Clonal selection detection algorithm for the V-BLAST system

Authors:
Caihong Mu;Mingming Zhu
Affiliations:
Institute of Intelligent Information Processing, Xidian University, Xi'an, China;Institute of Intelligent Information Processing, Xidian University, Xi'an, China
Venue:
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part II
Year:
2006

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Abstract

A novel detection algorithm for V-BLAST system is proposed, based on the clonal selection theory and the idea of immune evolution. The complexity of the clonal selection detection algorithm for V-BLAST system (CA-VBLAST) is analyzed and the bit error ratio (BER) performance is verified via computer simulations. Simulation results show that the BER performance of CA-VBLAST detector with proper algorithm parameters is comparable with the maximum likelihood (ML) detector which presents the best BER performance but the highest computational complexity, and our CA-VBLAST detector obtains a much more decreased complexity.