###### Abstract  
Underwater wireless sensor networks (UWSNs) widely used for maritime object detection or for monitoring of oceanic parameters that plays vital role prediction of tsunami to life-cycle of marine species by deploying sensor nodes at random locations. However, the dynamic and unpredictable underwater environment poses significant challenges in communication, including interference, collisions, and energy inefficiency. In changing underwater environment to make routing possible among nodes or/ and base station (BS) an adaptive receiver-initiated deep adaptive with power control and collision avoidance MAC (DAWPC-MAC) protocol is proposed to address the challenges of interference, collisions, and energy inefficiency. The proposed framework is based on Deep Q-Learning (DQN) to optimize network performance by enhancing collision avoidance in a varying sensor locations, conserving energy in changing path loss with respect to time and depth and reducing number of relaying nodes to make communication reliable and ensuring synchronization. The dynamic and unpredictable underwater environment, shaped by variations in environmental parameters such as temperature (T) with respect to latitude, longitude, and depth, is carefully considered in the design of the proposed MAC protocol. Sensor nodes are enabled to adaptively schedule wake-up times and efficiently control transmission power to communicate with other sensor nodes and/or courier node plays vital role in routing for data collection and forwarding. DAWPC-MAC ensures energy-efficient and reliable time-sensitive data transmission, improving the packet delivery rati (PDR) by 14%, throughput by over 70%, and utility by more than 60% compared to existing methods like TDTSPC-MAC, DC-MAC, and ALOHA MAC. These enhancements significantly contribute to network longevity and operational efficiency in time-critical underwater applications. Deep Q-learning (DQN); collision avoidance; energy efficiency; throughput; MAC protocol; underwater wireless sensor network (UWSN) +
Footnote †: journal: Marine Science and Engineering  
_Article_
distributed sensors that utilize acoustic signals, enable the monitoring and transmission of critical information, overcoming the unique physical challenges posed by the underwater environment. UWSNs have expanded the scope of applications, including oceanographic mapping, marine biodiversity monitoring, underwater earthquake detection, maritime navigation, and disaster prediction [1]. They also play a pivotal role in tactical surveillance and resource management, providing real-time data to improve our understanding of underwater ecosystems and address pressing global challenges. However, the underwater environment presents significant challenges including high bit error rates (BER), often caused by environmental interference, and the inherent vulnerability of acoustic channels increases the likelihood of communication failures. Additional complications include fluctuating channel conditions, limited bandwidth (B), and limited channel capacity (C), all of which can degrade network performance. These harsh conditions underscore the necessity of robust MAC protocols. Effective MAC protocols are critical for managing channel access, mitigating interference, and ensuring reliable communication under challenging conditions [2]. UWSNs preferably rely on acoustic waves rather than radio frequency (RF) signals, while still offering merits such as a high penetration rate. Although acoustic waves have slower propagation speeds (1500 m/s) compared to RF signals. They are preferred for underwater communication due to their ability to travel for longer distances with less attenuation [3; 4]. However, UWSN communication protocols encounter substantial obstacles, such as restricted bandwidth, elevated bit error rates, and the sluggish speed of acoustic signal propagation [5]. The MAC protocol, an essential component of the data link layer, oversees the allocation of access to the communication channel among nodes within a network [6].