A Fundamental Study on Energy Efficient Wireless Communication Networks: Modeling, Algorithms, and Applications

节能无线通信网络的基础研究：建模、算法和应用

• 批准号: 1610874
• 负责人: Yu Cheng
• 金额: $ 38万
• 依托单位: Illinois Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-08-01 至 2020-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1610874&HistoricalAwards=false
• 关键词: Fundamental; Study; Energy; Efficient; Wireless

The rapid development and wide deployment of wireless networks incur a fast escalation of energy demand, which eagerly calls for energy-efficient networking techniques. At the same time, wireless networks are evolving into complex forms with multi-dimensional resources including communication link, radio, channel, antenna, and transmit power; algorithms with low complexity for energy efficiency optimization are highly demanded. This project targets at a fundamental study on energy-efficient wireless networking through establishment of a uniformed analytical framework, development of efficient and low-complexity algorithms, and application of the generic studies into important scenarios in the fifth generation (5G) cellular systems. This interdisciplinary research will not only provide various training projects to undergraduate and graduate studies, but also inspire students to pursue high-quality research with a creative, open-minded, and cross-disciplinary perspective. This project is going to demonstrate that a uniformed multidimensional optimization framework for energy efficiency optimization can be constructed by the principle of scheduling proper transmission patterns, which are defined by the interference model of the network. With such a uniformed optimization model, low-complexity decomposition techniques are fundamentally related to a maximum weighted transmission pattern (MWTP) problem, under a physical interference model according to the signal-to-interference-plus-noise ratio. Approximation algorithms and associated performance analysis for the MWTP problem (which is NP-hard in general) are critical research issues to be studied. Distributed algorithms for solving the energy efficiency optimization problem further involves decomposition with multi-objective optimization, and innovative Lyapunov function design and associated stability analysis under the physical interference model, which will also be addressed in this project. Energy efficient solutions in a couple of important 5G cellular scenarios will be enabled through innovative modeling and algorithms in the uniformed multidimensional framework, including joint optimization that incorporates massive MIMO interference mitigation with flow constraint at network layer and base station sleeping at system level, formulation and algorithm development for a MWTP problem under the massive MIMO interference model, and modeling of the interplay between massive MIMO and device-to-device communications. In this project, the proposed research seamlessly integrates studies in the areas of optimization, graph theory, dual decomposition, approximation algorithms, and wireless communication and networking. The research outcomes are expected to provide important guidance for the development of the 5G cellular systems.

无线网络的快速发展和广泛部署导致能源需求快速上升，迫切需要节能的网络技术。与此同时，无线网络正在向复杂形态演进，拥有通信链路、无线、信道、天线、发射功率等多维资源；能源效率优化的低复杂度算法的需求量很大。该项目旨在通过建立统一的分析框架、开发高效且低复杂度的算法以及将通用研究应用于第五代（5G）蜂窝系统的重要场景，对节能无线网络进行基础研究。这种跨学科研究不仅将为本科生和研究生提供各种培养项目，还将激发学生以创造性、开放性和跨学科的视角进行高质量的研究。该项目将证明，可以通过调度适当的传输模式（由网络干扰模型定义）的原则来构建用于能源效率优化的统一多维优化框架。通过这种统一的优化模型，在根据信号干扰加噪声比的物理干扰模型下，低复杂度分解技术从根本上与最大加权传输模式（MWTP）问题相关。 MWTP 问题（一般是 NP 难问题）的近似算法和相关性能分析是需要研究的关键研究问题。解决能效优化问题的分布式算法进一步涉及多目标优化分解，以及物理干扰模型下创新的Lyapunov函数设计和相关稳定性分析，这些也将在本项目中得到解决。通过统一多维框架中的创新建模和算法，将在几个重要的 5G 蜂窝场景中实现节能解决方案，包括将大规模 MIMO 干扰抑制与网络层流量约束和系统级基站休眠相结合的联合优化、大规模 MIMO 干扰模型下的 MWTP 问题的制定和算法开发，以及大规模 MIMO 之间相互作用的建模。 MIMO 和设备到设备通信。在该项目中，所提出的研究无缝集成了优化、图论、对偶分解、近似算法以及无线通信和网络领域的研究。 研究成果有望为5G蜂窝系统的发展提供重要指导。