异构无线供电反向散射通信网络优化研究

Heterogeneous wireless-powered backscatter communication network (WPBCN) is a novel network paradigm to meet the future requirements of Internet of Things (IoT), which becomes the focus of academia and industry. However, since the research on this network paradigm is in its infancy, there still exist many critical technical challenges to be solved, such as the improvement of network throughput, enhancement of network reliability and satisfaction of diverse service requirements of users. Considering the above challenges, this project, with the aim to design novel network optimization schemes, is carried out under deterministic network environment and stochastic network environment. Under the deterministic network environment, using the optimization techniques, we first design a beamforming scheme to enhance network throughput, then propose a high reliability communication scheme based on cooperative communication, and subsequently design an optimization algorithm to satisfy quality of service (QoS) constraints of users. Under the stochastic network environment, the network optimization frameworks are constructed by Markov decision process or Markov game. With reinforcement learning or deep reinforcement learning, we first design a low-complexity time scheduling scheme, then propose an optimal policy of applying cooperative communication, and subsequently design the dynamic access mechanism of users with different priorities. The research work of this project will provide theoretical bases and technical approaches for heterogeneous WPBCN to meet the requirements of high throughput, high reliability and diverse services, and promote its application in the future IoT.

异构无线供电反向散射通信网络是满足未来物联网需求的新型网络。然而该网络中仍有很多关键问题和技术难题亟待解决，例如如何提高网络容量、增强网络可靠性和满足用户多样化服务需求等。针对上述问题，本项目以构建新型的网络优化方案为目标，面向确定性网络环境和不确定性网络环境开展研究工作。针对确定性网络环境，利用优化技术，提出了基于波束成形的网络性能增强方案，构建了基于协作通信的高可靠性通信机制，设计了满足用户业务QoS的性能优化算法。针对不确定性网络环境，利用马尔可夫决策过程或马尔可夫博弈构建了网络优化框架，依托强化学习和深度强化学习技术，设计了低复杂度的时隙资源调度方案，构建了协作通信的最优准入策略，提出了不同优先级的无线设备的动态接入机制。本项目研究成果将为异构无线供电反向散射通信网络满足高容量、高可靠性和多样化服务的网络需求提供理论依据和技术支持，推动其在未来物联网中的实用化进程。

为推动物联网通信的发展与应用，本项目针对异构无线供电反向散射通信网络展开研究工作。针对非协作通信场景，提出了基于博弈论的能量交互模型，实现了不同服务提供商的效益优化；构建了面向能量采集和任务卸载的全双工通信机制，探究了自干扰强度与系统性能的物理关联。针对协作通信场景，设计了基于主动射频中继的协作通信方案，设计了高效的时隙调度方案，有效改善了能量采集和信息传输的效率；设计了基于被动反射中继的协作传输方案，实现了主被动波束成形与网络资源的适配。所提出的协作通信方案实现了高可靠的通信机制，拓展了网络覆盖范围。针对服务需求驱动场景，设计了基于强化学习的中继节点传输模式动态切换策略；面向安全传输需求，设计了基于智能反射面的物理层安全传输策略；面向海量连接和服务质量要求，设计了集群接入控制和簇内资源分配方案。本项目研究成果有效提高了网络容量、增强了网络可靠性和满足了多样化的网络服务需求，为物联网的发展和应用提供了理论依据和方案支撑。