Sparse Adaptive Channel Estimation Based on l p -Norm-Penalized Affine Projection Algorithm

Abstract EN

We propose an l p -norm-penalized affine projection algorithm (LP-APA) for broadband multipath adaptive channel estimations.

The proposed LP-APA is realized by incorporating an l p -norm into the cost function of the conventional affine projection algorithm (APA) to exploit the sparsity property of the broadband wireless multipath channel, by which the convergence speed and steady-state performance of the APA are significantly improved.

The implementation of the LP-APA is equivalent to adding a zero attractor to its iterations.

The simulation results, which are obtained from a sparse channel estimation, demonstrate that the proposed LP-APA can efficiently improve channel estimation performance in terms of both the convergence speed and steady-state performance when the channel is exactly sparse.