Sparse Channel Estimation Using Correntropy Induced Metric Criterion Based SM-NLMS Algorithm

In this paper, a correntropy induced metric (CIM) criterion based set-membership NLMS (SM-NLMS) algorithm is proposed and its derivation is given in detail for estimating a sparse channel identification system. In the proposed algorithm, the CIM is utilized to exploit the sparsity-aware property of the sparse broadband multiple-path channels to achieve a better channel state information (CSI). Moreover, the proposed CIM criterion based SM-NLMS (CIMSM-NLMS) algorithm is carried out by mimicking a modified cost function under a restricted condition of CIM. The channel estimation performance of the proposed CIMSM-NLMS algorithm obtained by computer simulation is provided for appraising a sparse channel. The achieved simulation results reveal that the proposed CIMSM-NLMS algorithm is stable and outperforms the conventional SM-NLMS and sparse NLMS, LMS and SM-NLMS algorithms in terms of both the convergence and steady-state misalignment.

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