Low-complexity multiuser detection and reduced-rank wiener filters for ultra-wideband multiple access

Zhi Tian, Hongya Ge, Louis L. Scharf

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

17 Scopus citations

Abstract

Realizing the large user capacity planned for ultra-wideband (UWB) systems motivates multiuser detection (MUD). However, it is impractical to implement conventional chip-rate MUD methods, because UWB signaling gives rise to high detection complexity and difficulty in capturing energy scattered by dense multipath. In this paper, we develop a reception model for UWB multiple access based on frame-rate sampled signals in lieu of chip-rate samples. This model enables low-complexity MUD, of which we examine a reduced-rank Wiener filter for blind symbol detection. We show that frame-rate UWB samples have a small number of distinct eigenvalues in the data covariance matrix, resulting in warp convergence of reduced-rank filtering. The proposed MUD method exhibits good performance at low complexity, even in the presence of strong frequency-selective multipath fading.

Original languageEnglish (US)
Title of host publication2005 IEEE International Conference on Acoustics, Speech, and Signal Processing,ICASSP '05 - Proceedings - Audio and ElectroacousticsSignal Processing for Communication
PublisherInstitute of Electrical and Electronics Engineers Inc.
PagesIII621-III624
ISBN (Print)0780388747, 9780780388741
DOIs
StatePublished - 2005
Event2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05 - Philadelphia, PA, United States
Duration: Mar 18 2005Mar 23 2005

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
VolumeIII
ISSN (Print)1520-6149

Other

Other2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05
Country/TerritoryUnited States
CityPhiladelphia, PA
Period3/18/053/23/05

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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