基于受控博弈的超密集异构网络异质QoS资源自优化方法研究

Ultra-dense heterogeneous network is utilized to approach the future 1000 ultra-high traffic volume. Nevertheless, the dense deployment of network would intensify the competition of users due to the limited wireless resources. Traditional centralized resource management has the best overall performance but the complexity is too high. The signaling complexity of the fully distributed resource control is low but it is difficult to achieve global optimization. Therefore, it is difficult to guarantee the heterogeneous QoS requirements by utilizing the single centralized or distributed methods. This project will focus on the core problem of how to efficiently and smartly allocate the dynamic network resources to satisfy the heterogeneous QoS requirements and investigate the self-optimizing theory and methods of resource configuration in ultra-dens heterogeneous network. The main research contents include the network utilization modeling by considering the heterogeneous QoS requirements, the new theory and methods of self-optimization algorithm based on the controlled game, as well as the analysis of the algorithm cost. The potential innovations of this project include the following three folds. First, we intend to propose the new resource management idea, i.e., controlled game and competition orderly, based on the characteristics of ultra-dense network architecture with centralized control and self-autonomy. Second, we intend to utilize the self-optimizing technology under the controlled game framework to design the resources configuration methods to approach the global optimal performance. Third, we will introduce the Vibrational Inequality (VI, GVI) theories to design self-optimizing algorithms. Finally, a complete resource self-optimized configuration scheme will be formed to improve resource utilization ratio.

超密集异构组网是满足未来无线网络千倍数据流量需求的重要手段。然而，网络的密集化同时也加剧了用户对有限资源的竞争，采用传统单一的集中式或分布式资源分配模式无法以较低复杂度最优化网络性能，难以保障用户异质服务质量（QoS）需求。本项目拟基于受控博弈这一结合局部竞争与全局优化的新型资源管控思想，围绕“如何更加高效、智能、自主地配置超密集异构网络资源以保障异质QoS需求”这一核心科学问题，研究动态资源的自优化配置方法。具体研究内容包括面向异质QoS需求特征的网络效用建模、基于受控博弈的资源优化机理和资源自优化方法等。本项目创新点是从超密集异构网络可控与自治的网络架构特征出发，提出“受控博弈，有序竞争”的资源管控思路，利用“受控博弈”框架和“自优化”技术设计逼近全局最优性能的资源配置方法，引入比传统博弈论更加完备的变分不等式理论设计自优化算法，最终形成完整的资源自主优化配置方案，提升资源利用率。

超密集异构网络是满足未来无线网络千倍数据流量需求的重要技术之一。然而，网络的密集部署加剧了用户对有限资源的竞争，用户服务质量（QoS）需求的异质化对无线资源管理带来了更大的挑战。本项目围绕“如何更加高效、智能、自主地配置超密集异构网络资源以保障异质QoS需求”这一核心科学问题，针对超密集异构网络“集中可控”与“分布式自治”架构特征，研究面向超密集异构网络的资源分配新理论与方法，实现网络资源的高效智能优化配置。针对上述研究内容，本项目首先研究了面向超密集异构网络用户关联问题，提出了高效用户关联与资源优化方法；其次，研究了异构网络多维资源管理方法，提出了满足异质服务质量要求的超密集网络计算、通信和缓存三维资源智能分配系列方法，解决了超密集网络用户之间的资源竞争和按需分配问题；最后，研究了数据资源共享问题，提出了基于契约理论的多种数据资源共享激励机制。在本项目的资助下，项目组共发表论文18篇、其中SCI期刊论文16篇，包括通信领域著名期刊IEEE Internet of Things Journal 、IEEE Transactions on Vehicular Technology 2篇、Digital Communications and Networks、IEEE Wireless Communications Letters、IEEE Transactions on Green Communications and Networking等，授权国家发明专利7项，超额完成既定目标。本项目相关研究成果可为超密集异构网络高效、智能资源配置提供理论支撑。

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