Reduced-dimension multiuser detection

Yao Xie, Yonina C. Eldar, Andrea J. Goldsmith

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

Abstract

We explore several reduced-dimension multiuser detection (RD-MUD) structures that significantly decrease the number of required correlation branches at the receiver front-end, while still achieving performance similar to that of the conventional matched-filter (MF) bank. RD-MUD exploits the fact that the number of active users is typically small relative to the total number of users in the system and relies on ideas of analog compressed sensing to reduce the number of correlators. We first develop a general framework for both linear and nonlinear RD-MUD structures. We then present theoretical performance analysis for two specific detectors: the linear reduced-dimension decorrelating (RDD) detector, which combines subspace projection and thresholding to determine active users and sign detection for data recovery, and the nonlinear reduced-dimension decision-feedback (RDDF) detector, which combines decision-feedback orthogonal matching pursuit for active user detection and sign detection for data recovery. The theoretical performance results for both detectors are validated via numerical simulations.

Original languageEnglish (US)
Title of host publication2012 IEEE International Conference on Communications, ICC 2012
Pages2265-2269
Number of pages5
DOIs
StatePublished - 2012
Externally publishedYes
Event2012 IEEE International Conference on Communications, ICC 2012 - Ottawa, ON, Canada
Duration: Jun 10 2012Jun 15 2012

Publication series

NameIEEE International Conference on Communications
ISSN (Print)1550-3607

Other

Other2012 IEEE International Conference on Communications, ICC 2012
CountryCanada
CityOttawa, ON
Period6/10/126/15/12

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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