Algorithms for Sparse Channel Estimation

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Daei Omshi, Sajjad | 2013

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Type of Document: M.Sc. Thesis
Language: Farsi
Document No: 45713 (05)
University: Sharif University of Technology
Department: Electrical Engineering
Advisor(s): Babaei Zadeh, Masoud
Abstract:
Recently, there has been much interest in sparse channel estimation, i.e. recovering a channel which has much less non zero tabs than its length. These channels have been observed in underwater and broadband wireless channels. In the last few years methods available to estimate these channels have used sparse structure information to improve the estimates. However, these methods are vulnerable to noise and interference. In other words, these methods do not use channel posterior information obtained from the received signal and this is detrimental to the estimator performance. In order to solve these problems in this thesis, motivated by CoSAMP algorithm which is a sparse signal processing method, we proposed a new algorithm which not only exploited the channel sparsity but also used channel posterior information along with noise prior information and channel sparsity rate to improve the estimates. Computer simulations show that this algorithm is better than the existing algorithms in terms of MSE and achieves Cramèr-Rao bound of the estimation and also improves the estimation performance with comparable computational complexity when compared to other algorithms
Keywords:
Sparse Channel Estimation ; Sparse Signal Processing ; Cramer-Rao Bound

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