A modified compressed sampling matching pursuit algorithm on redundant dictionary and its application to sparse channel estimation on OFDM

This paper proposes a modified compressed sensing algorithm for sparse multipath channel estimation in wideband OFDM systems. By using a virtual channel representation, the sparse nature of a multipath channel is revealed and exploited. Unlike other proposed sparse channel estimation schemes, it is noted that a truly sparse assumption on the channel impulse response (CIR) must factor in the leakage of energy of each multipath component resulting from bandpass filtering and the resulting limited bandwidth. We propose to represent the CIR as a strongly correlated redundant frame so that the representation is truly sparse. However, the introduction of correlated frames complicates the canonical compressed sensing problem. A model-based modification to CoSaMP [1] algorithm is thus proposed for recovering the CIR. Simulation results are presented indicating a significant improvement over straightforward application of canonical compressed sensing techniques.