NeTS: Medium: Multicell MIMO for Scalable High-Density Wireless Networks

公众对数据的需求一直在以巨大的速度增长，而且增长没有减弱的迹象。特别是，用户对智能手机、平板电脑和笔记本电脑等无线设备的数据要求越来越高。为了满足这一需求，在高需求地区部署的无线接入点(AP)的数量大幅增加，这导致附近无线通信之间的严重干扰，这降低了性能，并可能导致未满足的用户需求。这项研究正在研究基于多输入多输出(MIMO)通信的高级编码、信号处理和调度技术的开发，以显著减少竞争传输之间的干扰，从而显著增加可容纳的总体用户需求。该项目将通过向无线用户开放增强和虚拟现实等新型高需求应用程序来造福社会，并将在面对不断增长的数据需求时保持这些应用程序和其他应用程序的性能。该项目还将通过整合先进的信号处理开发和无线网络的统一课程来加强教育，而不是将这些作为单独的学科来对待的传统方法。这项研究是在覆盖家庭网络和小型企业的单个2-6个AP集群的AP协调框架内，研究多小区MIMO的新的非线性处理技术。为了满足大型企业无线网络的需求，该项目还在研究一种分层方法，该方法使用创新技术来处理群集之间的边缘节点干扰问题，以跨多个AP群集扩展性能。该项目将在多AP无线网络的性能扩展领域开发算法、技术和协议扩展。这些贡献包括：(1)用于最大化AP集群中的下行链路性能的新的非线性预编码方法，(2)用于在集群中选择用于并发通信的用户组的新算法，以及基于来自VLSI电路划分的经典算法迭代地改进用户分组的算法，(3)分割移动和静止用户并按需分配移动时隙的时隙协议，(4)跨AP集群提供一致的接入点定向以消除集群边界上的客户端之间的干扰的方法，(5)在集群之间执行的松散协调协议，其将允许相邻集群处理它们之间的干扰，而无需在网络上交换全部信道状态信息的昂贵开销，以及(6)用于客户端协调访问多个提供商网络的新的物理层感知技术。

The public's demand for data has been growing at an enormous rate and growth is showing no signs of diminishing. In particular, users are increasingly demanding data from wireless devices such as smart phones, tablets, and laptops. To accommodate this demand, the number of wireless access points (APs) being deployed in high-demand areas has increased substantially and this has resulted in significant interference between nearby wireless communications, which reduces performance and can result in unmet user demands. This research is studying the development of advanced coding, signal processing, and scheduling techniques based on multiple-input multiple-output (MIMO) communication to significantly reduce interference between competing transmissions, thereby substantially increasing the overall user demand that can be accommodated. The project will benefit society by opening up new types of high-demand applications, such as augmented and virtual realities, to wireless users and will maintain performance for these and other applications in the face of ever-increasing data demands. The project will also enhance education through unified courses that integrate advanced signal processing developments and wireless networking instead of the traditional approach, which treats these as separate disciplines. This research is investigating new nonlinear processing techniques for multicell MIMO within a framework of AP coordination for single clusters of 2-6 APs, which covers home networks and small enterprises. To address the demands of large enterprise wireless networks, the project is also researching a hierarchical approach, which employs innovative techniques to deal with the problem of edge-node interference between clusters to scale performance across multiple AP clusters. The project will develop algorithms, techniques, and protocol extensions in the area of performance scaling for multi-AP wireless networks. Among the contributions are: (1) a novel non-linear precoding approach for maximizing downlink performance in an AP cluster, (2) a new algorithm for selecting groups of users for concurrent communication in a cluster and an algorithm, based on a classic algorithm from VLSI circuit partitioning, for iteratively improving the user groupings, (3) a slotted protocol that segments mobile and stationary users and allocates mobile slots on demand, (4) an approach to providing consistent access point orientation across AP clusters so as to eliminate interference between clients at cluster boundaries, (5) a loose coordination protocol executed between clusters that will allow neighboring clusters to handle interference between them without the costly overhead of exchanging full channel state information across the network, and (6) new physical-layer-aware techniques for client-coordinated access to multiple providers networks.