Accurate Sampling Timing Acquisition for Baseband OFDM Power-line Communication in Non-Gaussian Noise

TL;DR

This paper introduces a novel, low-complexity method for accurate sampling timing acquisition in OFDM-based power-line communication systems, effectively handling non-Gaussian noise and improving performance over traditional schemes.

Contribution

The paper presents a new five-step estimation technique for sampling timing in OFDM power-line communication, addressing non-Gaussian noise and reducing computational complexity.

Findings

Significant performance improvements over conventional schemes.

Robustness against non-Gaussian, cyclo-stationary, and correlated noise.

Analytical expressions for variances and biases of estimators.

Abstract

In this paper, a novel technique is proposed to address the joint sampling timing acquisition for baseband and broadband power-line communication (BB-PLC) systems using Orthogonal-Frequency-Division-Multiplexing (OFDM), including the sampling phase offset (SPO) and the sampling clock offset (SCO). Under pairwise correlation and joint Gaussian assumption of received signals in frequency domain, an approximated form of the log-likelihood function is derived. Instead of a high complexity two-dimension grid-search on the likelihood function, a five-step method is employed for accurate estimations. Several variants are presented in the same framework with different complexities. Unlike conventional pilot-assisted schemes using the extra phase rotations within one OFDM block, the proposed technique turns to the phase rotations between adjacent OFDM blocks. Analytical expressions of the variances and biases are derived. Extensive simulation results indicate significant performance improvements over conventional schemes. Additionally, effects of several noise models including non-Gaussianity, cyclo-stationarity, and temporal correlation are analyzed and simulated. Robustness of the proposed technique against violation of the joint Gaussian assumption is also verified by simulations.