Linear MIMO Techniques in Multiuser Wireless Communications

最近对无线通信系统中的MIMO系统的研究一直集中在Costa的脏纸编码（Dirty Paper Coding）上，这是一种优雅的方法，用于（至少原则上）实现矢量BC和MIMO BC信道的两个重要性能度量（即，总容量和加权总速率）的理论界限。尽管理论上非常吸引人，但DPC技术存在几个缺点;即，非常复杂的实现方式、如果考虑次优THP解决方案则会导致性能损失、以及在许多相关场景中甚至可能禁止实际实现、在相应通信链路的发射机侧需要非常精确的信道状态信息。特别地，后者在备选通信场景中被证明是严重的缺点，例如在具有高移动性应用的网络中，或者备选地对于干扰信道场景，其中多个空间分布的MIMO系统在网络会话期间或在蜂窝网络的边界处彼此干扰。为此，线性MIMO技术，不诉诸DPC是非常有吸引力的候选人，用于开发无线通信网络中的空间信号处理的潜在性能增强，而没有与DPC和THP相关的挑战性要求。然而，有趣的是，尽管线性MIMO技术似乎是基本波束成形技术的自然扩展，空时处理的成功演进甚至开始于基本波束成形技术，但底层优化通常变得相当复杂，甚至比理论上要求更高的DPC更复杂，并且线性MIMO的几个问题至今仍未解决。考虑到线性MIMO信号处理的本质挑战，现有的以前的工作主要集中在次优方案的基础上（块）对角化的底层多用户MIMO信道或通过施加单独解码的数据流的约束，而不利用多个合作接收器在各自的数据汇的潜力。在这个提出的项目中，将不施加这样的限制，因为目标是利用最近发现的具有线性预编码的MIMO BC和具有线性用户分离的MIMO MAC之间的对偶结果。这个新的对偶结果将作为一个有条理的处理线性MIMO系统在多用户通信的情况下，各自的算法的设计的基本框架。

The recent research on MIMO systems in wireless communication systems has been concentrating on Costa’s Dirty Paper Coding, which is an elegant approach for – at least principally – achieving the theoretically bounds of two important performance measures for the vector BC and MIMO BC channel, namely the sum capacity and the weighted sum rate. Although theoretically very appealing, the DPC technique suffers from a couple of drawbacks; that are the very complex implementation, the performance loss if considering the suboptimal THP solution, and, which in many relevent scenarios might even be prohibitive for practical implementation, the requirement of very precise channel state information at the transmitter side of the respective communication links. Especially, the latter turns out to be a severe drawback in alternative communication scenarios, e.g. as in networks with high mobility applications, or alternatively for the interference channel scenario, where multiple spatially distributed MIMO systems interfere with each other during a network session or at the border of a cellular network. To this end, linear MIMO techniques which do not resort to DPC are very attractive candidates for the exploitation of the potential performance enhancements by spatial signal processing in wireless communication networks without the challenging requirements related with DPC and THP. However, interestingly enough, although linear MIMO techniques appear to be the natural extension of the fundamental beamforming techniques, which the successful evolution of space time processing even started with, the underlying optimizations generally turn out to be rather complicated, even more complicated than for the theoretically more demanding DPC, and a couple of problems with linear MIMO have remained unsolved until now. Taking into account the intrinsical challenges of linear MIMO signal processing the existing previous work mainly concentrates on suboptimal schemes based on the (block) diagonalization of the underlying multiuser MIMO channels or by imposing the constraint of separately decoded data streams without exploiting the potential of multiple cooperating receivers at the respective data sinks. In this proposed project, such restrictions will not be imposed, since the goal is rather to exploit the recently discovered duality results between the MIMO BC with Linear Precoding and the MIMO MAC with linear user separation. This new duality results will serve as the fundamental framework for a methodical treatment of linear MIMO systems in multiuser communication scenario and the design of respective algorithms.