Title
Maximum-likelihood MIMO detection using adaptive hybrid tree search
Abstract
A hybrid tree search algorithm is described for maximum-likelihood symbol detection in spatial multiplexing (SM) systems. Essentially, the search tree is iteratively expanded in the breadth-first (BF) manner until the probability that the current most likely path is correct exceeds a specified threshold, at which point the depth-first (DF) stage is initiated to traverse the rest of the tree. In contrast to the sphere decoding (SD) algorithm, the proposed algorithm uses the BF stage to enhance the accuracy of the initial DF search direction, by exploiting the diversity inherent in the SM scheme. Simulation results demonstrate that the proposed algorithm achieves a significantly lower complexity than the SD algorithm in many scenarios of practical interest.
Year
DOI
Venue
2011
10.1109/PIMRC.2011.6139754
PIMRC
Keywords
Field
DocType
spatial multiplexing system,sd algorithm,sm scheme,tree searching,communication complexity,space division multiplexing,maximum likelihood detection,adaptive hybrid tree search,mimo communication,sphere decoding algorithm,bf stage,breadth-first manner,df search,maximum-likelihood mimo detection,decoding,maximum-likelihood symbol detection,depth-first stage,maximum likelihood,search algorithm,spatial multiplexing,modulation,signal to noise ratio
Mathematical optimization,Tree traversal,Computer science,Signal-to-noise ratio,MIMO,Algorithm,Real-time computing,Communication complexity,Decoding methods,Spatial multiplexing,Search tree,Traverse
Conference
ISSN
ISBN
Citations 
pending E-ISBN : 978-1-4577-1347-7
978-1-4577-1347-7
1
PageRank 
References 
Authors
0.37
8
3
Name
Order
Citations
PageRank
Kuei-Chiang Lai1739.29
Jiun-Jie Jia2182.98
Liwei Lin312228.76