A MACA-Based Energy-Efficient MAC Protocol Using Q-Learning Technique for Underwater Acoustic Sensor Network

One of the major challenge in underwater acoustic wireless sensor networks (UWASNs) is designing the energy efficient medium access control (MAC) protocol. Because in UWASNs, all nodes are battery-operated and replacing these batteries every time is a crucial problem in UWASNs. Various challenges such as, high error rate, long propagation latency and low bandwidth also affect the designing of MAC protocols in UWASNs. In this research, a MACA-based energy-efficient MAC protocol using the Q-learning technique is proposed for UWASNs. Our opted protocol decreases collisions while retaining better energy efficiency. The ability of the sensor Rx nodes to avoid collisions in the absence of any previous interference knowledge, which eliminates the requirement for further indicating, is a crucial component of the suggested technique. Compared to other MAC protocols, simulation results demonstrate that our opted MAC protocol performs significantly better in terms of throughput, end-to-end delay, and energy consumption.