DocumentCode :
2045769
Title :
Memory-constrained ML-optimal tree search detection
Author :
Dai, Yongmei ; Yan, Zhiyuan
Author_Institution :
Dept. of Electr. & Comput. Eng., Lehigh Univ., Lehigh, PA
fYear :
2008
fDate :
19-21 March 2008
Firstpage :
1037
Lastpage :
1041
Abstract :
In this paper, we propose a memory-constrained tree search (MCTS) algorithm for the detection in multiple-input multiple-output (MIMO) systems. The MCTS algorithm offers a wide range of trade-offs between computational complexity and memory requirement, and is guaranteed to achieve the exact maximum-likelihood performance. By tuning the memory size, the MCTS algorithm ranges from being memory-efficient to being computation-efficient with abundant choices in between.We show that the MCTS algorithm visits slightly fewer nodes and requires slightly less memory than the sphere decoding (SD) algorithm in the memory-efficient case, and visits similar number of nodes and requires significantly less memory than the stack algorithm in the computation-efficient case.
Keywords :
MIMO systems; computational complexity; tree searching; computational complexity; maximum-likelihood performance; memory requirement; memory-constrained tree search algorithm; multiple-input multiple-output system; sphere decoding algorithm; stack algorithm; tree search detection; Computational complexity; Detection algorithms; Diversity methods; Electronic mail; Hardware; MIMO; Maximum likelihood decoding; Maximum likelihood detection; Receiving antennas; Wireless communication; MIMO; ML; Sphere Decoding; ZF-IC; stack;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Sciences and Systems, 2008. CISS 2008. 42nd Annual Conference on
Conference_Location :
Princeton, NJ
Print_ISBN :
978-1-4244-2246-3
Electronic_ISBN :
978-1-4244-2247-0
Type :
conf
DOI :
10.1109/CISS.2008.4558671
Filename :
4558671
Link To Document :
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