Title :
A best-first tree-searching approach for ML decoding in MIMO system
Author :
Shen, Chung-An ; Eltawil, Ahmed M. ; Mondal, Sudip ; Salama, Khaled N.
Author_Institution :
EECS Dept., Univ. of California, Irvine, CA, USA
fDate :
May 30 2010-June 2 2010
Abstract :
In MIMO communication systems maximum-likelihood (ML) decoding can be formulated as a tree-searching problem. This paper presents a tree-searching approach that combines the features of classical depth-first and breadth-first approaches to achieve close to ML performance while minimizing the number of visited nodes. A detailed outline of the algorithm is given, including the required storage. The effects of storage size on BER performance and complexity in terms of search space are also studied. Our result demonstrates that with a proper choice of storage size the proposed method visits 40% fewer nodes than a sphere decoding algorithm at signal to noise ratio (SNR) = 20dB and by an order of magnitude at 0 dB SNR.
Keywords :
MIMO communication; error statistics; maximum likelihood decoding; tree searching; BER performance; MIMO communication; ML decoding; best first tree searching approach; maximum-likelihood decoding; sphere decoding algorithm; Bit error rate; Constellation diagram; Degradation; MIMO; Matrix decomposition; Maximum likelihood decoding; Receiving antennas; Signal to noise ratio; Throughput; Transmitting antennas;
Conference_Titel :
Circuits and Systems (ISCAS), Proceedings of 2010 IEEE International Symposium on
Conference_Location :
Paris
Print_ISBN :
978-1-4244-5308-5
Electronic_ISBN :
978-1-4244-5309-2
DOI :
10.1109/ISCAS.2010.5537825
