Paper Info
Title
Variable-breadth K-best detector for MIMO systems
Abstract
Tree search detection algorithms can provide Maximum-Likelihood detection over Gaussian MIMO channels with lower complexity than the exhaustive search. Furthermore, the performance of MIMO detectors is highly influenced by the channel matrix condition number. In this paper, the impact of the 2-norm condition number in data detection is exploited in order to decrease the complexity of already proposed algorithms. A suboptimal tree search method called K-Best is combined with a channel matrix condition number estimator and a threshold selection method. This approach leads to a variable-breadth K-Best detector with predictable average performance and suitable for hardware implementation. The results show that the proposed scheme has lower complexity, i.e. it is less power consuming, than a fixed K-Best detector of similar performance.
Year
DOI
Venue
2010
10.1145/1815396.1815580
IWCMC
Keywords
Field
DocType
variable-breadth k-best detector,mimo system,similar performance,suboptimal tree search method,exhaustive search,2-norm condition number,fixed k-best detector,predictable average performance,channel matrix condition number,data detection,maximum-likelihood detection,lower complexity,condition number
Condition number,Mimo systems,Mathematical optimization,Brute-force search,Computer science,MIMO,Algorithm,Communication channel,Gaussian,Detector,Distributed computing,Estimator
Conference
Citations 
PageRank 
References 
0
0.34
11
Authors
4
Name
Order
Citations
PageRank
Sandra Roger1496.90
Alberto González222030.27
Vicenc Almenar311918.19
Antonio M. Vidal414334.64