密集分布式无线网络通过密集布设远程接入单元可以进一步缩短用户和天线间的接入距离，从而获得低传播损耗和高空间复用的优势，提高系统频谱效率和功率效率，是构建未来高效能绿色宽带移动通信系统关键技术之一。 在回程链路容量受限条件下，抑制密集分布式无线网络中RAU间干扰以及导频污染是极具挑战的，有必要深入研究适合密集分布式无线网络低复杂度、鲁棒的干扰管理技术。本项目拟开展利用长时信道信息的密集分布式无线网络资源调度技术研究，在密集分布式无线网络容量最大化准则下着力解决RAU间干扰以及导频污染等问题，从RAU资源、用户资源以及导频资源等方面，探寻利用长时信道信息的RAU选择与用户调度算法，设计利用长时信道信息的导频调度算法，发展利用长时信道信息的多小区协同调度算法，为构建高效能的密集分布式无线通信系统打下基础。

Massive distributed wireless network (MDWN) densely spreads out large numbers of remote access units (RAUs) over a given coverage area. This approach further reduces the access distance between users and RAUs, resulting in lower propagation losses and higher spatial reuse, therefore effectively improves the spectrum efficiency and power efficiency. MDWN technique is now considered as a key part of future energy-efficient green broadband mobile communication system. With capacity-limited backhaul, it is very challenging to mitigate inter-RAU interference and pilot contamination for MDWN. Therefore, it is important to investigate low complexity and robust interference management techniques for MDWN. In this project, we plan to focus on resource scheduling techniques for MDWN using long-term channel information. To deal with the issues about inter-RAU interference and pilot contamination according to maximum capacity criteria, respectively from the perspectives of antenna resource, user resource and pilot resource, we investigate long-term channel state information aided RAU selection and user scheduling algorithms, pilot reuse algorithms, multi-cell coordinated scheduling algorithms. The proposed algorithms form essential components in building up a highly efficient massive distributed wireless communication system.