Several experiments and field trials have shown that deterministic components characterize the Power Line Communication (PLC) noise across multiple-conductors. This article aims at understanding the main origins of these noise components and evaluate several methods to characterize them statistically. The correlation, distance-correlation, mutual information estimation, and a proposed linear coefficient ratio, are used to analyze the noise time-series statistically. The analysis of the PLC noise deterministic components allow us to develop an enhanced noise model that includes them. The presence of deterministic noise fosters the development of coding and decoding algorithms that aim at mitigating the noise effect. New decoding techniques called Quasi-Deterministic-Decoding are detailed and tested with single-input-multiple-output (SIMO) 1\times 2 and multiple-input-multiple-output (MIMO) 2\times 2 transmission configurations using real PLC noise and channel realizations. The proposed model leads to a better representation of the PLC noise traces and, consequently, the development of improved coding algorithms for reliable data transmission at low signal-to-noise ratios.
