Please use this identifier to cite or link to this item: http://localhost:8081/xmlui/handle/123456789/9873
Title: PERFORMANCE ANALYSIS OF SENSITIVE BITS MAXIMUM LIKELIHOOD DETECTOR IN AN SDMA SYSTEM
Authors: Yadam, Shree Devi
Keywords: ELECTRONICS AND COMPUTER ENGINEERING;SENSITIVE BITS MAXIMUM LIKELIHOOD DETECTOR;SDMA SYSTEM;LINEAR MINIMUM MEAN SQUARE DETECTOR
Issue Date: 2005
Abstract: A system where many users share a common channel is called muttiuser communication system. Multiuser detection is a key technique for combating multi-access interference. It deals with the estimation/demodulation of simultaneously occurring mutually interfering digital streams of information. Multiuser Detection is a better strategy as compare to single user detection because information about multiple- users is used jointly to better detect each individual user. Some of the conventional multiuser detectors are Maximum-Likelihood Detector (MLD), Linear Minimum Mean Square (LMMSE) Detector (LMMSE), ordered Successive interference cancellation (V-BLAST), Decorrelating Detector etc. Maximum-Likelihood Detector is the optimal detector. It is optimal in the sense that itgives best bit error rate performance in comparison to other detectors. But it is highly complex as it requires the exhaustive search of all possible combinations of transmitted symbol vector. In the past few years quite a lot of research has been taking place to reduce the complexity of the Maximum-Likelihood Detector. One such detector was proposed by Jungiang Li, Khaled Ben Lataief and Zhigang Cao in the year 2004. This is the "Sensitive: Bits Maximum-Likelihood Detector'". In this dissertation we have studied and simulated this Detector in an SDMA system with QPSK modulation. Also its performance has been compared to that of ML, LMMSE and V-BLAST detectors. It has been found that this detector has a complexity very much lower as compared to MLD, but with a little loss of performance. Also the algorithm chosen for initial stage has an impact on the performance of this detector.
URI: http://hdl.handle.net/123456789/9873
Other Identifiers: M.Tech
Research Supervisor/ Guide: Varma, S. K.
metadata.dc.type: M.Tech Dessertation
Appears in Collections:MASTERS' DISSERTATIONS (E & C)

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