The evolution of Internet of Things (IoT) into multi-layered environments has positioned Low-Power Wide Area Networks (LPWANs), particularly Long Range (LoRa), as the backbone for connectivity across both surface and subterranean landscapes. However, existing LoRa-based network designs often treat ground-based wireless sensor networks (WSNs) and wireless underground sensor networks (WUSNs) as separate systems, resulting in inefficient and non-integrated connectivity across diverse environments. To address this, we propose Hetero-Net, a unified heterogeneous LoRa framework that integrates diverse LoRa end devices with multiple unmanned aerial vehicle (UAV)-mounted LoRa gateways. Our objective is to maximize system energy efficiency through the joint optimization of the spreading factor, transmission power, and three-dimensional (3D) placement of the UAVs. To manage the dynamic and partially observable nature of this system, we model the problem as a partially observable stochastic game (POSG) and address it using a multi-agent proximal policy optimization (MAPPO) framework. An ablation study shows that our proposed MAPPO Hetero-Net significantly outperforms traditional, isolated network designs, achieving energy efficiency improvements of 55.81\% and 198.49\% over isolated WSN-only and WUSN-only deployments, respectively.

翻译：摘要：物联网向多层环境的演进使得低功耗广域网（LPWAN），特别是远距离无线电（LoRa），成为连接地面和地下景观的骨干网络。然而，现有的基于LoRa的网络设计通常将地面无线传感器网络（WSNs）和地下无线传感器网络（WUSNs）视为独立系统，导致不同环境间的连接效率低下且缺乏集成性。为解决这一问题，我们提出异构网络（Hetero-Net），一个统一的异构LoRa框架，该框架集成多种LoRa终端设备与多个搭载无人机的LoRa网关。目标是联合优化扩频因子、传输功率以及无人机的三维（3D）部署位置，以最大化系统能效。为应对该系统的动态和部分可观测特性，我们将问题建模为部分可观测随机博弈（POSG），并采用多智能体近端策略优化（MAPPO）框架求解。消融研究表明，我们提出的MAPPO异构网络显著优于传统孤立网络设计，相比仅部署WSN和仅部署WUSN的方案，能效分别提升55.81%和198.49%。