TY - JOUR
T1 - Partial MAP-based list detection for MIMO systems
AU - Bai, Lin
AU - Choi, Jinho
PY - 2009
Y1 - 2009
N2 - The partial maximum a posteriori probability (PMAP) principle can be applied to reduce the complexity of the multiple-input-multiple-output (MIMO) detection through the successive interference cancellation (SIC). In this paper, we apply the PMAP principle to the list detection method for MIMO detection, where the SIC is performed with a list of candidates. The PMAP principle helps to choose candidate symbol vectors in the list detection. It is shown that the proposed method outperforms the conventional list detection method with a reasonable complexity.
AB - The partial maximum a posteriori probability (PMAP) principle can be applied to reduce the complexity of the multiple-input-multiple-output (MIMO) detection through the successive interference cancellation (SIC). In this paper, we apply the PMAP principle to the list detection method for MIMO detection, where the SIC is performed with a list of candidates. The PMAP principle helps to choose candidate symbol vectors in the list detection. It is shown that the proposed method outperforms the conventional list detection method with a reasonable complexity.
KW - Interference cancellation
KW - List decoding
KW - Maximum a posteriori probability (MAP) detection
KW - Maximum likelihood (ML) detection
KW - Multiple-input-multiple-output (MIMO) system
KW - Vertical Bell Laboratories layered space-time (V-BLAST)
UR - https://www.scopus.com/pages/publications/66449137547
U2 - 10.1109/TVT.2008.2005196
DO - 10.1109/TVT.2008.2005196
M3 - 文章
AN - SCOPUS:66449137547
SN - 0018-9545
VL - 58
SP - 2544
EP - 2548
JO - IEEE Transactions on Vehicular Technology
JF - IEEE Transactions on Vehicular Technology
IS - 5
ER -