An Improved Proportionate Normalized Least-Mean-Square Algorithm for Broadband Multipath Channel Estimation. (20th March 2014)

• Record Type: Journal Article
• Authors: Li, Yingsong; Hamamura, Masanori
• Other Names: Karimi H. R. Academic Editor.; Yang X. Academic Editor.; Yu Z. Academic Editor.; Zhang W. Academic Editor.
• Is Part Of: TheScientificWorldjournal. Volume 2014(2014)
• Publication Date: 2014-03-20
• Subjects: Science -- Periodicals; Technology -- Periodicals; Medicine -- Periodicals; 505
• DOI: 10.1155/2014/572969
• Languages: English
• ISSNs: 2356-6140

Abstract

Abstract : To make use of the sparsity property of broadband multipath wireless communication channels, we mathematically propose an l p -norm-constrained proportionate normalized least-mean-square (LP-PNLMS) sparse channel estimation algorithm. A general l p -norm is weighted by the gain matrix and is incorporated into the cost function of the proportionate normalized least-mean-square (PNLMS) algorithm. This integration is equivalent to adding a zero attractor to the iterations, by which the convergence speed and steady-state performance of the inactive taps are significantly improved. Our simulation results demonstrate that the proposed algorithm can effectively improve the estimation performance of the PNLMS-based algorithm for sparse channel estimation applications.