channels at the receiving end by the aid of a basis expansion model, and estimating basis coefficients on the basis of channel models by the aid of a channel estimation process to obtain channel information; detecting the signals according to the obtained channel information by the aid of a sphere detection process. The multi-antenna transportation communication network system and the signal detection method have the advantages that transmission bit error rates of transportation communication networks can be effectively reduced, and the complexity can be effectively lowered.

A method and apparatus for analysis of molecular combinations featuring two or more molecular subsets is described. The computational method estimates the electrostatic affinity of the system via utilization of a basis expansion representing charge density and electrostatic potential functions associated with the first and second molecular subsets in a coordinate system. An electrostatic affinity, representing a correlation of the charge density and electrostatic potential functions of the first and second molecular subsets, is computed via suitable application of translation and rotation operators to the basis expansion coefficients over a sequence of different sampled configurations for the molecular combination. The method may also be combined with other methods for computation of shape complementarity in determining a composite or augmented score reflecting both electrostatic affinity and shape complementarity for configurations of a molecular combination.

A method and apparatus for analysis of molecular combinations featuring two or more molecular subsets is described. The computational method estimates the electrostatic affinity of the system via utilization of a basis expansion representing charge density and electrostatic potential functions associated with the first and second molecular subsets in a coordinate system. An electrostatic affinity, representing a correlation of the charge density and electrostatic potential functions of the first and second molecular subsets, is computed via suitable application of translation and rotation operators to the basis expansion coefficients over a sequence of different sampled configurations for the molecular combination. The method may also be combined with other methods for computation of shape complementarity in determining a composite or augmented score reflecting both electrostatic affinity and shape complementarity for configurations of a molecular combination.

A method and apparatus for analysis of molecular combinations featuring two or more molecular subsets is described. The method computes the shape complementarity of the system utilizing a basis expansion representing molecular shapes of the first and second molecular subsets in a coordinate system. The precomputed sets of translated expansion coefficients for the first molecular subset are first constructed via application of a translation operator to a reference set of expansion coefficients and then stored on a computer recordable medium for later retrieval. Then, a shape complementarity score, representing a correlation of the first and second molecular subsets, is computed via suitable application of rotation operators to both the stored translated expansion coefficients of the first molecular subset and the reference expansion coefficients for the second molecular subset over the sequence of different sampled configurations for the molecular combination.

A method of correcting a communication signal with BCH product codes is disclosed. The method comprising the steps of receiving a codeword vector, establishing a generator polynomial, establishing a check polynomial, calculating a binary-matrix, and calculating the binary syndrome S=Hrt. If an all zero vector results, no errors exist in the received vector. If errors exist, a tm x (N−k) binary matrix is created, the power basis expansion of (r(α1), r(α3), r(α5), . . . r(α2t−1)) is calculated, and the syndrome is solved. The speed of the method comes from using word-level XOR's to apply the check polynomial to the stream at all offsets. The utility of this approach is due in part to the fact that the conversion matrix involved can be created quickly using only items needed elsewhere in BCH decoders: a field table and the generator polynomial coefficients.

The invention belongs to the field of wireless communication technology, and discloses a simplified BEM channel estimation method for a high-speed mobile SC-FDMA system. The method comprises the following steps: calculating and storing a matrix required to estimate base coefficients in advance, and estimating the base coefficients; and deducing a mathematical relationship between the base coefficients and a frequency domain channel response matrix by using the channel characteristics and the transformation relation of time domain-frequency domain, and estimating a frequency domain channel response of received signals. According to the method disclosed by the invention, a complex exponential basis expansion model with the minimum model error is selected, the number of optimal basis functions is determined, and thus the estimation accuracy can be increased; a frequency domain matrix for estimating the base coefficients is calculated and stored in advance, and the calculation complexity can be reduced; and the mathematical relationship between the base coefficients and the frequency domain channel response matrix is deduced by adopting the time-frequency domain characteristics of a channel, the time-frequency domain conversion process of the channel with higher calculation complexity can be avoided, and the process that a receiver performs frequency-domain equalization processing for the received signals can be facilitated.

