Title :
A reduced-complexity sphere decoding algorithm for MIMO systems
Author :
Ni, Ying-Jun ; Li, Ming-Qi ; Guo, Wen-Qiang
Author_Institution :
Sch. of Math. Sci., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
Abstract :
Sphere decoding (SD), as an algorithm searching for the closest lattice point within a certain search radius, is a corrected maximum likelihood (ML) algorithm for multiple- input multiple-output (MIMO) systems, with low complexity. The sphere radius and the number of search floating points visited throughout the tree traversal searching are the decisive factors for the complexity of the algorithm. In this paper, a new reduce-complexity detection algorithm based on the complex SD for MIMO systems is presented. The algorithm performs a fixed number of total search floating points to detect the p-QAM modulation symbols independently on the noise level. Simulation results show that with 4×4 system via 4-QAM and 16-QAM, the new SD algorithm has a lower complexity than the conventional SD at low signal-noise ratio (SNR) especially.
Keywords :
MIMO communication; computational complexity; maximum likelihood decoding; quadrature amplitude modulation; tree searching; 16-QAM; 4-QAM; MIMO systems; SNR; computational complexity; corrected maximum likelihood algorithm; multiple- input multiple-output systems; noise level; p-QAM modulation symbol detection; reduce-complexity detection algorithm; reduced-complexity sphere decoding algorithm; search floating points; signal-noise ratio; tree traversal searching; Complexity theory; Lattices; MIMO; Maximum likelihood decoding; Noise level; Signal processing algorithms; MIMO systems; ML decoding; computational complexity; p-QAM modulation; sphere decoding;
Conference_Titel :
Apperceiving Computing and Intelligence Analysis (ICACIA), 2010 International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-8025-8
DOI :
10.1109/ICACIA.2010.5709935
