Noncooperative Beamforming for Ad hoc Networks

当前的无线数据网络，例如基于单天线传输的802.11b/g/a（Wi-Fi），在给定区域中可以支持的用户数量（容量）方面是低效的。多天线阵与波束赋形和空时编码相结合可以大大提高蜂窝网络的容量。然而，使用天线阵列来增强Ad hoc网络中的容量（即，当基站不可用时）还没有得到很好的理解。在Ad hoc网络中利用天线阵列的新波束成形和空时编码技术的发展将大大增加未来Wi-Fi和Wi-Max类型应用中可以支持的用户数量和数据速率，并减少对蜂窝和光学骨干基础设施的依赖。本计画针对Ad hoc无线网路的容量需求，提出并分析了一种基于迭代最小均方误差波束形成的分布式阵列处理算法。在IMMSE中，每个节点处的发射波束形成器被设置为使用训练序列计算的常规MMSE接收波束形成器的共辄。IMMSE，然后研究使用非合作博弈论，以获得收敛性和效率的结果。IMMSE算法扩展到空时编码产生近似的解决方案，以最大限度地提高解耦的香农容量的Ad hoc网络。这些IMMSE-Deflation（IMMSE-D）算法试图平衡期望的链路容量与对其他链路的干扰税，因此可以提供比贪婪容量最大化算法更好的网络吞吐量。通过在网络仿真软件包中嵌入IMMSE和IMMSE-D算法来评估整个网络的吞吐量。

Current wireless data networks, such as 802.11b/g/a (Wi-Fi) which arebased on single antenna transmission are inefficient in terms ofthe number of users (capacity) that can be supported in a given area. It is well known that multiple antenna elements (arrays) can be combined withbeamforming and space-time coding to greatly enhance the capacity ofcellular networks. However, the use of antenna arrays to enhance capacity in Ad hoc networks (i.e. when a base station is not available)is not well understood. The development of new beamforming and space-time coding techniques that exploit antenna arrays in Ad hoc networks will greatly increase the number of users and data rates that can be supported in future Wi-Fi and Wi-Max type applications, and reduce dependence on cellular and optical backbone infrastructures. This project specifically develops and analyzes a class of distributed array processing algorithms for increasing Ad hoc wireless network capacity based on iterative minimum mean-square error (IMMSE) beamforming. In IMMSE, the transmit beamformer at each node is set to the conjugate of the conventional MMSE receive beamformer computed using a training sequence. IMMSE is then studied using noncooperative game theory in order to obtain convergence and efficiency results. The IMMSE algorithm is extended to space-time coding to yield approximate solutions to maximizing decoupled Shannon capacities of Ad hoc networks. These IMMSE-Deflation (IMMSE-D)algorithms attempt to balance desired link capacity with a tax oninterference to other links, and hence may offer better networkthroughput than greedy capacity-maximization algorithms. Overallnetwork throughput is evaluated by embedding the IMMSE and IMMSE-Dalgorithms in a network simulation software package.