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
T2 - 2008 IEEE Radio and Wireless Symposium, RWS
Y2 - 22 January 2008 through 24 January 2008
ER -