Fast Compressed Sensing-Based Sparse Multipath Channel Estimation with Smooth L0 Algorithm

Broadband wireless channel is a time dispersive and becomes strongly frequency selective. Commonly, the channel is composed of a few dominant coefficients and a large part of coefficients is approximately zero or under noise floor. To exploit the sparsity of multi-path channel (MPC), there are various methods have been proposed. They are, namely, greedy algorithms, iterative algorithms, and convex program. The former two algorithms are easy to be implemented but not stable, on the other hand, the last method is stable but difficult to be implemented as practical channel estimation problems because of computational complexity. In this paper, we introduce a novel channel estimation strategy using smooth L0 (SL0) algorithm which combines stable and low complexity. Computer simulations confirm the effectiveness of the introduced algorithm comparisons with the existing methods. We also give various simulations to verify the sensing training signal method.