Paper Info
Title
ML Symbol Detection Based on the Shortest Path Algorithm for MIMO Systems
Abstract
This paper presents a new maximum likelihood (ML) symbol detection algorithm for multiple-input multiple-output (MIMO) systems. To achieve the ML performance with low complexity, we search the integer points corresponding to symbol vectors in increasing order of the distance from the unconstrained least-squares solution. For each integer point, we test if it is the ML solution, and continue the integer point search until one of searched points is determined to be the ML solution. We present an efficient iterative search strategy, which is based on the shortest path algorithm for a graph. The simulation results show that the proposed algorithm has the lower complexity compared to the sphere decoding for channel matrices having low condition numbers. For further complexity reduction, we propose to use scaling, lattice-reduction, and regularization techniques. By applying these techniques, the computational complexity of proposed algorithm is reduced significantly when the channel matrix has a high condition number.
Year
DOI
Venue
2007
10.1109/TSP.2007.896080
IEEE Transactions on Signal Processing
Keywords
Field
DocType
shortest path algorithm,low complexity,ml performance,ml symbol detection,proposed algorithm,integer point,mimo systems,complexity reduction,ml solution,symbol detection algorithm,computational complexity,lower complexity,condition number,maximum likelihood,algorithm design and analysis,cost function,detectors,shortest path problem,iterative methods,lattice reduction,channel coding
Average-case complexity,Mathematical optimization,Algorithm design,Shortest path problem,Reduction (complexity),Bidirectional search,Shortest Path Faster Algorithm,Mathematics,Dijkstra's algorithm,Computational complexity theory
Journal
Volume
Issue
ISSN
55
11
1053-587X
Citations 
PageRank 
References 
11
0.58
13
Authors
2
Name
Order
Citations
PageRank
Kyungchun Lee110615.06
Joohwan Chun239635.12