Interference Management and the Capacity of Wireless Networks

项目摘要：干扰管理和无线网络的容量干扰被认为是在无线网络中实现更高数据速率的主要障碍。最近出现的干扰对齐的想法表明，无线网络的容量可以显着高于先前的估计。关键思想是巧妙地设计信号，使其占据一半的带宽，使它们在每个接收器上投射重叠的阴影，从而构成干扰，同时在需要它们的接收器上保持不同。令人惊讶的结论是，“每个人都得到一半的蛋糕”，即，不管竞争相同无线频谱的用户的数量如何，潜在地，每个用户都能够访问一半的带宽而不受其他用户的干扰。本研究将干扰对齐的观点整合到现有的无线网络容量结果中，并使用集体的见解，工具和技术来开发最佳的干扰管理算法。从本研究中产生的干扰管理的综合视图是一个重大的贡献，无线网络设计的理论和实践。它提供的分析见解不仅在估计无线网络的性能极限方面至关重要，而且在寻找接近这些极限的有效方法方面也至关重要。了解无线网络的能力对于工业界、学术界、政府机构和整个社会来说都是至关重要的，以便对未来的无线网络有现实的期望。研究人员采用分层的方法，包括以下三个方面：（1）基本场景的容量表征，（2）不同类别网络的广义自由度表征，（3）大型网络的分布式干扰管理算法。在微观层面上，该研究探讨了元素网络的参数化连续体的能力，这些网络捕获了干扰对齐是容量最佳的场景与经典强干扰，非常强的干扰和嘈杂干扰情况之间的过渡状态。在一个粗略的，但更大的规模，容量近似的形式获得的广义自由度表征的无线网络，包括中继，反馈和合作的影响。第三阶段采取宏观的无线网络，并结合从容量和自由度的角度到分布式干扰管理算法的见解。网络管理算法的稳定性和信道不确定性的鲁棒性也进行了研究。

Project Summary: Interference Management and the Capacity of Wireless NetworksInterference is believed to be the principal barrier to achieving higher data rates in wireless networks. The recent emergence of the idea of interference alignment has shown that the capacity of wireless networks can be significantly higher than prior estimates. The key idea is to design signals cleverly to occupy half the bandwidth in such a manner that they cast overlapping shadows at each receiver where they constitute interference, while they remain distinct at the receivers where they are desired. The surprising conclusion is that "everyone gets half the cake", i.e., regardless of the number of users competing for the same wireless spectrum, potentially every user is able to access half the bandwidth with no interference from other users. This research integrates the interference alignment perspective into the existing array of wireless network capacity results and uses the collective insights, tools and techniques to develop optimal interference management algorithms. The integrated view of interference management resulting from this research is a significant contribution to both the theory and practice of wireless network design. It contributes analytical insights that are pivotal in not only estimating the performance limits of wireless networks but also in finding efficient ways to approach these limits. Understanding the capabilities of wireless networks is essential for the industry, the academia, the government agencies and the society in general to have realistic expectations from the wireless networks of the future.The investigators adopt a layered approach with the following three thrusts - (1) Capacity characterizations for elemental scenarios, (2) Generalized degrees of freedom characterizations for different classes of networks, and (3) Distributed interference management algorithms for large networks. At the microscopic level, the research explores the capacity of a parameterized continuum of elemental networks that capture the transitional regime between scenarios where interference alignment is capacity optimal and the classical strong interference, very strong interference and noisy interference cases. On a coarse but larger scale, capacity approximations are obtained in the form of generalized degrees of freedom characterizations for wireless networks, including the impact of relays, feedback and cooperation. The third stage takes a macroscopic view of wireless networks and combines the insights obtained from the capacity and degrees of freedom perspectives into distributed interference management algorithms. The stability of network management algorithms and their robustness to channel uncertainty is also investigated.