An Efficient Partially Overlapping Channels Assignment for Smart Grid IoT With Differentiated QoS

In smart grid (SG), internet of things (IoT) has drawn much attention around the years due to increased volume of traffic. Various types of electrical devices in SG demand a differentiated quality of service (QoS). However, the spectrum resource for SG wireless communication is quite limited. The network performance and spectrum utilization in a SG-IoT network can be greatly enhanced by adopting wireless mesh networks (WMNs) with multi-radio multi-channel (MRMC) and partially overlapping channels (POCs). In this paper, a game-based efficient POCs assignment algorithm is proposed to satisfy the diverse QoS and improve the spectrum utilization efficiency. The utility function in the proposed game model is taken both of the differentiated QoS and interference into consideration to optimize the network capacity. Then Nash Equilibrium (NE) of the game model is analyzed, and a variable learning step algorithm (VLSCA) is designed to improve its convergence speed. In the simulations, seven SG application services divided into four priority levels are considered to compare with the other two typical channel assignment algorithms. The results show that our algorithm has better performance to ensure a higher priority level traffic with lower end-to-end delays and packet loss ratios.