MIMO spatial non-stationary channel estimation method based on image contour extraction

Abstract

A spatial non-stationary channel estimation method based on image contour extraction is characterized in that in a large-scale MIMO spatial non-stationary channel moving scene, sparse received signals in an angle time delay domain are represented in an image form, and then the number of estimated paths, the angle of each path and the time delay are obtained by using an estimation algorithm of image contour extraction; after a sparse receiving signal in a space time delay domain is represented in an image form, effective visual region estimation corresponding to each channel path is obtained by utilizing an estimation algorithm of image contour extraction, so that path gain and channel reconstruction are realized; according to the method, an image contour extraction technology and the sparsity of the channel in an angle time delay domain and a space time delay domain are utilized to estimate the angle and time delay of each path of the channel and a visual region which does not depend on sub-array division, and a traditional iterative optimization method is replaced to solve the problem of spatial non-stationary channel estimation.

Description

technical field [0001] The present invention relates to a technology in the field of wireless communication, in particular to a massive MIMO space non-stationary channel estimation based on an image contour extraction technology. Background technique [0002] Most of the existing channel estimation techniques proposed for spatial non-stationary characteristics only involve the situation where both ends of the receiver and transmitter are stationary, but little attention is paid to the computational complexity of the algorithm and the scenario where the terminal is moving. A method design that achieves a good balance between computational complexity. At the same time, regarding the spatial non-stationary characteristics, that is, the consideration of the visual area in the prior art mostly depends on the sub-array division, and inappropriate division settings will inevitably lead to matching errors, thereby causing the performance loss of the reconstructed channel. SUMMARY ...

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Problems solved by technology

[0002] Most of the existing channel estimation techniques proposed for spatially non-stationary characteristics only involve the situation where the receiving and transmitting ends are stationary, but little attention is paid to the computational complexity of the algorithm and the scene where the terminal moves, and there is a lack of performance and Method Design for Better Balance Between Computational Complexity

At the same time, the prior art considers the spatial non-stationary characteristics, that is, the consideration of the visible area, which mostly depends on the sub-array division. Improper division settings will inevitably lead to matching errors, resulting in performance loss of the reconstructed channel.

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