Abstract
For a multiple-input multiple output (MIMO) communication system, the optimal detection is by the maximum-likelihood (ML) approach, which, however, has complexity that increases exponentially with the number of transmit antennas. In this paper, we propose a novel algorithm that implements the MIMO ML detection with reduced complexity. Our algorithm is developed based on a branch-and-bound (BB) principle. We apply a new type of cost function and give an efficient calculation algorithm. The initial reference data vector could be obtained by efficient MMSE-based algorithms. We also observe the impacts of initial reference data vectors.
| Original language | English |
|---|---|
| Title of host publication | 2008 IEEE Radio and Wireless Symposium, RWS |
| Pages | 627-630 |
| Number of pages | 4 |
| DOIs | |
| Publication status | Published - 2008 Sep 9 |
| Event | 2008 IEEE Radio and Wireless Symposium, RWS - Orlando, FL, United States Duration: 2008 Jan 22 → 2008 Jan 24 |
Publication series
| Name | 2008 IEEE Radio and Wireless Symposium, RWS |
|---|
Other
| Other | 2008 IEEE Radio and Wireless Symposium, RWS |
|---|---|
| Country | United States |
| City | Orlando, FL |
| Period | 08-01-22 → 08-01-24 |
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All Science Journal Classification (ASJC) codes
- Computer Networks and Communications
- Electrical and Electronic Engineering
- Communication
Cite this
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A novel branch-and-bound based maximum-likelihood MIMO detection algorithm. / Chang, Ming-Xian.
2008 IEEE Radio and Wireless Symposium, RWS. 2008. p. 627-630 4463570 (2008 IEEE Radio and Wireless Symposium, RWS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - A novel branch-and-bound based maximum-likelihood MIMO detection algorithm
AU - Chang, Ming-Xian
PY - 2008/9/9
Y1 - 2008/9/9
N2 - For a multiple-input multiple output (MIMO) communication system, the optimal detection is by the maximum-likelihood (ML) approach, which, however, has complexity that increases exponentially with the number of transmit antennas. In this paper, we propose a novel algorithm that implements the MIMO ML detection with reduced complexity. Our algorithm is developed based on a branch-and-bound (BB) principle. We apply a new type of cost function and give an efficient calculation algorithm. The initial reference data vector could be obtained by efficient MMSE-based algorithms. We also observe the impacts of initial reference data vectors.
AB - For a multiple-input multiple output (MIMO) communication system, the optimal detection is by the maximum-likelihood (ML) approach, which, however, has complexity that increases exponentially with the number of transmit antennas. In this paper, we propose a novel algorithm that implements the MIMO ML detection with reduced complexity. Our algorithm is developed based on a branch-and-bound (BB) principle. We apply a new type of cost function and give an efficient calculation algorithm. The initial reference data vector could be obtained by efficient MMSE-based algorithms. We also observe the impacts of initial reference data vectors.
UR - http://www.scopus.com/inward/record.url?scp=50949131265&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=50949131265&partnerID=8YFLogxK
U2 - 10.1109/RWS.2008.4463570
DO - 10.1109/RWS.2008.4463570
M3 - Conference contribution
AN - SCOPUS:50949131265
SN - 1424414636
SN - 9781424414635
T3 - 2008 IEEE Radio and Wireless Symposium, RWS
SP - 627
EP - 630
BT - 2008 IEEE Radio and Wireless Symposium, RWS
ER -