科研之友
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摘要
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.
