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Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/24

Title: Non-linear channel equalization using computationally efficient neuro-fuzzy channel equalizer
Authors: Sahu, P K
Patra, S K
Panigrahi, S P
Keywords: computational complexity
fuzzy neural nets
AWGN Channels
Issue Date: Dec-2002
Publisher: IEEE
Citation: IEEE International Conference on Personal Wireless Communications, 15-17 Dec. 2002, New Delhi, India, P 16 -19
Abstract: The paper investigates the problem of channel equalization in digital cellular radio (DCR). These channels are affected by intersymbol interference (ISI) with non-linearity in the presence of additive white Gaussian noise (AWGN). We propose a computationally efficient neuro-fuzzy system based equalizer for use in communication channels with these anomalies. This equalizer performs close to the optimum maximum a-posteriori probability (MAP) equalizer with a substantial reduction in computational complexity and can be trained with a supervised scalar clustering algorithm. These features can make the equalizer very suitable for mobile communication applications. Simulation studies indicate that this equalizer performs close to the optimal equalizer.
Description: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
URI: http://hdl.handle.net/2080/24
Appears in Collections:Conference Papers

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