Interference management with realistic assumptions on the knowledge of channel state information at the transmitters

我们的建议旨在开发有效的传输和接收方案的干扰限制多用户通信网络的信道状态信息（CSI）在发射机侧的可用性与现实的假设。过去几年对干扰受限网络容量限制的广泛研究已经证明，发射机处的CSI知识（CSIT）可以提供相当大的性能改进。事实上，对于许多网络，已经表明，在高SNR下，可以通过使用称为干扰对齐（IA）的方法利用CSIT来实现最佳性能。然而，在多用户网络中，网络的全局CSI必须在每个发射机处可用以执行IA。在该提议中，我们考虑了更现实的IA场景，其中发射机仅能够访问有限数量的CSI。我们的目标是开发计划，最佳地利用任何CSI是可用的，以提高频谱效率。在我们的第一种情况下，我们假设发射机可以访问延迟CSI，这意味着可用的信息是完全过时的，相对于当前的信道。先前已经示出，仅使用延迟的CSI，仍然可以在没有CSI可用的情况下实现复用增益。然而，许多解决方案中的延迟CSI问题是基于启发式方法。我们正在寻找可应用于一般设置的统一紧凑的解决方案。第二种情况是某些发射机不会对某些接收机产生干扰的情况。这种情况在真实的世界中是常见的，其中一些设备位于较远的位置。在部分连接的网络中，先前已经表明，IA即使在发射机处没有CSI也可以有效。我们的目标是通过利用网络特性来改进基于IA的方案。例如，收发器处的多天线节点可以在降维子空间中接收或发送，同时创建虚拟部分连接的网络。最后，我们研究了几个现实场景，并调整我们的解决方案以考虑实际的损伤。我们研究了在现实中多种条件并存的情况下，不同IA方法的联合应用。我们将进行真实的实验的多输入多输出（MIMO）的测试平台，以验证我们的算法在实际环境中的性能。

Our proposal aims at developing efficient transmission and reception schemes for interference-limited multi-user communication networks with realistic assumptions on the availability of channel state information (CSI) at the transmitter side. Extensive research on the capacity limits of interference-limited networks in the last several years has proved that knowledge of CSI at the transmitters (CSIT) can provide considerable performance improvements. Indeed, for many networks it has been shown that at high SNR the optimal performance can be achieved by exploiting the CSIT using a method called interference alignment (IA). However, the global CSI of the network must be available at each transmitter to perform IA in a multi-user network.In this proposal, we consider more realistic IA scenarios where the transmitters only have access to a limited amount of CSI. The goal is to develop schemes that optimally exploit whatever CSI is available to improve spectral efficiency.In our first scenario, we assume that the transmitters have access to delayed CSI, which means that the available information is completely outdated with respect to the current channel. It has been previously shown that using only delayed CSI it is still possible to achieve multiplexing gains over the case where no CSI is available. However, many of the solutions in the delayed-CSI problem are based on heuristic methods. We are looking for unified and compact solutions that can be applied to general settings.The second scenario is the case where some transmitters do not create interference for some receivers. This situation is common in the real world where some devices are at distant locations. In partially connected networks, it has been previously shown that IA can be effective even without CSI at the transmitter. Our objective here is to improve the IA-based schemes by exploiting network properties. For example, multi-antenna nodes at the transceivers can receive or transmit in reduced-dimensional subspaces while creating a virtual partially connected network.Finally, we investigate several realistic scenarios and adapt our solutions to account for practical impairments. We study joint application of different IA methods as multiple conditions coexist in reality. We will carry out real experiments on a multiple-input-multiple-output (MIMO) testbed to verify the performance of our algorithms in a practical setting.