Memory Channel Models of a Hybrid PLC-VLC Link for a Smart Underground Mine

Abstract

In this article, discrete memory channel models of a low-cost, visible light communication (VLC) and a hybrid amplify-and-forward (AF) powerline communication (PLC) and VLC channel are derived using data obtained from an underground mining testbed. The testbed is set up close to the mining face, where blasting occurs. Then, the noise distributions as a result of the connection of a blasting equipment and the mains switchboard supply on the powerline channel are modeled. The baseband signals are communicated over software-defined radios, using multicarrier modulation in the VLC and hybrid AF PLC-VLC channels. Aided by a Fritchman 3-state semi-hidden Markov model (SHMM) for channel state classification, the channels are modeled using a first-order (FO) Markov process, which considers only one previous state in the channel. In addition, the block diagonal (BD) Markov model, which groups similar successive states of the channel, is implemented in order to reduce the training complexity. The models for the error distribution are then derived for both VLC and hybrid PLC-VLC channels. Results show that the probability of error obtained from the trained models closely matches the probability of error obtained from the channel measurements, validating the suitability of the SHMM for modeling VLC and hybrid PLC-VLC channels. In addition, the modified BD Markov model, which groups the channel states shows better performance with reduced complexity when compared with the FO Markov model.