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An information theoretic study of reduced-complexity receivers for intersymbol interference channels

Author(s)
Abou Faycal, Ibrahim C. (Ibrahim Chafik)
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Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Advisor
Amos Lapidoth.
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M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582
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Abstract
The complexity of the optimal receiver for communications over a discrete-time additive Gaussian intersymbol interference channel typically grows exponentially with the duration of the channel impulse response. Consequently, practical sub-optimal receivers are often designed as though the channel impulse response were shorter than it is. While previous studies on the performance of such receivers have mainly focused on bit error rates in uncoded systems, this thesis takes a different approach to the problem. We adopt an information theoretic approach and study the rates that are achievable in the Shannon sense over the true channel with the given, possibly sub-optimal, decoding rule. One can establish that, under such mismatch conditions, the achievable rates are bounded in the Signal-to-Noise Ratio necessitating the use of a linear equalizer at the front end of the decoder. We derive the achievable rates for these schemes and optimize under complexity constraints the design of the equalizer and the receiver. Overall, two ensemble of codes are considered: the Independent Identically Distributed Gaussian ensemble and the "spherical" ensemble, where codewords are uniformly distributed over a sphere.
Description
Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2001.
 
Includes bibliographical references (leaves 105-108).
 
Date issued
2001
URI
http://hdl.handle.net/1721.1/8922
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Publisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.

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