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: 1526434
• 负责人: Zhi-Quan Luo
• 金额: $ 31万
• 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: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1526434&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.

智能消费设备数量的爆炸性增长导致预测，在10年内，无线蜂窝网络需要提供比当前4G技术高1000倍的吞吐量。到那时，网络应该能够为基于云的数据密集型应用提供光纤般的用户体验，拥有10 Gb/S的个人传输速率。要将如此海量的数据实时从网络传输到用户的手持设备上，需要革命性的网络基础设施和先进的网络配置。设想的未来移动网络的两个关键推动因素是基站的超高密度部署和基于云的集中式处理。该项目解决了管理这种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。将审议不同子网络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，以优化基于云的无线电接入网络的配置。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，还将利用跨网络优化公式，制定能够优化利用网络资源的实用方案。这些算法将进行优化，以充分利用云中心提供的计算资源，解决并行/分布式实施、异步计算和负载均衡等关键问题。目标是确定应如何通过拟议的跨网络框架部署计算资源，以显著提高基于云的无线电接入网络的性能。