A dual channel and node mobility based cognitive approach to optimize wireless networks in coal mines

This study investigates the network capability by introducing a self-adaptive cognition approach that can sense and dynamically configure the communication channel requirements to optimize the wireless links in coal mines. The cognitive scheme based on dual-channel is initiated to sense the optimal channel of transmission and the multi-node mobility system is employed to cover the area of the network where signal strength is below the threshold level. The searching model of target nodes is presented to locate the field of intermittent link and cognitive controlled mobile nodes are utilized to restore the site of intermittent link. The visible light communication (VLC) and radio frequency (RF) channels are integrated into a cognition access point and the channel modeling of both links is performed to evaluate their performance in the hostile environment of coal mines. Multi-mode waveguide and geometrical optic (GO) models are employed in the modeling of RF signal propagation and the ray-tracing approach based on Lambertian radiation pattern (LRP) is utilized to characterize the visible light propagation. The estimation of received signal power and other evaluating parameters of communication reveals the significance of the proposed study against the challenges of intermittent links in coal mines.