Hybrid Device-to-Device and Device-to-Vehicle Networks for Energy-Efficient Emergency Communications

TL;DR

This paper proposes a hybrid D2D and D2V network framework to improve energy-efficient emergency communications postdisaster, combining clustering, caching, UAV path planning, and multiobjective optimization.

Contribution

It introduces a joint approach to establish, optimize, and fuse D2D and D2V networks for energy-efficient emergency response, including novel path planning and network configuration methods.

Findings

Outperforms benchmark schemes in energy efficiency

Achieves optimal tradeoff between response time and energy consumption

Effectively supports large-scale postdisaster emergency communications

Abstract

Recovering postdisaster communications has become a major challenge for search and rescue. Device-to-device (D2D) and device-to-vehicle (D2V) networks have drawn attention. However, due to the limited D2D coverage and onboard energy, establishing a hybrid D2D and D2V network is promising. In this article, we jointly establish, optimize, and fuse D2D and D2V networks to support energy-efficient emergency communications. First, we establish a D2D network by optimally dividing ground devices (GDs) into multiple clusters and identifying temporary data caching centers (TDCCs) from GDs in clusters. Accordingly, emergency data returned from GDs is cached in TDCCs. Second, given the distribution of TDCCs, unmanned aerial vehicles (UAVs) are dispatched to fetch data from TDCCs. Therefore, we establish a UAV-assisted D2V network through path planning and network configuration optimization. Specifically, optimal path planning is implemented using cascaded waypoint and motion planning and optimal network configurations are determined by multiobjective optimization. Consequently, the best tradeoff between emergency response time and energy consumption is achieved, subject to a given set of constraints on signal-to-interference-plus-noise ratios, the number of UAVs, transmit power, and energy. Simulation results show that our proposed approach outperforms benchmark schemes in terms of energy efficiency, contributing to large-scale postdisaster emergency response.