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
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;
Conference_Titel :
Wireless Communications and Mobile Computing Conference (IWCMC), 2011 7th International
Conference_Location :
Istanbul
Print_ISBN :
978-1-4244-9539-9
DOI :
10.1109/IWCMC.2011.5982522