Research On The Wireless Multipath Channel Estimation Algorithm Based On Compressed Sensing

Under normal circumstances, communication can be divided into two categories: wired communication and wireless communication. Cellular mobile, broadband wireless access, microwave relay, satellite wireless communications, etc, are all belonged to the category of wireless communication. They disseminate information through wireless electromagnetic waves in the air, and have characteristics of information unpredictability, using flexible and convenient and so on. Thus channel estimation plays an important role in wireless communication.In recent years, research on compressed sensing theory in the field of wireless communications has made great progress. The impulse response of the wireless multipath channel in CS theory using is sparse, Which makes it possible to meet the requirement of reconstructing the original signal. Based on this, the CS theory has a broad prospect in the wireless multipath channel estimation.In this thesis, the main content of the CS theory is described. And the signal reconstruction algorithm in CS theory is classified, the key research on several typical algorithms in greedy algorithm is made, details of the geometric model of several algorithms are introduced. Then, the traditional two typical algorithms channel estimation method is introduced, and their mathematical models are described in detail. Finally, the research and the analysis of the CS theory in channel estimation are made by using the characteristic of the sparsity in wireless multipath channel.This thesis mainly focuses on the following two points:The matching pursuit algorithm, orthogonal matching pursuit algorithm, regularized orthogonal matching pursuit algorithm, compressive sampling matching pursuit algorithm and generalized orthogonal matching pursuit algorithm in greedy algorithm has completed the reconstruction of one-dimensional signal, and the comparison of the reconstruction effect. Meanwhile, using the computer simulation to compare the various signal reconstruction algorithms in the situations of different sparse degrees and different observation numbers.By Deriving and analyzing the sparse multipath channel estimated system model based on compressed sensing, and using the generalized orthogonal matching pursuit algorithm(GOMP), a multi path channel estimation method for generalized orthogonal matching pursuit algorithm based on the wireless is proposed. Through computer simulation, we compare our proposed algorithm with the traditional method of channel estimation, and analyze the mean square error of the channel reconstruction. Thus can get the advantages of the compressed sensing technology in the wireless multipath channel estimation and obtain good estimation performance.