Channel Estimation Method for Wireless Sensor Networks Based on Joint Block Sparse Reconstruction

Abstract

This invention discloses a channel estimation algorithm and a system of a wireless sensor network based on joint block sparse reconstruction. The algorithm comprises the following steps: S1, initializing an OFDM (Orthogonal Frequency Division Multiplexing) Rayleigh multipath channel parameter; S2, according to the channel parameter, generating a Rayleigh wireless sensor network multipath channel block sparse channel structure and an information bit stream which needs to be sent and contains a pilot frequency sequence; S3, mapping the information bit stream to be a QPSK (Quadrature Phase Shift Keying) symbol sequence, and performing series / parallel connection switch on the symbol sequence to perform IFFT (Inverse Fast Fourier Transform); S4, adding a cyclic prefix CP, and adding an additive Gaussian noise effect in a transmission process; S5, removing the cyclic prefix CP, and performing parallel / series connection switch on the symbol sequence to perform FFT (Fast Fourier Transform); and S6, performing OFDM Rayleigh multipath channel estimation by using the Block Sparse Bayesian Learning model BSBL algorithm based on space-time correlation. By utilizing the algorithm and the system, under the condition of acquiring the same estimation performance, the required amount of the pilot frequencies or the training length is greatly reduced; and the spectrum utilization efficiency and the channel estimation performance of the wireless sensor network are improved.

Description

technical field [0001] The invention relates to the technical field of the Internet of Things, in particular to a wireless sensor network channel estimation method based on joint block sparse reconstruction. Background technique [0002] The Internet of Things has a wide range of uses, covering industrial and agricultural production, environmental monitoring, modern logistics, security and other fields. According to the forecast of the "China Market Intelligence Center", the scale of my country's Internet of Things industry will reach 1 trillion yuan in 2015, and it will exceed 5 trillion yuan in 2020. The Internet of Things can integrate the physical world and the information world well, and fundamentally change the existing IT system. However, the large-scale industrialization of the Internet of Things still needs to solve some key problems, and one of the main technologies of the Internet of Things is the wireless sensor network, and the immaturity of wireless sensor net...

AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved by the present invention is to provide a wireless sensor network channel based on joint block sparse reconstruction that can reduce the complexity of channel estimation and has high algorithm precision in view of the defects of large amount of computation and lack of timeliness in the prior art. estimation method

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