A New Approach to Peak Threshold Estimation for Impulsive Noise Reduction Over Power Line Fading Channels

ADEBISI, Bamidele, ANOH, Kelvin, RABIE, Khaled M., IKPEHAI, Augustine, FERNANDO, Michael and WELLS, Andrew (2018). A New Approach to Peak Threshold Estimation for Impulsive Noise Reduction Over Power Line Fading Channels. IEEE Systems Journal, 1-12.

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Official URL: https://ieeexplore.ieee.org/document/8327812
Link to published version:: https://doi.org/10.1109/JSYST.2018.2808230
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Abstract

Impulsive noise (IN) is a major component that degrades signal integrity in power line communication (PLC) systems. PLC systems driven by orthogonal frequency-division multiplexing (OFDM) have Rayleigh distributed amplitudes. Based on the dynamic nature of each OFDM symbol, peak amplitude of the symbol was recently shown to be a suitable threshold for detecting IN, and this technique outperforms the conventional optimal blanking (COB) scheme. In this study, we improve the dynamic peak-based threshold estimation (DPTE) scheme that relies on the OFDM Rayleigh distributed amplitudes by converting the default Rayleigh distribution to uniform distribution to unveil IN with power levels below that of the conventional peak signal. Then, we perform nonlinear mitigation processing on the received signals, whose amplitudes exceed the uniformly distributed amplitude using blanking, a scheme we will refer to as uniformly distributed DPTE (U-DPTE). Our results (based on U-DPTE) significantly outperform the DPTE scheme by up to 4-dB gain in terms of output signal-to-noise ratio (SNR). Additionally and unlike earlier DPTE studies, we propose a novel threshold criterion that compensates the Gaussian noise power-level amplification (after equalization) for achieving the optimal SNR over a log-normal multipath fading channel. The results further reveal the suboptimality of the DPTE scheme over COB.

Item Type: Article
Uncontrolled Keywords: Operations Research
Identification Number: https://doi.org/10.1109/JSYST.2018.2808230
Page Range: 1-12
SWORD Depositor: Symplectic Elements
Depositing User: Symplectic Elements
Date Deposited: 05 Feb 2019 16:13
Last Modified: 08 Apr 2019 10:48
URI: http://shura.shu.ac.uk/id/eprint/23948

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