Approximate maximum likelihood detectors for MIMO spatial multiplexing systems

Wenjie Jiang, Shuji Kubota, Yusuke Asai

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

1 Citation (Scopus)

Abstract

In multiple antenna systems using spatial multiplexing to raise data rates, it is preferable to use maximum likelihood (ML) detection to fully benefit from multiplexing and diversity gain. In this paper, we present two tree based near ML detectors that use new ordering criteria in conjunction with an efficient tree search strategy. Compared with conventional tree detectors, the error performance of the new detectors closely approximates that of the exact ML detector while achieving a dramatic reduction in complexity. Moreover, the new schemes ensure a fixed detection delay and parallelization in tree search.

Original languageEnglish
Title of host publicationIEEE Wireless Communications and Networking Conference, WCNC
Pages153-158
Number of pages6
Publication statusPublished - 2008
Externally publishedYes
EventIEEE Wireless Communications and Networking Conference, WCNC 2008 - Las Vegas, NV
Duration: 2008 Mar 312008 Apr 3

Other

OtherIEEE Wireless Communications and Networking Conference, WCNC 2008
CityLas Vegas, NV
Period08/3/3108/4/3

Fingerprint

Multiplexing
MIMO systems
Maximum likelihood
Detectors
Antennas

Keywords

  • Layer ordering
  • Maximum likelihood detection
  • MIMO system
  • Spatial multiplexing
  • Tree search

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Jiang, W., Kubota, S., & Asai, Y. (2008). Approximate maximum likelihood detectors for MIMO spatial multiplexing systems. In IEEE Wireless Communications and Networking Conference, WCNC (pp. 153-158). [4489063]

Approximate maximum likelihood detectors for MIMO spatial multiplexing systems. / Jiang, Wenjie; Kubota, Shuji; Asai, Yusuke.

IEEE Wireless Communications and Networking Conference, WCNC. 2008. p. 153-158 4489063.

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

Jiang, W, Kubota, S & Asai, Y 2008, Approximate maximum likelihood detectors for MIMO spatial multiplexing systems. in IEEE Wireless Communications and Networking Conference, WCNC., 4489063, pp. 153-158, IEEE Wireless Communications and Networking Conference, WCNC 2008, Las Vegas, NV, 08/3/31.
Jiang W, Kubota S, Asai Y. Approximate maximum likelihood detectors for MIMO spatial multiplexing systems. In IEEE Wireless Communications and Networking Conference, WCNC. 2008. p. 153-158. 4489063
Jiang, Wenjie ; Kubota, Shuji ; Asai, Yusuke. / Approximate maximum likelihood detectors for MIMO spatial multiplexing systems. IEEE Wireless Communications and Networking Conference, WCNC. 2008. pp. 153-158
@inproceedings{8cb6146f1f774fdc9d6336923c231226,
title = "Approximate maximum likelihood detectors for MIMO spatial multiplexing systems",
abstract = "In multiple antenna systems using spatial multiplexing to raise data rates, it is preferable to use maximum likelihood (ML) detection to fully benefit from multiplexing and diversity gain. In this paper, we present two tree based near ML detectors that use new ordering criteria in conjunction with an efficient tree search strategy. Compared with conventional tree detectors, the error performance of the new detectors closely approximates that of the exact ML detector while achieving a dramatic reduction in complexity. Moreover, the new schemes ensure a fixed detection delay and parallelization in tree search.",
keywords = "Layer ordering, Maximum likelihood detection, MIMO system, Spatial multiplexing, Tree search",
author = "Wenjie Jiang and Shuji Kubota and Yusuke Asai",
year = "2008",
language = "English",
isbn = "9781424419968",
pages = "153--158",
booktitle = "IEEE Wireless Communications and Networking Conference, WCNC",

}

TY - GEN

T1 - Approximate maximum likelihood detectors for MIMO spatial multiplexing systems

AU - Jiang, Wenjie

AU - Kubota, Shuji

AU - Asai, Yusuke

PY - 2008

Y1 - 2008

N2 - In multiple antenna systems using spatial multiplexing to raise data rates, it is preferable to use maximum likelihood (ML) detection to fully benefit from multiplexing and diversity gain. In this paper, we present two tree based near ML detectors that use new ordering criteria in conjunction with an efficient tree search strategy. Compared with conventional tree detectors, the error performance of the new detectors closely approximates that of the exact ML detector while achieving a dramatic reduction in complexity. Moreover, the new schemes ensure a fixed detection delay and parallelization in tree search.

AB - In multiple antenna systems using spatial multiplexing to raise data rates, it is preferable to use maximum likelihood (ML) detection to fully benefit from multiplexing and diversity gain. In this paper, we present two tree based near ML detectors that use new ordering criteria in conjunction with an efficient tree search strategy. Compared with conventional tree detectors, the error performance of the new detectors closely approximates that of the exact ML detector while achieving a dramatic reduction in complexity. Moreover, the new schemes ensure a fixed detection delay and parallelization in tree search.

KW - Layer ordering

KW - Maximum likelihood detection

KW - MIMO system

KW - Spatial multiplexing

KW - Tree search

UR - http://www.scopus.com/inward/record.url?scp=51649131160&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=51649131160&partnerID=8YFLogxK

M3 - Conference contribution

SN - 9781424419968

SP - 153

EP - 158

BT - IEEE Wireless Communications and Networking Conference, WCNC

ER -