A Novel Neural Detector Based on Self-Organizing Map for Frequency-Selective Rayleigh Fading Channel

Xiaoqiu WANG; Hua LIN; Jianming LU; Takashi YAHAGI

A Novel Neural Detector Based on Self-Organizing Map for Frequency-Selective Rayleigh Fading Channel

Xiaoqiu WANG, Hua LIN, Jianming LU, Takashi YAHAGI

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In a high-rate indoor wireless personal communication system, the delay spread due to multi-path propagation results in intersymbol interference which can significantly increase the transmission bit error rate (BER). The technique most commonly used for combating the intersymbol interference and frequency-selective fading found in communications channels is the adaptive equalization. In this paper, we propose a novel neural detector based on self-organizing map (SOM) to improve the system performance of the receiver. In the proposed scheme, the SOM is used as an adaptive detector of equalizer, which updates the decision levels to follow the received faded signal. To adapt the proposed scheme to the time-varying channel, we use the Euclidean distance, which will be updated automatically according to the received faded signal, as an adaptive radius to define the neighborhood of the winning neuron of the SOM algorithm. Simulations on a 16 QAM system show that the receiver using the proposed neural detector has a significantly better BER performance than the traditional receiver.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E87-A No.8 pp.2084-2091

Publication Date: 2004/08/01

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Type of Manuscript: PAPER

Category: Digital Signal Processing

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Xiaoqiu WANG, Hua LIN, Jianming LU, Takashi YAHAGI, "A Novel Neural Detector Based on Self-Organizing Map for Frequency-Selective Rayleigh Fading Channel" in IEICE TRANSACTIONS on Fundamentals, vol. E87-A, no. 8, pp. 2084-2091, August 2004, doi: .
Abstract: In a high-rate indoor wireless personal communication system, the delay spread due to multi-path propagation results in intersymbol interference which can significantly increase the transmission bit error rate (BER). The technique most commonly used for combating the intersymbol interference and frequency-selective fading found in communications channels is the adaptive equalization. In this paper, we propose a novel neural detector based on self-organizing map (SOM) to improve the system performance of the receiver. In the proposed scheme, the SOM is used as an adaptive detector of equalizer, which updates the decision levels to follow the received faded signal. To adapt the proposed scheme to the time-varying channel, we use the Euclidean distance, which will be updated automatically according to the received faded signal, as an adaptive radius to define the neighborhood of the winning neuron of the SOM algorithm. Simulations on a 16 QAM system show that the receiver using the proposed neural detector has a significantly better BER performance than the traditional receiver.
URL: https://globals.ieice.org/en_transactions/fundamentals/10.1587/e87-a_8_2084/_p

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@ARTICLE{e87-a_8_2084,
author={Xiaoqiu WANG, Hua LIN, Jianming LU, Takashi YAHAGI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Novel Neural Detector Based on Self-Organizing Map for Frequency-Selective Rayleigh Fading Channel},
year={2004},
volume={E87-A},
number={8},
pages={2084-2091},
abstract={In a high-rate indoor wireless personal communication system, the delay spread due to multi-path propagation results in intersymbol interference which can significantly increase the transmission bit error rate (BER). The technique most commonly used for combating the intersymbol interference and frequency-selective fading found in communications channels is the adaptive equalization. In this paper, we propose a novel neural detector based on self-organizing map (SOM) to improve the system performance of the receiver. In the proposed scheme, the SOM is used as an adaptive detector of equalizer, which updates the decision levels to follow the received faded signal. To adapt the proposed scheme to the time-varying channel, we use the Euclidean distance, which will be updated automatically according to the received faded signal, as an adaptive radius to define the neighborhood of the winning neuron of the SOM algorithm. Simulations on a 16 QAM system show that the receiver using the proposed neural detector has a significantly better BER performance than the traditional receiver.},
keywords={},
doi={},
ISSN={},
month={August},}

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TY - JOUR
TI - A Novel Neural Detector Based on Self-Organizing Map for Frequency-Selective Rayleigh Fading Channel
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2084
EP - 2091
AU - Xiaoqiu WANG
AU - Hua LIN
AU - Jianming LU
AU - Takashi YAHAGI
PY - 2004
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E87-A
IS - 8
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - August 2004
AB - In a high-rate indoor wireless personal communication system, the delay spread due to multi-path propagation results in intersymbol interference which can significantly increase the transmission bit error rate (BER). The technique most commonly used for combating the intersymbol interference and frequency-selective fading found in communications channels is the adaptive equalization. In this paper, we propose a novel neural detector based on self-organizing map (SOM) to improve the system performance of the receiver. In the proposed scheme, the SOM is used as an adaptive detector of equalizer, which updates the decision levels to follow the received faded signal. To adapt the proposed scheme to the time-varying channel, we use the Euclidean distance, which will be updated automatically according to the received faded signal, as an adaptive radius to define the neighborhood of the winning neuron of the SOM algorithm. Simulations on a 16 QAM system show that the receiver using the proposed neural detector has a significantly better BER performance than the traditional receiver.
ER -