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Performance of Analog Nonlinear Filtering for Impulsive Noise Mitigation in OFDM-based PLC Systems

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posted on 2018-05-25, 09:11 authored by Reza Barazideh, Balasubramaniam Natarajan, Alexei V. Nikitin, Ruslan L. Davidchack
Asynchronous and cyclostationary impulsive noise can severely impact the bit-error-rate (BER) of OFDM-based powerline communication systems. In this paper, we analyze an adaptive nonlinear analog front end filter that mitigates various types of impulsive noise without detrimental effects such as self-interference and out-of-band power leakage caused by other nonlinear approaches like clipping and blanking. Our proposed Adaptive Nonlinear Differential Limiter (ANDL) is constructed from a linear analog filter by applying a feedback-based nonlinearity, controlled by a single resolution parameter. We present a simple practical method to find the value of this resolution parameter that ensures the mitigation of impulsive without impacting the desired OFDM signal. Unlike many prior approaches for impulsive noise mitigation that assume a statistical noise model, ANDL is blind to the exact nature of the noise distribution, and is designed to be fully compatible with existing linear front end filters. We demonstrate the potency of ANDL by simulating the OFDM-based narrowband PLC compliant with the IEEE standards. We show that the proposed ANDL outperforms other approaches in reducing the BER in impulsive noise environments.

History

Citation

2017 IEEE 9th Latin-American Conference on Communications (LATINCOM), 2017

Author affiliation

/Organisation/COLLEGE OF SCIENCE AND ENGINEERING/Department of Mathematics

Source

2017 IEEE 9th Latin-American Conference on Communications (LATINCOM), Guatemala City, Guatemala

Version

  • AM (Accepted Manuscript)

Published in

2017 IEEE 9th Latin-American Conference on Communications (LATINCOM)

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

isbn

978-1-5386-2097-7;978-1-5386-2098-4

Copyright date

2017

Available date

2018-05-25

Publisher version

https://ieeexplore.ieee.org/document/8240158/

Language

en

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