A channel selection game for multi-operator LoRaWAN deployments

Abstract

With over 75 billion Internet of Things (IoT) devices expected worldwide by the year 2025, inaugural MAC layer solutions for long-range IoT deployments no longer suffice. LoRaWAN, the principal technology for comprehensive IoT deployments, enables low power and long range communications. However, synchronous transmissions on the same spreading factors and within the same frequency channel, augmented by the necessary clustering of IoT devices, will cause collisions and drops in efficiency. The performance is further impacted by the shortage of radio resources and by multiple operators utilizing the same unlicensed frequency bands. In this paper, we propose a game theoretic based channel selection algorithm for LoRaWAN in a multi-operator deployment scenario . We begin by proposing an optimal formulation for the selection process with the objective of maximizing the total normalized throughput per spreading factor, per channel. Then, we propose centralized optimal approaches, as well as distributed algorithms , based on reinforcement learning and regret matching dynamics, to finding both the Nash and Correlated equilibria of the proposed game. We simulate our proposals and compare them to the legacy approach of randomized channel access, stressing their efficiency in improving the total normalized throughput as well as the packet delivery ratios .