DocumentCode
2732081
Title
Reduced complexity Sphere Decoding
Author
Li, Boyu ; Ayanoglu, Ender
Author_Institution
Dept. of Electr. Eng. & Comput. Sci., Univ. of California - Irvine, Irvine, CA, USA
fYear
2011
fDate
4-8 July 2011
Firstpage
147
Lastpage
151
Abstract
In Multiple-Input Multiple-Output (MIMO) systems, Sphere Decoding (SD) can achieve performance equivalent to full search Maximum Likelihood (ML) decoding with reduced complexity. Several researchers reported techniques that reduce the complexity of SD further. In this paper, a new technique is introduced which decreases the computational complexity of SD substantially, without sacrificing performance. The reduction is accomplished by deconstructing the decoding metric to decrease the number of computations and exploiting the structure of a lattice representation. Simulation results show that this approach achieves substantial gains for the average number of real multiplications and real additions needed to decode one transmitted vector symbol. As an example, for a 4 × 4 MIMO system, the gains in the number of multiplications are 85% with 4-QAM and 90% with 64-QAM, at low SNR.
Keywords
MIMO communication; communication complexity; maximum likelihood decoding; quadrature amplitude modulation; MIMO system; QAM; SNR; computational complexity; decoding metric; lattice representation; maximum likelihood decoding; multiple-input multiple-output system; sphere decoding; transmitted vector symbol; Complexity theory; Lattices; MIMO; Maximum likelihood decoding; Modulation; Signal to noise ratio; Low Computational Complexity; MIMO; ML Decoding; SD;
fLanguage
English
Publisher
ieee
Conference_Titel
Wireless Communications and Mobile Computing Conference (IWCMC), 2011 7th International
Conference_Location
Istanbul
Print_ISBN
978-1-4244-9539-9
Type
conf
DOI
10.1109/IWCMC.2011.5982522
Filename
5982522
Link To Document