IIoT Wireless Network Design Algorithms for Smart Mines and Tunnels

Safety and high productivity of mines and tunnels can be ensured by collecting critical data. Fast emerging Industrial Internet of Things (IIoT) approach is an effective tool to perform this tedious task. The work of this thesis focuses on investigating underground IIoT communication systems and suggesting a number of algorithms for performance improvement. First we characterized wireless propagation in mines and tunnels via simulation as well as experiments. Then analytically optimized various system parameters for better performance improvement and lifetime enhancement with power saving features at the node level as well as at the network level. Then we developed a new medium access control (MAC) protocol to provide better connectivity to the IIoT system in harsh underground environments using Long Range (LoRa) wireless technology. The MAC protocols play a crucial role to collect data in a timely manner and meet the application specific QoS requirements. LoRaWAN, the incumbent MAC protocol of LoRa is a pure ALOHA protocol which is prone to collisions at high density. In contrast, the proposed MAC algorithm provides a paradigm shift in methodology to not only address the low throughput and high probability of collisions, but also maintain the low cost, and long life benefit to IIoT devices. The new MAC protocol is presented in this thesis along with empirical evidence to showcase the improvement over the existing LoRaWAN standard. The added benefit is that existing hardware can still be utilized which results in a low cost solution. Also, appropriate modifications of relevant parameters as well as the inclusion of timing corrections steps in the ACK packets provide a very unique approach in addressing the deficiencies of the LoRaWAN.