## 1 Introduction  
UACNs employ sound waves to transmit information and facilitate data exchange between underwater devices via underwater acoustic channels. UACNs play a pivotal role in numerous fields, including ocean observation, underwater operations, military applications, and business [1, 2]. UACNs typically comprise three main components: fixed underwater acoustic sensor nodes, mobile autonomous underwater vehicles (AUVs), and water gateway nodes. A distributed, multi-hop, three-dimensional network is formed by the aggregation of multiple nodes at different locations. The nodes exchange data via underwater acoustic communication and relay information to the central node through the underwater relay nodes. Although there are conceptual similarities between UACNs and terrestrial wireless electromagnetic wave networks, underwater acoustic channels are considerably more complex than terrestrial wireless channels. This complexity arises from several factors, including multipath effects, Doppler effects, time-varying characteristics, and limited available bandwidth. These factors result in a high BER, high susceptibility to link interruptions, and increased packet loss in communication transmissions [3, 4, 5, 6]. Consequently, UACNs cannot directly adopt the protocols and techniques of terrestrial wireless electromagnetic wave protocols and technologies. When designing routing protocols for UACNs, it is essential to fully consider the characteristics of the underwater acoustic channels and the underwater environment in order to establish a reliable transmission mechanism that achieves a high PDR in the multi-hop network. In UACNs, factors such as data surges and node failures can lead to network congestion, resulting in packet loss and reception interference, as well as increased queuing delay. This further increases the end-to-end delay and reduces the PDR [7]. Furthermore, sensor nodes in UACNs typically operate on independently sourced power, which is limited and challenging to replenish. Consequently, the energy consumption must be taken into account when designing routing protocols for UACNs. To address the aforementioned challenges, researchers have proposed cross-layer design approaches, as evidenced by the following references: [8; 9; 10]. In contrast to traditional network protocols, which are designed independently within their respective layers, cross-layer protocols facilitate information sharing between different layers, enabling the network to dynamically adjust routing decisions and resource allocation based on real-time channel conditions, node states, and application requirements. This optimization enhances overall network performance [11]. In [12; 13; 14], the authors emphasize the importance of considering node energy consumption, transmission path selection, and routing strategy optimization in routing protocol design to improve energy utilization efficiency. However, the impact of node congestion on energy consumption, end-to-end delay, and PDR is not investigated. References [15; 16] address the dual issues of energy efficiency and congestion in protocol design; however, insufficient attention is paid to the critical impact of channel quality on PDR. In [17], the receiver signal-to-noise ratio (SNR) is employed to forecast the channel quality, which incorporates the propagation characteristics of signals. However, the physical layer effects during orthogonal frequency-division multiplexing (OFDM) modulation and demodulation are not fully considered. To increase the PDR in complex marine environments, a cross-layer routing protocol, the CLCQ, for UACNs is proposed that combines channel quality and node congestion state. The design of this protocol fully accounts for the specific characteristics of the marine environment. The winter sound velocity profile data from a specific sea area are employed to calculate the channel impulse response and propagation loss using the BELLHOP ray model. These real marine channel characteristics are then introduced into the OFDM communication system.