CIF: Small: Collaborative Research: Optimal Provision of Backhaul and Radio Access Networks: A Cross-Network Approach

CIF：小型：协作研究：回程和无线接入网络的优化配置：跨网络方法

• 批准号: 1813090
• 负责人: Mingyi Hong
• 金额: $ 8.97万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-28 至 2020-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1813090&HistoricalAwards=false
• 关键词: CIF; Small; Collaborative; Research; Optimal

The explosive growth in the number of smart consumer devices leads to projections that within 10 years' time, wireless cellular networks need to offer 1000x throughput increase over the current 4G technology. By that time the network should be able to deliver fiber-like user experience boasting 10 Gb/s individual transmission rate for data intensive cloud-based applications. To move such a huge amount of data from the network to the users' handheld devices in real time, revolutionary network infrastructure and advanced network provision are required. Two key enablers of the envisioned future mobile networks are the ultra-dense deployment of base stations and centralized cloud-based processing. This project addresses the challenging problem of managing such densely deployed, cloud-based radio access networks.The proposed research includes the introduction of a unified cross-network framework to manage a cloud-based radio access network. Important aspects of resource management in different sub-networks, including the backhaul and the cloud networks, will be considered. The project focuses on providing theoretical insights as well as designing practical algorithms for the optimal provisioning of a cloud-based radio access network. Fundamental computational issues of key cross-network resource management tasks will be investigated, revealing their intrinsic complexity. Moreover, practical schemes capable of optimally utilizing resources across networks will be developed, using cross-network optimization formulations. These algorithms will be optimized to fully exploit the computational resources offered by the cloud centers, addressing key issues such as parallel/distributed implementation, asynchronous computation, and load balancing. The goal is to determine how computational resources should be deployed through the proposed cross-network framework to dramatically improve the performance of a cloud-based radio access network.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

智能消费设备数量的爆炸性增长导致人们预测，在 10 年内，无线蜂窝网络的吞吐量需要比当前 4G 技术提高 1000 倍。到那时，网络应该能够为数据密集型云应用程序提供类似光纤的用户体验，并拥有 10 Gb/s 的单独传输速率。为了将如此大量的数据从网络实时转移到用户的手持设备，需要革命性的网络基础设施和先进的网络供应。设想的未来移动网络的两个关键推动因素是基站的超密集部署和基于云的集中处理。该项目解决了管理此类密集部署的基于云的无线电接入网络的挑战性问题。拟议的研究包括引入统一的跨网络框架来管理基于云的无线电接入网络。将考虑不同子网中资源管理的重要方面，包括回程和云网络。该项目的重点是提供理论见解以及设计实用算法，以实现基于云的无线电接入网络的最佳配置。将研究关键跨网络资源管理任务的基本计算问题，揭示其内在的复杂性。此外，将使用跨网络优化公式开发能够跨网络优化利用资源的实用方案。这些算法将经过优化，充分利用云中心提供的计算资源，解决并行/分布式实现、异步计算和负载平衡等关键问题。目标是确定如何通过拟议的跨网络框架部署计算资源，以显着提高基于云的无线电接入网络的性能。该奖项反映了 NSF 的法定使命，并通过使用基金会的评估进行评估，认为值得支持。智力价值和更广泛的影响审查标准。