An Improved Proportionate Normalized Least-Mean-Square Algorithm for Broadband Multipath Channel Estimation

• Published in: The Scientific World Journal Vol. 2014; no. 2014; pp. 1 - 9
• Main Authors: Li, Yingsong, Hamamura, Masanori
• Format: Journal Article
• Language: English
• Published: Cairo, Egypt Hindawi Publishing Corporation 01.01.2014; Hindawi Limited; John Wiley & Sons, Inc; Wiley
• Subjects: Algorithms; Broadband transmission; Heuristic; Lagrange multiplier; Least squares; Medicine; Mobile communication systems; Models, Theoretical; Q; R; Research Article; Science; Sparsity; T; Technology; Wireless communication systems; Wireless Technology
• ISSN: 2356-6140; 1537-744X; 1537-744X
• DOI: 10.1155/2014/572969

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.