Variable is good: Adaptive sparse channel estimation using VSS-ZA-NLMS algorithm

Guan Gui, Shinya Kumagai, Abolfazl Mehbod Niya, Fumiyuki Adachi

Research output: Contribution to conferencePaper

12 Citations (Scopus)

Abstract

Broadband wireless communication often requires accurate channel state information (CSI) at the receiver side due to the fact that broadband channel is described well by sparse channel model. To exploit the channel sparsity, invariable step-size zero-attracting normalized least mean square (ISS-ZA-NLMS) algorithm was applied in adaptive sparse channel estimation (ASCE). However, ISS-ZA-NLMS cannot trade off the algorithm convergence rate, estimation performance and computational cost. In this paper, we propose a variable step-size ZA-NLMS (VSS-ZA-NLMS) algorithm to improve the adaptive sparse channel estimation in terms of bit error rate (BER) and mean square error (MSE) metrics. First, we derive the proposed algorithm and explain the difference between VSS-ZA-NLMS and ISS-ZA-NLMS algorithms. Later, to verify the effectiveness of the proposed algorithm, several selected computer simulation results are shown.

Original languageEnglish
DOIs
Publication statusPublished - 2013 Jan 1
Event2013 International Conference on Wireless Communications and Signal Processing, WCSP 2013 - Hangzhou, China
Duration: 2013 Oct 242013 Oct 26

Other

Other2013 International Conference on Wireless Communications and Signal Processing, WCSP 2013
CountryChina
CityHangzhou
Period13/10/2413/10/26

Keywords

  • Adaptive sparse channel estimation
  • invariable step size (ISS)
  • variable step size (VSS)
  • zero-attracting normalized least mean square (ZA-NLMS)

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Signal Processing

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    Gui, G., Kumagai, S., Mehbod Niya, A., & Adachi, F. (2013). Variable is good: Adaptive sparse channel estimation using VSS-ZA-NLMS algorithm. Paper presented at 2013 International Conference on Wireless Communications and Signal Processing, WCSP 2013, Hangzhou, China. https://doi.org/10.1109/WCSP.2013.6677215