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.

翻译：灾后通信恢复已成为搜救工作的重大挑战。设备到设备（D2D）与设备到车辆（D2V）网络备受关注。然而，受限于D2D覆盖范围与车载能源，构建混合D2D与D2V网络具有广阔前景。本文联合构建、优化并融合D2D与D2V网络，以支持高能效应急通信。首先，通过将地面设备（GDs）最优划分为多个集群，并从集群内的地面设备中识别临时数据缓存中心（TDCCs），建立D2D网络。相应地，来自地面设备的应急数据被缓存至TDCCs。其次，根据TDCCs的分布，派遣无人机（UAVs）从TDCCs获取数据。因此，通过路径规划与网络配置优化，构建无人机辅助的D2V网络：具体而言，采用级联航路点与运动规划实现最优路径规划，并通过多目标优化确定最优网络配置。最终，在满足信干噪比、无人机数量、发射功率与能量等约束条件下，达成应急响应时间与能耗的最佳折中。仿真结果表明，所提方法在能效方面优于基准方案，有助于大规模灾后应急响应。