The invention discloses a channel estimation method for a comb-shaped pilot frequency OFDM system. The channel estimation method comprises the following steps: presetting an iterative loop time threshold; adopting long and short preambles to carry out OFDM synchronization on a receiving signal, and presetting an initial loop time counting value; extracting each data symbol behind the synchronization position of the receiving signal; estimating the coefficient of a basis expansion model by use of the pilot frequency in each data symbol, and then calculating a channel estimated value of the data symbol corresponding to the time domain; if the loop time counting value is smaller than the preset iterative loop time threshold, executing channel encoding, interweaving and modulation on an obtained sending signal to serve the same as a new receiving signal, and returning to repeat the channel estimation operation; otherwise, in the case of non algorithm convergence before and after iterative loop, adjusting the synchronization position, presetting an initial loop time value, and executing the channel estimation operation again; and otherwise, completing the channel estimation operation, and outputting the decoded sending signal. The channel estimation method disclosed by the invention can be used for improving the accuracy of channel estimation of a high-speed mobile wireless channel.

The invention discloses a method for multi-dimensional joint estimation of dynamic sparse channels under an MIMO system. The method comprises the following steps: (1) modeling a time-frequency doubly selective channel by using a complex exponential basis expansion model; (2) ensuring that BEM coefficients of different antennae and different orders have joint sparsity, and re-arranging basis expansion model coefficients by using the block sparsity to form a block structure; (3) adopting a hierarchical pilot design for multi-antenna scenarios, distributing pilot locations in N sub-carriers with equal intervals, and deducing a channel estimation model; (4), determining the channel sparsity K (j) at the moments corresponding to different OFDM symbols according to the time correlation of the dynamic sparse channels, wherein j is equal to 1, 2, ..., J; (5) reconstructing to obtain a sparse coefficient FORMULA according to the determined sparsity corresponding to each moment; and (6) recovering a channel tap coefficient FORMULA from the sparse coefficient. By adopting the method disclosed by the invention, the dynamic features of the sparse channels can be effectively estimated, the channel characteristics of the dynamic sparse channels can be obtained, and the accuracy of channel estimation and the spectrum utilization can be increased.

The invention belongs to the technical field of satellite communication, and discloses a multi-user detection method for a low-earth orbit satellite random access system based on a CRDSA protocol. Themulti-user detection method comprises the steps that multiple access users transmit user groups to a satellite according to the CRDSA protocol; a satellite receiving terminal sequentially processes aplurality of superimposed user groups on each time slot in a frame according to the CRDSA protocol; the satellite receiving terminal performs modeling on a channel of each user on the time slot by adopting a basis expansion model when processing K superimposed user groups on a certain time slot; solving a base coefficient of each user in a joint manner according to a maximum likelihood method; fitting each user channel by using the solved base coefficients; reconstructing all interference user groups and performing interference elimination by using the top (K-1) pieces of user data which aredetected and decoded when processing other time slots and the top (K-1) fit user channels; detecting and decoding the residual signals after interference elimination; and performing iterative channelestimation and interference elimination by using decoding bits. The multi-user detection method is high in channel estimation accuracy, accurate in interference elimination and low in packet error rate.

The invention provides a channel estimation method, system and device and a readable storage medium. The method comprises the following steps: generating a delay-Doppler domain random sequence matrix, performing constellation mapping, obtaining a target data symbol matrix, and converting the target data symbol matrix into a time-frequency domain data symbol matrix; inserting the pilot frequency matrix into a transmitted time-frequency domain symbol matrix, performing inverse fast Fourier transform after obtaining a time-frequency domain transmitting end symbol matrix, performing parallel-to-serial conversion processing after obtaining a time-domain transmitting signal matrix, transmitting a serial transmitting end symbol sequence to a receiving end, performing serial-to-parallel conversion processing, and transmitting the serial transmitting end symbol sequence to the receiving end; obtaining a time domain receiving matrix of a receiving end and carrying out fast Fourier transform to generate a receiving signal matrix of a frequency domain; and modeling the fast time-varying channel by adopting a basis expansion model, and calculating a received signal after channel estimation according to the restored time domain channel matrix, thereby carrying out symbol error rate performance analysis. The method can be applied to an OTFS system and is compatible with an OFDM system, and the performance of the channel estimation method is effectively improved.

