Sparse channel estimation algorithm based on compressed sensing in MIMO NC-OFDM system

Abstract

Multiple-input multiple-output non-contiguous orthogonal frequency division multiplexing（MIMO NC-OFDM）system is a commonly used system in cognitive radio. One of the key technical that affects the MIMO NC-OFDM performance is channel estimation in the condition of non-continuous carrier caused by licensed users’ occupation. Sparsity adaptive matching pursuit（SAMP）algorithm was proposed as a new method to estimate sparse channel in MIMO NC-OFDM system. Compared with other state-of-the-art greedy algorithms，the most innovative feature of the SAMP is that it is capable to adjust the step length adaptively to approach the original signal and reconstruct the sparse signal without prior information of the sparsity. Simulation result shows that，the new channel estimation method outperforms many existing iterative algorithms in reconstruction performance and can be implemented easily in practical application.

Keywords

• multiple-input multiple-output non-contiguous orthogonal frequency division multiplexing;cognitive radio;compressed sensing;channel estimation;sparsity adaptive matching pursuit