Multilink and AUV-Assisted Energy-Efficient Underwater Emergency Communications

TL;DR

This paper proposes an energy-efficient underwater emergency communication network using multiple links and autonomous vehicles, optimizing data collection and transmission to improve response times and reduce energy consumption.

Contribution

It introduces a novel multi-link underwater emergency network with AUV assistance, combining reinforcement learning and evolutionary algorithms for optimal resource allocation.

Findings

Outperforms benchmark schemes in energy efficiency

Reduces emergency response time significantly

Optimizes AUV deployment and power control effectively

Abstract

Recent development in wireless communications has provided many reliable solutions to emergency response issues, especially in scenarios with dysfunctional or congested base stations. Prior studies on underwater emergency communications, however, remain under-studied, which poses a need for combining the merits of different underwater communication links (UCLs) and the manipulability of unmanned vehicles. To realize energy-efficient underwater emergency communications, we develop a novel underwater emergency communication network (UECN) assisted by multiple links, including underwater light, acoustic, and radio frequency links, and autonomous underwater vehicles (AUVs) for collecting and transmitting underwater emergency data. First, we determine the optimal emergency response mode for an underwater sensor node (USN) using greedy search and reinforcement learning (RL), so that isolated USNs (I-USNs) can be identified. Second, according to the distribution of I-USNs, we dispatch AUVs to assist I-USNs in data transmission, i.e., jointly optimizing the locations and controls of AUVs to minimize the time for data collection and underwater movement. Finally, an adaptive clustering-based multi-objective evolutionary algorithm is proposed to jointly optimize the number of AUVs and the transmit power of I-USNs, subject to a given set of constraints on transmit power, signal-to-interference-plus-noise ratios (SINRs), outage probabilities, and energy, which achieves the best tradeoff between the maximum emergency response time (ERT) and the total energy consumption (EC). Simulation results indicate that our proposed approach outperforms benchmark schemes in terms of energy efficiency (EE), contributing to underwater emergency communications.