Collaborative Research: NSF-AoF: CNS Core: Small: Towards Scalable and Al-based Solutions for Beyond-5G Radio Access Networks

合作研究：NSF-AoF：CNS 核心：小型：面向超 5G 无线接入网络的可扩展和基于人工智能的解决方案

基本信息

批准号：
2225577
负责人：
Taejoon Kim
金额：
$ 28.5万
依托单位：
University of Kansas Center for Research Inc
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2023
资助国家：
美国
起止时间：
2023-01-01 至 2025-12-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2225577&HistoricalAwards=false
关键词：
Collaborative Research NSF AoF CNS

项目摘要

Over the last few years, discussions oriented toward defining sixth generation (6G) requirements and possible technologies have started to circulate within the wireless community. One of the key ideas will likely be to take steps to remove the conventional cell boundaries and facilitate enhanced joint uplink and downlink processing using many dispersed access points (APs). These ideas fall within the academic definition of cell-free massive multiple-input multiple-output (CFmMIMO). It alleviates the existing cell-edge and handover problems and improves energy efficiency. The primary limiting factor is achieving cell-free operation in a practically feasible way, with computational complexity and fronthaul requirements that are scalable to large networks with many users. This poses many important research questions that must be explored systematically and in-depth. This project firstly develops scalable artificial intelligence (AI)-based solutions. Together with the appropriate (cost-efficient) AP deployment planning tools (e.g., where to put the APs), these developments constitute a significant step toward enabling the low-latency and uniformly reliable wireless services at a lower cost. Given the international nature of the project, the project contributes to the development of a diverse workforce in AI and 6G wireless networks through the formation of international research teams integrating undergraduate and graduate students. Project research activities are organized into three thrusts. Thrust 1 develops scalable AI-based resource allocation solutions enabling the implementation of large-scale CFmMIMO. The developed solutions are further enhanced by exploring AI architectures applicable to large networks. This includes the security aspects, especially in the context of AI algorithms and architecture, and the cloud radio access network. Thrust 2 focuses on establishing network planning and waveform constraints to address scalable deployment solutions. This includes the development of infrastructure-aware minimum-cost AP deployment methodologies by taking into account the QoS requirements and available transport infrastructure. The developed methodologies are further augmented by developing a network-wide user signal detection method, accounting for the fronthaul capacity and the quantization resolution at each AP. This task also investigates how CFmMIMO can address many of today’s most challenging spectrum policy issues. Evaluation Thrust evaluates and analyzes the methodologies developed in Thrusts 1&2. This employs the existing US and European experimental testbeds and provides a continuous feedback cycle between theory and experimentation. The US team will build upon the prior experience with Colosseum. On the European side, the team will experiment with the Open Air Interface (OAI).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.

在过去几年中，无线社区内针对定义第六代 (6G) 要求和可能技术的讨论已经开始进行彻底改革，其中一个关键想法可能是采取措施消除传统的小区边界并促进增强的联合上行链路。这些想法属于无小区大规模多输入多输出（CFmMIMO）的学术定义，它缓解了现有的小区边缘和切换问题并提高了主要能源效率。限制因素正在以一种实际可行的方式实现无小区操作，其计算复杂性和前传要求可扩展到具有许多用户的大型网络，这提出了许多必须系统和深入探索的重要研究问题。基于智能 (AI) 的解决方案与适当的（经济高效的）AP 部署规划工具（例如，AP 的放置位置）一起，是朝着实现低延迟且一致可靠的无线服务迈出的重要一步。成本更低。鉴于该项目的国际性质，该项目通过组建整合本科生和研究生的国际研究团队，促进人工智能和 6G 无线网络领域多元化劳动力的发展。项目研究活动分为三个重点。通过探索适用于大型网络的人工智能架构，进一步增强了基于人工智能的资源分配解决方案，特别是在人工智能算法和架构以及云无线电方面。接入网络。 Thrust 2 侧重于建立网络规划和波形约束，以解决可扩展的部署解决方案，这包括通过考虑 QoS 要求和可用的传输基础设施来开发基础设施感知的最低成本 AP 部署方法。该任务还研究了 CFmMIMO 如何解决当今许多最具挑战性的频谱政策问题。推论 1 和 2 中开发的方法采用了现有的美国和欧洲实验测试平台，并在理论和实验之间提供了持续的反馈循环。在欧洲方面，该团队将进行实验。开放空中接口 (OAI)。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。