Title :
Reduced complexity analysis for ML MIMO systems
Author_Institution :
Dept. of Electron. & Commun. Eng., Pondicherry Eng. Coll., Puducherry, India
Abstract :
In this paper, we propose an uncomplicated Maximum Likelihood (ML) metric along with the breadth first tree search algorithm, to reduce the number of operations required and number of nodes to be processed while decoding the transmitted symbols of MIMO (Multiple Input Multiple Output) systems. Using the similarity property of the QAM (Quadrature Amplitude Modulation) the complexity of the system is reduced without compromising the performance.
Keywords :
MIMO communication; decoding; quadrature amplitude modulation; tree searching; ML MIMO systems; QAM; breadth first tree search algorithm; decoding; quadrature amplitude modulation; reduced complexity analysis; transmitted symbols; uncomplicated maximum likelihood metric; Bit error rate; Complexity theory; Detectors; MIMO; Quadrature amplitude modulation; Vectors; Breadth first tree search algorithm; MIMO; ML; QAM;
Conference_Titel :
Emerging Trends in Computing, Communication and Nanotechnology (ICE-CCN), 2013 International Conference on
Conference_Location :
Tirunelveli
Print_ISBN :
978-1-4673-5037-2
DOI :
10.1109/ICE-CCN.2013.6528529
