8 results about "DFT matrix" patented technology

The embodiments of the present application relate to the field of communications. Provided are a communication method and apparatus, which can meet precoding requirements in a complex communication scenario. The method comprises: acquiring a first precoding matrix, and sending first information, wherein the first information is precoded by the first precoding matrix, the first precoding matrix is a precoding matrix in a precoding matrix set, the precoding matrix set is associated with the number of antenna ports of a terminal device and the number of transmission layers of the terminal device, the precoding matrix set comprises N precoding matrices, and any non-zero element in any precoding matrix among the N precoding matrices meets wi, a substrate w being determined by means of a discrete Fourier transform (DFT) matrix with a length of X, the value of X being associated with the number of antenna ports, and the number of antenna ports being an integer multiple of 3, where i=0, 1, 2,..., X-1, and N is a positive integer.

The present application belongs to the technical field of calibration of phased array radar, and relates to a two-stage grouping asynchronous rotating electric vector radar array antenna calibration method, and the specific process is as follows: an attenuator and a phase shifter are configured to each element channel of the array antenna to be measured, and signals received by all channels are synthesized through a power divider; the phased array radar to be measured is equally grouped by channel number in a first stage; a grouping matrix is constructed based on a Hadamard matrix, and the channels grouped in the first stage are divided into rotating groups and fixed groups according to elements in the grouping matrix; a phase shift matrix for phase shift measurement of each row in different grouping matrices is constructed based on a discrete Fourier transform matrix with an order of N, and phase shift is performed; linear equations are constructed according to measurement results and solved, and the ambiguity coefficient, the amplitude of each channel and the phase difference between each channel are obtained, and each field normalization amplitude and phase is solved; amplitude and phase compensation of the channels is completed based on each field normalization amplitude and phase, and finally the amplitude and phase of all channels are consistent.

A receiver processes a radio signal received via a radio channel from a transmitter employing a plurality of antenna ports, determines complex precoder coefficients and delays of one or more space-delay precoders for one or more transmission layers and antenna ports at the transmitter so as to achieve a predefined property for a communication over the radio channel, and feeds back, explicitly or implicitly, delays and the complex precoder. The space-delay precoder has a dual-stage structure having a spatial codebook matrix including spatial beamforming vectors, a frequency-domain codebook matrix, and a combining element per layer for complex scaling or combining one or more of the vectors selected from the spatial and / or frequency-domain codebook matrices. The frequency-domain codebook matrix is defined by a sub-matrix of a DFT matrix, which the sub-matrix of the DFT matrix is associated with a range of delay values.

The present application provides a communication method and a communication system. The communication method, applied to a transmitter, includes: collecting a bitstream; modulating and converting the bitstream and obtaining a frequency domain signal matrix; multiplying the frequency domain signal matrix with an inverse approximate Discrete Fourier Transform (DFT) matrix and obtaining a time domain signal matrix; post-processing the time domain signal matrix and obtaining a time domain signal, and sending the time domain signal to a receiver connected with the transmitter. The communication method, applied to a receiver, includes: receiving a time domain signal from a transmitter connected with the receiver; pre-processing the time domain signal and obtaining a time domain signal matrix; multiplying the time domain signal matrix with an approximate DFT matrix and obtaining a frequency domain signal matrix; demodulating and converting the frequency domain signal matrix and obtaining a bitstream.

The embodiment of the application provides a communication method and device, relates to the field of communication, and more types of waveforms are introduced for communication or sensing by setting waveform parameters, so that flexible configuration of different waveforms can be realized. In the method, a first device determines a second signal according to a third signal and a first pre-processing matrix selected from a first pre-processing matrix set, so as to determine a first signal according to the second signal. By setting the first pre-processing matrix set to include a unit matrix and at least one first type of matrix, or to include a DFT matrix and at least one first type of matrix, the first type of matrix is not a square matrix, or neither a unit matrix nor a DFT matrix, more types of waveforms can be introduced for communication or sensing. Different pre-processing matrices are configured to realize flexible configuration of different waveforms, so that different service requirements in the communication or sensing scene can be met.

The application relates to a multi-dimensional fast Fourier transform acceleration method based on matrix operation in the field of computing power optimization. The method comprises the following steps: S1, applying for a computing resource, copying computing data to device global memory on the host side, generating a DFT matrix and an input data matrix; S2, reading the DFT matrix data and the input data matrix from the global memory to a register and a shared memory; S3, using multi-thread parallelism to complete the calculation task of matrix element multiplication of the input data matrix and a rotation factor matrix, and obtaining intermediate calculation result data; S4, calling a matrix operation unit to perform matrix multiplication on the intermediate calculation result data obtained in the step S3 and the DFT matrix, and outputting final calculation result data; and S5, copying the final calculation result data from the device global memory to the host memory on the host side, and releasing the computing resource. The application adopts matrix operation to calculate multi-dimensional FFT, and uses a high-performance matrix operation unit of a GPU to accelerate the calculation, so that the FFT calculation efficiency on the GPU is improved.

Signal processing methods based on compressed sensing (CS) theory, intended to solve storage space and communication limitations in a Nyquist sampling framework, have attracted increased attention in recent years. In conventional harmonic detection, sparse bases are typically represented by a discrete Fourier transform (DFT) matrix. Harmonic non-synchronous sampling inevitably leads to spectral leakage and fence effect. To address this issue, we present an improved CS model for harmonic detection in power systems. A windowing technique is introduced in the compression sampling process. The fixed-point continuation algorithm combined with interpolation technique is used to directly extract harmonic parameters from the sparse coefficients without reconstructing the original signal. The proposed harmonic detection method, using an improved CS model, can achieve an accuracy comparable to that of the windowed interpolation FFT algorithm.