Statistical modeling of the average channel gain and delay spread in in-home PLC channels

This work describes a complete statistical modeling of the average channel gain in dB (ACG_dB) and the root mean squared delay spread (RMS-DS) for power line communication (PLC) systems. The PLC channel features are estimated from 148,037 channel frequency responses measured in 7 typical different places in an urban area in Brazil. Two frequency bands are considered: from 1.7 up to 30 MHz and from 1.7 up to 100 MHz. The resulting datasets for ACG_dB and RMS-DS were fitted to well known continuous distributions, including symmetric (Logistic and Normal) and asymmetric (Exponential, Gamma, Inverse Gaussian, Loglogistic, Lognormal, Nakagami, Rayleigh, Rician, Skew-normal, t-Student and Weibull) cases. The best distribution fitted to the considered dataset is indicated by the log-likelihood value and three distinct information criteria. The achieved results revealed that the ACG_dB is better modeled by the Skew-normal and the Nakagami distributions for the frequency bands from 1.7 up to 30 MHz and 100 MHz, respectively, whereas the RMS-DS is little bit better modeled by the Gamma distribution, then by the Lognormal distribution, in both frequency bands considered.