Channel Estimation Method Based on Three-Level Threshold Variable Step Adaptive Compressive Sensing Technology

Abstract

The invention relates to a channel estimation method based on a three-level threshold variable step size self-adaptive compressed sensing technology, which belongs to the technical field of channel estimation. The present invention proposes a channel estimation method based on MVssAMP aiming at the shortcomings of traditional channel estimation schemes. In this method, when the sparsity of the channel is unknown, the pilot of the channel sending end and the pilot of the channel receiving end are known conditions, an initial step size is given, and then the effective control of the step size is realized by setting three thresholds , so that the step size can be increased at a reasonable speed until it is close to the real channel sparsity, at which time the estimation accuracy of the channel is also gradually improved. This method has higher channel estimation accuracy. In addition, the original sparse channel can be accurately reconstructed at the data output end only by inserting a small amount of pilot signals at the data sending end of the channel, so that the insertion method of the pilot signal breaks through the limitation of the Nyquist criterion, greatly saving frequency band resource.

Description

technical field [0001] The invention belongs to the technical field of channel estimation, and in particular relates to a channel estimation method based on a three-level threshold variable step size self-adaptive compressed sensing technology. Background technique [0002] Orthogonal Frequency Division Multiplexing (Orthogonal Frequency Division Multiplexing, OFDM) is widely used in the field of wireless communication, so channel estimation for OFDM systems has become a key technology of wireless channels. Traditional channel estimation methods need to satisfy the Nyquist criterion when inserting pilots, which results in a large number of pilots and low accuracy of channel estimation. Therefore, channel estimation technology has attracted widespread attention. At present, in response to this problem, some scholars have proposed a channel estimation scheme based on compressed sensing technology. With the help of compressed sensing technology, the original sparse data informa...

AI Technical Summary

Problems solved by technology

This method greatly reduces the number of pilot insertions and improves spectrum utilization. However, traditional compressed sensing algorithms such as OMP need to use the channel sparsity as prior information, which makes its application in channel estimation has limitations

Recently, some scholars proposed to apply the sparsity-adaptive compressive sensing algorithm to channel estimation, thus breaking the defect that compressive sensing requires known sparsity in channel estimation, but this technology takes a long time, and the sparsity estimation not very accurate

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