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Publication Type : Conference Paper
Publisher : ICECT 2011 - 2011 3rd International Conference on Electronics Computer Technology
Source : ICECT 2011 - 2011 3rd International Conference on Electronics Computer Technology, Volume 3, Kanyakumari, p.258-262 (2011)
ISBN : 9781424486779
Keywords : Algorithms, Antennas, BER performance, Capacity limit, Communication channels (information theory), Computational complexity, Decoding, Decoding algorithm, Feedback control, High rate, Maximum likelihood, Maximum-likelihood detection, MIMO channel, MIMO systems, Multiple antenna systems, Multiple input multiple output transmissions, Multiple-input multiple-output channels, Multiple-input-multiple-output systems, Performance analysis, Rapid prototyping, Receiver algorithms, Spectral efficiencies, Spectrum analyzers, Sphere decoding algorithm, Sphere decoding algorithm (SD), Spheres, Wireless communications, Wireless telecommunication systems
Campus : Coimbatore
School : School of Engineering
Department : Electronics and Communication
Year : 2011
Abstract : Multiple Input Multiple Output (MIMO) transmission system is one of the recent and the most promising approach which is currently practiced for high-rate wireless communication. Here we discuss the fundamental capacity limits for transmission over multiple-input multiple-output (MIMO) channels. These capacity limits highlight the potential spectral efficiency of MIMO channels, which grows approximately linearly with the number of antennas, assuming ideal propagation. In MIMO, many receiver algorithms have been used for the detection of the transmitted symbols. Intended for a rapid prototyping of MIMO, this paper discusses some of the algorithms used and they are compared based on complexity and BER performance for a 4×4 system. Out of the discussed algorithms, Maximum Likelihood (ML) is found to be the best in terms of BER but the complexity increases exponentially with increase in number of transmitters. A new algorithm called the Sphere decoding algorithm is proposed to gradually replace ML as it reduces the computational complexity while maintaining the same performance as that of ML. The algorithms are simulated in MATLAB and their BER performances are validated. © 2011 IEEE.
Cite this Research Publication : Ia Ammu and Deepa, Rb, “Performance analysis of decoding algorithms in multiple antenna systems”, in ICECT 2011 - 2011 3rd International Conference on Electronics Computer Technology, Kanyakumari, 2011, vol. 3, pp. 258-262.