MAC Protocol for ISAC in Underwater Acoustic Networks With Dynamic Target Monitoring–Localization–Tracking

This paper proposes a multiple access control (MAC) protocol for integrated sensing and communication in underwater acoustic networks (ISAC-UANs) with dynamic target monitoring, localization, and tracking, where some ISAC nodes are deployed to collaboratively communicate and detect targets via integrated underwater acoustic signals. The proposed integrated underwater sensing and communication (USAC)-MAC protocol focuses on addressing the challenges of packet collisions and resource contention in the dual-function network. Specifically, the protocol is divided into three stages: target monitoring, target localization, and the target tracking phase. The target monitoring phase is carried out to initialize the network topology and search for detection targets. The conflict-free concurrent transmission constraints are established based on topological information to enable conflict-free and efficient data transmission. After detecting the target, the protocol transfers into the target localization phase, which localizes the target applying the time of arrival (TOA) method. We model the optimization problem to minimize the Cramér-Rao lower bound (CRLB) and employ the particle swarm optimization (PSO) algorithm to solve it under the constraint of the geometric position of nodes. During the target tracking phase, we enhance target detection accuracy by dynamically selecting detection node clusters based on predicted target trajectories. Concurrently, we schedule packet transmission times to minimize the communication frame length. Thereby, a joint optimization problem for the CRLB of localization and the frame length of communication is established and addressed by the simulated annealing (SA) algorithm, ensuring detection precision while reducing communication latency. Simulation results demonstrate that the proposed protocol exhibits superior performance with higher throughput, shorter frame length, shorter information update times, and more precise detection accuracy.