Structured matching pursuit for reconstruction of dynamic sparse channels

Xudong Zhu, Linglong Dai, Guan Gui, Wei Dai, Zhaoceng Wang, Fumiyuki Adachi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

In this paper, by exploiting the special features of temporal correlations of dynamic sparse channels that path delays change slowly over time but path gains evolve faster, we propose the structured matching pursuit (SMP) algorithm to realize the reconstruction of dynamic sparse channels. Specifically, the SMP algorithm divides the path delays of dynamic sparse channels into two different parts to be considered separately, i.e., the common channel taps and the dynamic channel taps. Based on this separation, the proposed SMP algorithm simultaneously detects the common channel taps of dynamic sparse channels in all time slots at first, and then tracks the dynamic channel taps in each single time slot individually. Theoretical analysis of the proposed SMP algorithm provides a guarantee that the common channel taps can be successfully detected with a high probability, and the reconstruction distortion of dynamic sparse channels is linearly upper bounded by the noise power. Simulation results demonstrate that the proposed SMP algorithm has excellent reconstruction performance with competitive computational complexity compared with conventional reconstruction algorithms.

Original languageEnglish
Title of host publication2015 IEEE Global Communications Conference, GLOBECOM 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479959525
DOIs
Publication statusPublished - 2015 Jan 1
Event58th IEEE Global Communications Conference, GLOBECOM 2015 - San Diego, United States
Duration: 2015 Dec 62015 Dec 10

Publication series

Name2015 IEEE Global Communications Conference, GLOBECOM 2015

Other

Other58th IEEE Global Communications Conference, GLOBECOM 2015
CountryUnited States
CitySan Diego
Period15/12/615/12/10

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering
  • Communication

Fingerprint Dive into the research topics of 'Structured matching pursuit for reconstruction of dynamic sparse channels'. Together they form a unique fingerprint.

  • Cite this

    Zhu, X., Dai, L., Gui, G., Dai, W., Wang, Z., & Adachi, F. (2015). Structured matching pursuit for reconstruction of dynamic sparse channels. In 2015 IEEE Global Communications Conference, GLOBECOM 2015 [7416980] (2015 IEEE Global Communications Conference, GLOBECOM 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GLOCOM.2014.7416980