On the Achievable Rate of MIMO Narrowband PLC with Spatio-Temporal Correlated Noise

TL;DR

This paper investigates the theoretical capacity of MIMO NB-PLC systems considering complex cyclostationary noise, proposing a noise whitening approach to optimize data transmission and improve receiver design.

Contribution

It introduces a novel noise classification and whitening method for MIMO NB-PLC, deriving capacity bounds and evaluating achievable rates with real and simulated noise data.

Findings

Derived theoretical capacity for MIMO NB-PLC with correlated noise

Demonstrated effective noise whitening improves achievable rates

Validated approach with measured and simulated noise samples

Abstract

Narrowband power line communication (NB-PLC) systems are an attractive solution for supporting current and future smart grids. A technology proposed to enhance data rate in NB-PLC is multiple-input multiple-output (MIMO) transmission over multiple power line phases. To achieve reliable communication over MIMO NB-PLC, a key challenge is to take into account and mitigate the effects of temporally and spatially correlated cyclostationary noise. Noise samples in a cycle can be divided into three classes with different distributions, i.e. Gaussian, moderate impulsive, and strong impulsive. However, in this paper we first show that the impulsive classes in their turn can be divided into sub-classes with normal distributions and, after deriving the theoretical capacity, two noise sample sets with such characteristics are used to evaluate achievable information rates: one sample set is the measured noise in laboratory and the other is produced through MIMO frequency-shift (FRESH) filtering. The achievable information rates are attained by means of a spatio-temporal whitening of the portions of the cyclostationary correlated noise samples that belong to the Gaussian sub-classes. The proposed approach can be useful to design the optimal receiver in terms of bit allocation using waterfilling algorithm and to adapt modulation order.