Process for canceling Intercarrier Interference in a OFDM receiver receiving OFDM blocks in presence of Doppler, comprising the steps of: receiving a OFDM block comprising N samples; applying a FFT for the purpose of generating N frequency domain representations composing the received signal (R); multiplying said received signal (R) by the hermitian value of the channel (HH), with H being the channel estimate; applying on said received signal a preconditioned conjugate gradient algorithm based on a N×N P preconditioner matrix; Characterized in that said preconditioner matrix is computed at follows: Formula (19) and formula (20), where formula (I) is a LFIR×PN selection matrix obtained by extracting a predetermined number (LFIR) of rows from the identity matrix IPN, LFIR being a predetermined integer inferior to PN, with p corresponding to the basis expansion order chosen and N is the FFT size; formula (II) is equal to HFH, with H being the frequency-domain channel matrix and F being the N×N discrete-Fourier transform unitary matrix F; formula (III) is the N×N identity matrix; formula (IV) is the varience of the noise; formula (V) is being the 1×N vector containing 1 in n-th position and 0 elsewhere.Sn(I)ℋ(II)I(III)σ(IV)1n(V)fnT=1nℋHℋSnT[SnℋH(ℋℋH+σz2I)ℋSnT]-1(19)G˘=[f0TS0f1TS1⋮fN-1TSN-1](20)

The invention provides a double-expansion underwater acoustic channel doppler diversity communication method based on a basis expansion model. In the method, zero padding suffix repetition code is used on a transmitting terminal, a base elimination algorithm is used on a receiving terminal, a time-varying double-expansion fading channel is decomposed into a time-invariant frequency selective fading component channel set. Then, doppler diversity gain is collected through a multichannel decision feedback equalizer, and intersymbol interference is resisted, and combined with a phase-lock loop, residual doppler distortion is tracked. The underwater acoustic communication scheme uses doppler which is usually seen as harmful component in conventional receiver design as a diversity gain source, effectively improves output signal to noise ratio of the receiver, and reduces error rate of a system. The multichannel decision feedback equalizer is used to reduce dependency on channel estimation of the receiver, and prevents large-matrix inverse operation which is relatively high in computation complexity.

The invention discloses a time-varying channel estimation method and system based on deep learning. A network input sample is reasonably constructed; the method is based on a single hidden layer neural network, and comprises the following steps: firstly, fully utilizing channel change characteristics in historical channel information and other characteristics in a received pilot signal; and further improving the performance of channel estimation by using the advantages of least square estimation; secondly, carrying out offline training on a back propagation neural network by using the constructed sample, and then obtaining time-varying channel information in real time in an online mode. In order to reduce the calculation complexity, only the received pilot signals and the information of the pilot sub-channels are adopted, and the pilot sub-channels are modeled by adopting a polynomial basis expansion model to reduce to-be-estimated parameters so as to carry out time-varying channel estimation. According to the method, the channel estimation precision can be remarkably improved, the calculation complexity is low, and the method is suitable for efficient acquisition of time-varying channel information in a high-speed moving scene.

A joint estimation method of a dynamic sparse channel is based on OFDM (Orthogonal Frequency Division Multiplexing) wireless communication system, and adopts a channel estimation method based on a pilot frequency. The method comprises the following steps: 1) structuring a dynamic sparse channel model; 2) modeling a time frequency doubly-selective channel by using a complex exponential basis expansion model; 3) acquiring an optimal pilot position distribution of J different OFDM symbols sent at J different times by using a discrete stochastic optimization algorithm, designing a sparse pilot frequency mode and deducing a channel estimation model; 4) estimating a sparsity K (j) at the current time j by using a differential symphysis orthogonal matching pursuit (DSOMP) algorithm; 5) and according to the SOMP (Simultaneous Orthogonal Matching Pursuit) algorithm and the sparsity K (j), estimating a channel characteristic of the dynamic channel at the time j. By adopting the method, the dual-selective fading of the time frequency can be effectively resisted; the channel characteristic of the dynamic channel can be estimated; and the accuracy of the channel estimation and the utilization ratio of the frequency spectrum can be improved.

