A Two-Way Relay Channel Estimation Method Based on Sparsity Adaptive Matching Pursuit Algorithm

Abstract:

To solve the problem that many existing two-way relay channel (TWRC) estimation methods require the sparse degree of the channel as prior information, we introduced a novel iterative greedy reconstruction algorithm based on compressed sensing (CS), called the sparisty adaptive matching pursuit (SAMP) to reconstruct the channel impulse response under orthogonal frequency division multiplexing (OFDM) system. The most innovative feature of SAMP is its capability of channel reconstruction without prior information of the sparse degree. Under the same condition we compared the algorithm with the other channel estimation methods including conventional least square (LS) algorithm, minimum mean square error (MMSE) algorithm and a orthogonal matching pursuit (OMP) algorithm based on CS. Simulation results show that the proposed algorithm has a better estimation performance and the algorithm improves the utilization of communication resources such as spectrum and energy. Thus it is suitable for real application.

• Periodical: Applied Mechanics and Materials (Volumes 263-266)
• Pages: 1037-1042
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.263-266.1037
• Online since: December 2012
• Authors: Ju Rong Wang, Jin He Zhou
• Keywords: Channel Estimation, Compressive Sensing (CS), Sparsity Adaptive Matching Pursuit (SAMP), Training Sequence, Two-Way Relay Channel (TWRC)

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