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280 results about "Channel feedback" patented technology

Large-scale MIMO channel state information feedback method based on FCFNN

The invention discloses a large-scale MIMO channel state information feedback method based on FCFNN, and mainly aims to solve the problems of overlarge technical feedback overhead and poor channel feedback quality in the prior art. According to the scheme, the method comprises the following steps: on a user side, performing two-dimensional discrete Fourier transform and truncation processing on adownlink channel matrix of a space-frequency domain to obtain a channel matrix H; building a channel feedback model including an encoder and a decoder, and training the channel feedback model; placingthe trained encoder and decoder on the user side and a base station side respectively; inputting the channel matrix H into the encoder to obtain a compressed vector h on the user side, and feeding back the compressed vector to a base station; inputting the h into the decoder to obtain a rebuilt channel matrix by the base station; and performing zero-padding and two-dimension inverse discrete Fourier transform on the rebuilt channel matrix to obtain an original space-frequency domain channel matrix. Through adoption of the large-scale MIMO channel state information feedback method, feedback overhead of the channel state information is lowered, and the channel rebuilding quality is improved remarkably. The large-scale MIMO channel state information feedback method can be applied to a large-scale multi-input and multi-output communication system under a frequency division duplex mode.
Owner:XIDIAN UNIV

Power amplifier linearization correcting circuit and method based on multi-channel feedback

ActiveCN102055411ASolve problems that are difficult to achieve high linearityAmplifier modifications to reduce non-linear distortionPower amplifiersNonlinear distortionFrequency spectrum
The invention discloses a power amplifier linearization correcting circuit and method based on multi-channel feedback, relates to a linearization technology in the technical field of communication, and aims to provide a power amplifier linearization correcting circuit and method capable of self-adaptively regulating a predistortion parameter of a system by tracking the linearization characteristic of a radio frequency power amplifier. The power amplifier linearization correcting method is technically characterized in that a signal output by a power amplifier is subjected to frequency spectrumdivision and is coupled to a feedback system by utilizing a plurality of paths of channels; a data recovery circuit recovers a plurality of paths of feedback information to form a path of signal; a predistortion trainer calculates the predistortion parameter by utilizing a baseband signal and a recovered feedback signal; a predistortion trainer A adds a predistortion signal complementing a nonlinear distorted signal of the power amplifier according to the predistortion parameter; and the predistortion signal in the baseband signal is counteracted in the power amplifier, thereby realizing the linearization correction of the power amplifier. The invention is mainly used for nonlinear predistortion correction of a radio frequency signal emission system.
Owner:CHENGDU KAITENG SIFANG DIGITAL RADIO & TELEVISION EQUIP CO LTD

Large-scale MIMO time-varying channel state information compression feedback and reconstruction method

The invention discloses a large-scale MIMO time-varying channel state information compression feedback and reconstruction method. The method comprises the steps that a channel matrix sequence is acquired, T channel matrixes are subjected to DFT separately, and a channel matrix sequence which is sparse in the angle delay domain is obtained; a channel feedback and reconstruction model CsiNet-LSTM isconstructed, the channel matrix sequence is input to a coder, and codewords are output; the codewords are sequentially input to a decoder, and a reconstructed channel matrix sequence is output; the channel feedback and reconstruction model is trained to gradually approximate to the channel matrix sequence to obtain model parameters; each channel matrix in the output reconstructed channel matrix sequence is subjected to two-dimensional inverse DFT, and a reconstruction value of an original space-frequency domain matrix sequence is obtained through recovery; and channel state information to befed back and reconstructed is input to the model, and a reconstruction value is output. According to the method, the feedback overhead of large-scale MIMO channel information can be reduced, the reconstruction precision is improved, and the excellent robustness is particularly achieved on decrease of the compression ratio.
Owner:SOUTHEAST UNIV

Quantization and inverse quantization method in large-scale MIMO channel state information feedback

The invention discloses a quantization and inverse quantization method in large-scale MIMO channel state information feedback. The method comprises the following steps: firstly, acquiring a channel matrix at a user side, and performing two-dimensional DFT on the channel matrix, so that the channel matrix in a space-frequency domain is transformed into a channel matrix sparse in an angle-time delaydomain; secondly, constructing a model Quantized-CsiNet which is subjected to quantized channel feedback and reconstruction; thirdly, training the quantized channel feedback and reconstruction model;secondly, performing two-dimensional inverse DFT on the output reconstructed channel matrix, and recovering a channel matrix reconstruction value of an original space-frequency domain; and finally, applying the trained Quantized-CsiNet model to channel state information feedback in each actual scene, and reconstructing an original channel matrix. According to the method, the quantization module and the inverse quantization module are added into the CsiNet, so that the actually transmissible channel state information bit stream can be obtained, the feedback overhead of large-scale MIMO channelinformation is reduced, the reconstruction precision is improved, and particularly, the method has excellent robustness for quantization errors.
Owner:SOUTHEAST UNIV
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