The invention relates to an MIMO-OFDM (Multiple-Input Multiple-Output-Orthogonal Frequency Division Multiplexing) fast time-varying channel estimation method. The method comprises the following steps:S1, inserting an optimal pilot frequency into a subcarrier selected for each OFDM symbol of a transmitting end, and making optimal pilot frequency symbols on any two selected subcarriers alternate; S2, transmitting transmitted data through an MIMO fast time-varying channel after OFDM modulation; S3, performing OFDM demodulation on received data on an mth receiving antenna at a receiving end, thenextracting a received signal on a pilot frequency point, and estimating a channel coefficient from each transmitting antenna to the receiving antenna through a transmitted optimal pilot frequency andthe extracted received signal, wherein the calculated channel coefficient is a channel efficient value (shown in the description) at a middle point moment of the OFDM symbol, t represents a middlepoint moment of a pth OFDM symbol, and n represents an nth transmitting antenna at the transmitting end; and S4, fitting channel coefficient values on other time points of the OFDM symbols by a complex exponential basis expansion model.

The invention discloses a channel prediction method combining deep learning and a basis extension model in the technical field of wireless communication. The channel prediction method comprises the following steps of: step 1, acquiring a correlation matrix of a channel according to channel information at a historical moment; step 2, carrying out eigenvalue decomposition on the correlation matrix to obtain an optimal primary function; step 3, modeling a channel by using the basis expansion model; step 4, acquiring a basis coefficient estimation value based on historically received pilot signals and an optimal basis function; step 5, constructing a training sample set according to the basis coefficient estimation value; step 6, training a BP neural network by using the training sample set; step 7, acquiring a channel prediction model with an optimal weight and an optimal threshold value; step 8, performing online prediction based on the channel prediction model; and step 9, converting the basis coefficient estimation value into a frequency domain channel matrix. The channel prediction method has low calculation complexity and high prediction precision, and is suitable for efficient acquisition of time-varying channel information in a high-speed mobile environment in the future.

The invention discloses a doubly-selective channel estimation method based on V-OFDM (Vector-Orthogonal Frequency Division Multiplexing). A way of adding pilot frequencies and pilot frequency protection intervals in V-OFDM sending data blocks is designed based on the existing V-OFDM transmission mechanism, so that perpendicularity of the pilot frequencies and the data is guaranteed. A BEM (Basis Expansion Model) channel module is utilized to carry out modelling on a channel at a receiving end and pilot frequency parts in the received V-OFDM data blocks are utilized to estimate a doubly-selective channel parameter matrix in the BEM model. In comparison with the conventional doubly-selective channel estimation and transmission scheme based on OFDM, the designed channel estimation scheme has the advantages that the estimation accuracy is improved and the complexity is reduced.

The invention discloses a cooperative spectrum sensing method based on cluster sparsity. The method comprises the following steps: solving the approximate emission power spectrum density phim(f) of a main user m at a position xm through a basis expansion model; partitioning a geographic region A into discrete grid points, wherein the Ng grid points are positioned in a virtual network, so that the receiving power spectrum density of a cognitive user t at a position xt is phit(f), and phit(f) is an approximate value of the power spectrum density of the cognitive user; acquiring a (N*1)-dimension receiving power spectrum density estimated vector; correlating the estimated value with the approximate value to obtain a system model; grouping (NbNg*1)-dimension vectors eta; solving a cluster sparsity (NbNg*1)-dimension vector eta with a FOCUSS algorithm according to the grouping result of the (NbNg*1)-dimension vectors eta; and estimating eta to obtain a bandwidth occupied by the main user and the position of the main user. Through adoption of the cooperative spectrum sensing method, information of spectrums can be acquired without re-judgment of recovered spectrums.

The invention discloses a communication symbol detection method and device, and a computer readable storage medium, and the method comprises the steps: filtering a communication symbol according to afunction expression of a transmission channel corresponding to the communication symbol on a preset basis expansion model when the communication symbol is detected, and obtaining a filtering signal; determining probability distribution of the filtering signal on preset signal classification, and determining a log-likelihood ratio of the communication symbol according to the probability distribution; and determining the type of the communication symbol according to the log-likelihood ratio, and completing the detection of the communication symbol. According to the invention, the symbol detection accuracy is improved from the aspects of channel representation, filtering processing and the like, and the detection performance is improved.