密集无线网络分布式和鲁棒性传输理论与方法

As a consequence of the rapid development of mobile communications, wireless networks tend to be more and more dense. In the next 5G mobile communication systems, wireless networks will be densified by Small Cell and D2D communication technologies. The performance of dense spectrum-shared networks is mainly limited by interference, and thus interference coordination transmission techniques are needed, which, however, strongly depend on accurate instantaneous environment information such channel state information. The densification of wireless networks causes a huge amount of environment information exchanging and gathering and also inevitable imperfection of environment information. The conventional centralized and non-robust transmission techniques will result in lots of backhaul overheads, delay, and performance loss. Therefore, this project aims to study distributed and robust transmission theories and methods for dense Small Cell and D2D multi-tier heterogeneous networks. The goal is to decrease the dependence of accurate instantaneous environment information, and achieve closed-to-globally-optimal performance through a small amount of signaling exchange. For this purpose, we will induce advanced theories such as generalized Nash equilibrium, variational inequality, potential game, etc., and design distributed interference coordination transmission methods. We will also develop generalized robust transmission theories and methods that are applicable to various imperfect environment information and various performance metrics. This project will develop new distributed and robust optimization theories and method and increase the practicability of dense wireless networks, thus bearing both important theoretical meanings and significant practical merits.

无线网络密集化是移动通信发展的必然趋势，Small Cell和D2D通信将是5G移动通信系统实现网络密集化的主要方式。在共享频谱资源的密集网络中，干扰是限制系统性能的主要因素，干扰协调传输技术成为关键，而其性能依赖于精确实时的信道状态等环境信息。然而无线网络密集化造成了海量环境信息交互汇聚和环境信息高度非理想性，传统的集中式和非鲁棒的传输技术将会造成极大的回传损耗、时延和性能损失。本项目将重点研究Small Cell和D2D密集多层异构网络的分布式和鲁棒性传输理论与方法，降低系统对精确实时环境信息的依赖，通过少量信令交互，获得逼近全局最优的性能。项目将在广义纳什均衡、变分不等式、潜博弈等理论基础上设计分布式干扰协调传输方法，并研究适用于多种非理想情况和性能指标的普适性鲁棒性传输理论与方法。项目研究将形成新的分布式和鲁棒性优化理论与方法，推动密集无线网络实用化，具有重要的理论价值和实际意义。

无线网络密集化是移动通信从4G向5G及5G后移动通信发展的必然趋势。网络中包括宏基站、Small Cell小基站、蜂窝用户、D2D用户等各种类型的接入设备，同时基站普遍配置多天线或大规模天线阵列，从而构成了密集异构无线网络。密集异构网络协同传输依赖于信道信息等环境信息，并造成了海量信令交互和高计算复杂度。本项目针对Small Cell密集多层异构网络、D2D密集多层异构网络、云无线异构网络、密集中继网络、非正交接入系统、可见光通信网络等展开研究，提出了高效的分布式功率分配、信道分配、波束成形、预编码、能效优化等理论与方法，以较低的信令开销和计算复杂度获得了较大的性能提升。同时，本项目还针对多天线MIMO、大规模MIMO、毫米波通信系统信道信息难以精确获取，信道信息普遍具有非理想性等问题，提出了一系列鲁棒性的传输方法，降低了通信系统对精准实时信道信息的依赖，提升了系统在非理想环境中的性能。迄今已发表论文57篇，其中国际权威期刊（SCI）论文40篇，ICC、GLOBECOM等权威国际会议论文17篇，申请发明专利39项，其中授权25项。

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