Reinforcement learning based ALOHA for multi-hop Wireless Sensor Networks with Informed Receiving

In this paper, an ALOHA based Medium Access Control (MAC) protocol (RL-ALOHA with Informed Receiving) is proposed for multi-hop Wireless Sensor Networks (WSNs), which overcomes the traditional problems of low throughput, while exploiting their advantages of simplicity, low computational complexity and overheads. Reinforcement Learning (RL) is implemented as an intelligent slot assignment strategy in order to avoid collisions with minimal additional overheads. To improve the energy efficiency, Informed Receiving (IR) and ping packets are applied to avoid idle listening and overhearing. The simulation results show that this approach significantly increases the energy efficiency, achieves over twice throughput of Slotted ALOHA and reduces the end-to-end delay.