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 language | English |
|---|---|
| Title of host publication | IEEE Wireless Communications and Networking Conference, WCNC |
| Pages | 153-158 |
| Number of pages | 6 |
| Publication status | Published - 2008 |
| Externally published | Yes |
| Event | IEEE Wireless Communications and Networking Conference, WCNC 2008 - Las Vegas, NV Duration: 2008 Mar 31 → 2008 Apr 3 |
Other
| Other | IEEE Wireless Communications and Networking Conference, WCNC 2008 |
|---|---|
| City | Las Vegas, NV |
| Period | 08/3/31 → 08/4/3 |
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Keywords
- Layer ordering
- Maximum likelihood detection
- MIMO system
- Spatial multiplexing
- Tree search
ASJC Scopus subject areas
- Engineering(all)
Cite this
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 proceeding › Conference contribution
}
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
AN - SCOPUS:51649131160
SN - 9781424419968
SP - 153
EP - 158
BT - IEEE Wireless Communications and Networking Conference, WCNC
ER -