## 2 Related Work
It integrates time synchronization with adaptive power control to reduce interference and energy consumption. By adjusting transmission power based on node proximity, CA-MAC ensures precise, energy-efficient communication while extending the network's lifespan. In [38], the AVCW-MAC protocol introduced a dynamic contention window based on individual node propagation delay. This adaptive backoff method, shaped by delay metrics and tuning factors K1 and K2, improves fairness in accessing the channel and maintains communication stability, even in large-scale deployments. TDTSPC-MAC [13] approaches energy-efficient communication through a hybrid mechanism combining clustering, time sync, power control, and layered sleep scheduling in a 3D UASN context. Spatial partitioning is guided by a distributed clustering algorithm to reduce contention and optimize resource use. Similarly, DC-MAC [32] employs game theory to design a delay-aware, collision-avoidant MAC protocol. Nodes operate based on a non-cooperative game model that adjusts transmission probability according to network size and CH density, with CH degree used as a metric for optimizing communication scheduling through informed handshakes. A reinforcement learning-based TRC-aware MAC protocol was introduced in [39] for decentralized, energy-conscious, multi-hop UWSNs. It features a contention-based relay strategy that is guided by environmental feedback and an RL agent to adaptively manage relay node selection. It utilizes ALOHA-inspired access and intermediate helper nodes to streamline long-range underwater transmissions while balancing energy consumption. Additionally, EE-UWSNs propose a joint MAC-routing scheme that manages power through transmission scoping, node inactivation, and multi-hop routing, optimizing communication over finite underwater environments. RAP-MAC [34] presents a robust and adaptive MAC framework suited for UA-SN scenarios, particularly in string-topology acoustic networks. It incorporates concurrent scheduling and real-time reconfiguration to adapt to changing network demands. Field tests in the South China Sea have demonstrated exceptional reliability and reach--achieving 601.6 bps at a distance of 87 km, outperforming conventional benchmarks by a substantial margin. Another promising work [40] introduced a MAC protocol based on receiver-initiated handshakes driven by traffic estimation. Here, the receiver only initiates communication after gauging the current network load, enhancing collision avoidance and overall efficiency. Similarly, DAMAC was designed as a delay-sensitive MAC protocol for ad hoc UWSNs with static topologies, especially for critical infrastructure monitoring, like undersea pipelines. By removing pre-handshake packets and using simultaneous transmission scheduling, it lowers latency and improves energy usage. However, its static design may limit applicability in more mobile or dynamic network configurations. Research Gaps and Our ContributionAs summarized in Table 2, existing protocols either focus on singular performance aspects or introduce excessive complexity. The proposed ACRLPC framework addresses these gaps by combining the following:  
* Hybrid CSMA/CA-TDMA channel access. * Actor-Critic RL for dynamic adaptation. * Optimized power control. * Lightweight synchronization. This integrated approach achieves superior energy efficiency while maintaining low latency and high reliability in dynamic underwater environments.