An Asynchronous Triggered MAC Protocol for Underwater Acoustic Networks

Abstract

Time Division Multiple Access (TDMA)-based Medium Access Control (MAC) protocols have proven their practicality through extensive field trials in Underwater Acoustic Networks (UANs), attributable to their hardware compatibility and ease of implementation. In conventional TDMA-based MAC designs, channel access is typically organized using synchronized, fixed-length slots to mitigate contention and coordinate transmissions. However, this paradigm imposes significant clock synchronization overhead in UANs with long and variable propagation delays and struggles to improve scheduling flexibility. Although some protocols attempt to refine this slot paradigm (adjust the slot length to improve channel reuse efficiency or scheduling frequency), they are still constrained by the trade-off between channel utilization and scheduling complexity. To this end, this paper proposes AT-MAC, an Asynchronous Triggered MAC protocol that aims to achieve efficient and fair channel access through coordinated asynchronous scheduling. AT-MAC introduces a triggered slot paradigm without time synchronization, decoupling transmission scheduling from a rigid timeline and enabling asynchronous, variable-length slots to accommodate the long and diverse propagation delays. To power this slot paradigm, AT-MAC augments conventional Multi-Agent Deep Reinforcement Learning to handle asynchronous interaction, achieving coordinated channel access under partial observations. It further devises a load-aware fairness guard mechanism to enable network-wide fairness status inference solely through local overhearing, thereby guiding adaptive scheduling correction to maintain fairness. Field-reconstructed simulations and on-board inference benchmarking demonstrate the feasibility of AT-MAC. Extensive simulation results further demonstrate its consistent performance gains across the evaluated scenarios and traffic conditions.