The technologies of the fourth industrial revolution have the potential to make zero harm possible for the first time in the history of mining. In the journey toward zero harm, rock stress monitoring systems are important for the risk management process. Although communication systems for underground mining have improved significantly over the past two decades, it remains difficult to achieve reliable-all-the-time wireless communication in ultra-deep level underground mines. The aim of this study is to explore and test a smart phone network for communicating sensor data from the underground production environment to the surface. In this paper, the evaluation and performance over distance of a wireless communication system is performed in underground mining environments. The wireless system transmits the data collected from a sensor installed in a narrow reef stope, horizontal tunnel, and vertical shaft area of a mock underground mine. The evaluation was performed using the received signal strength of a mobile receiver over distance. The path loss coefficients of the underground mining environment were then derived for the measurement areas. The results show that a communication speed of 80 Mbps was achieved in a 60 m range, thus, indicating the potential for the support of applications requiring higher data rates.

In this paper, 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 the probability of error obtained from the trained models closely match 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.

We introduce an efficient soft-decision decoder for permutation block codes when assuming AWGN and slow fading frequency-nonselective channels. The decoder implements a combination of the Hungarian algorithm and Murty’s algorithm for the $k$ th assignment. Results show that the proposed algorithm achieves better coding gain when compared with hard-decision decoding. A salient feature of the decoder is that it operates within practical computational complexity, especially for large codebooks.

The error distribution of multicarrier modulation in a narrowband powerline communication (PLC) channel with memory is presented for an underground mining environment. In the environment, the noise in the PLC channel originates from the mains switchboard and a blast control unit, connected to the powerline link. Using the error vectors measured from the channel, the memory channel model is obtained by training the measured data using a hidden Markov model and the Fritchman model for channel state classification. The channel with memory is modeled by considering the state transition probabilities between the current state and one previous state of the channel. The measured and modeled data are then compared in order to determine the suitability of the derived models. Using the error-free run distribution and probabilities of error of the modeled data, the modeled data match the measured data, validating the suitability of the derived models for an underground mining environment.

Channel impairments from the powerline communication (PLC) and visible light communication (VLC) technologies, are one of the causes of performance degradation in a hybrid PLC and VLC (HPV) system. In this paper, we focus on one of the inherent noise types in PLC channels, impulse noise (IN), which is characterised by short bursts of rapidly modified amplitudes caused by random switching of electrical devices onto the power network. Recently, a permutation coded orthogonal frequency division multiplexing (OFDM) with M-ary frequency shift keying (MFSK) scheme, in short, PC OFDM-MFSK, was proposed for IN mitigation in PLC systems. It is conceived that the robustness of this scheme against IN in standalone PLC systems will enhance the error performance of the HPV system. Furthermore, since one of the disadvantages of the PC OFDM-MFSK scheme compared to that using only the classical OFDM scheme, is degraded data rate, we propose a generalised PC OFDM-MFSK scheme to improve the degraded data rate. It is shown in this paper that the use of OFDM-MFSK improves the performance of an HPV system compared to that using only the classical OFDM modulation scheme, by a signal-to-noise (SNR) ratio gain of 6 dB at a bit error rate (BER) of 10-4. Furthermore, the use of the soft-decision Hungarian-Murty (HM) decoder enhances the error performance, showing an SNR gain of about 3 dB and reduces the decoding complexity of the PC OFDM-MFSK HPV system. Moreover, the generalisation of the PC OFDM-MFSK HPV system, does not increase the decoding complexity when the SD HM decoder is used.

Hybrid powerline and visible light communication (HPV) systems offer a cost-effective method of providing high-speed communication in indoor and outdoor environments, for the realisation of internet of things (IoT). However, in the HPV system the powerline communication (PLC) channel is inherently susceptible to impulse noise (IN) due to electrical appliances randomly connected to the powerline. This adversely affects the HPV system’s bit error rate (BER) performance. In this paper, a time-diversity Hermitian symmetry (TDHS) scheme, which mitigates the effects of IN in a PLC channel is proposed. The scheme employs the Hermitian symmetry structure to recover information symbols likely to have been affected by the IN. By using the TDHS scheme, the probability of the effect of IN on data symbols through a PLC channel, is drastically reduced by 75%. By simulations, the effectiveness of the TDHS scheme is demonstrated via the enhanced BER performance of the system. The TDHS scheme is then implemented over a permutation coded HPV system using the amplify-and-forward protocol at the PLC-VLC integration unit and the Hungarian-Murty (HM) soft-decision decoder at the destination. The combination of the TDHS scheme and the HM decoder in a coded system provides further BER performance enhancement, exceeding 10 dB gain in signal-to-noise ratio (SNR) at a BER of $10^{-4}$ .