DocumentCode :
3220865
Title :
A reduced complexity clustering algorithm for the K-user MIMO interference channel
Author :
Ben Halima, Slim ; Saadani, Ahmed
Author_Institution :
Orange Labs., Issy-Les-Moulineaux, France
fYear :
2012
fDate :
17-20 June 2012
Firstpage :
284
Lastpage :
288
Abstract :
In this paper, we propose a low complexity clustering algorithm for an overloaded MIMO interference channel. The algorithm is based on distributed interference alignment techniques. Starting from a small number of iterations in the iterative interference alignment process, the algorithm chooses the group of links that maximizes the chordal distance between the useful signal vector space and the interference signal vector space. Based on Monte-Carlo simulations, we evaluate the performance of the proposed algorithm in terms of system sum-capacity and compare it with the performance of optimal clustering and with the random clustering algorithms. The complexity of the proposed algorithm in terms of number of elementary operations is also studied.
Keywords :
MIMO communication; Monte Carlo methods; iterative methods; radiofrequency interference; K-user MIMO interference channel; Monte-Carlo simulations; chordal distance; complexity clustering algorithm reduction; distributed interference alignment techniques; elementary operations; interference signal vector space; iterations; optimal clustering; random clustering algorithms; signal vector space; system sum-capacity; Algorithm design and analysis; Clustering algorithms; Complexity theory; Integrated circuits; Interference; MIMO; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing Advances in Wireless Communications (SPAWC), 2012 IEEE 13th International Workshop on
Conference_Location :
Cesme
ISSN :
1948-3244
Print_ISBN :
978-1-4673-0970-7
Type :
conf
DOI :
10.1109/SPAWC.2012.6292911
Filename :
6292911
Link To Document :
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