NeTS: Small: Control of Partially Observable Wireless Networks: Fundamental Limits, Optimal Algorithms and Practical Implementation

状态相关的资源分配是提高网络效率的关键。在过去的二十年里，通过使用状态相关的资源分配算法，在设计具有最大吞吐量和低延迟的无线网络方面取得了显著的进展。然而，这些工作大多假设网络是完全可观察的，网络状态信息是完全已知的。由于多载波技术使得获得完整的网络状态信息变得极其昂贵，并且传输延迟和测量误差使得不可能知道确切的网络状态，因此这种假设变得越来越有问题。随着无线网络在日常生活中的广泛应用，部分可观测的无线网络需要新的理论和算法，在本项目中，PI将部分可观测的无线网络建模为部分可观测的马尔可夫过程，然后应用马尔可夫决策过程（MDP）框架。虽然可以使用MDP框架发现重要的结构属性，但通常找到最优解是NP难问题。为了克服这一困难，本项目使用基于漂移的竞争分析和基于漂移的大偏差分析来量化基本限制并导出最佳或接近最佳的算法。该项目有望在管理部分可观测的无线网络方面取得突破。部分可观测无线网络的基本限制，具有可证明的吞吐量和延迟保证的新型资源分配算法，以及在真实世界测试床上的实现将对未来无线网络的设计和实现产生重大影响。

State dependent resource allocation is critical for improving the network efficiency. Over the past two decades, remarkable progress has been made on the design of wireless networks with maximum throughput and low latency by using state dependent resource allocation algorithms. However, most of these works assume the network is fully observable and the network state information is perfectly known. This assumption is becoming increasingly questionable because of the multi-carrier technology, which makes it extremely expensive to obtain the complete network state information, and transmission delays and measurement errors, which make it impossible to know the exact network state. With wireless networks become pervasive in our daily life, new theories and algorithms are needed for partially observable wireless networks.In this project, the PI models a partially observable wireless network as a partially observable Markov process, and then applies the framework of Markov decision processes (MDP). While important structure properties may be discovered using the MDP framework, finding optimal solutions in general is an NP-hard problem. To overcome this difficulty, this project uses drift-based competitive analysis and drift-based large-deviations analysis for quantifying fundamental limits and deriving optimal or near optimal algorithms. The project is expected to lead to breakthroughs in managing partially observable wireless networks. Fundamental limits of partially observable wireless networks, novel resource allocation algorithms with provable throughput and latency guarantees, and implementations on a real-world test bed will have a significant impact on the design and implementation of future wireless networks.