Zhao Tingyin, Li Zhidu
School of Communications and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China.
Information and Communications Institute, Chongqing University of Posts and Telecommunications, Chongqing 400065, China.
Sensors (Basel). 2024 Jul 20;24(14):4711. doi: 10.3390/s24144711.
This paper presents an innovative approach towards space-ground integrated communication systems by combining terrestrial cellular networks, UAV networks, and satellite networks, leveraging advanced slicing technology. The proposed architecture addresses the challenges posed by future user surges and aims to reduce network overhead effectively. Central to our approach is the introduction of a marginal mobile station (MS)-assisted network resource allocation decision architecture. Building upon this foundation, we introduce the DP-DQN model, an enhanced decision-making algorithm tailored for MSs in dynamic network environments. Furthermore, this study introduces a feedback mechanism to ensure the accuracy and adaptability of the marginalization model over time. Through extensive simulations and experimental validations, our DP-DQN-based edge decision method demonstrates substantial potential in alleviating core network overhead while improving success access ratios compared to conventional methods.
本文提出了一种创新方法,通过结合地面蜂窝网络、无人机网络和卫星网络,并利用先进的切片技术,构建天地一体化通信系统。所提出的架构解决了未来用户激增带来的挑战,旨在有效降低网络开销。我们方法的核心是引入一种边缘移动台(MS)辅助的网络资源分配决策架构。在此基础上,我们引入了DP-DQN模型,这是一种针对动态网络环境中的移动台量身定制的增强型决策算法。此外,本研究引入了一种反馈机制,以确保边缘化模型随时间的准确性和适应性。通过广泛的仿真和实验验证,与传统方法相比,我们基于DP-DQN的边缘决策方法在减轻核心网络开销的同时提高成功接入率方面显示出巨大潜力。