RINGS: Intelligent and Resilient Virtualization of Massive MIMO Physical Layer

RINGS：大规模 MIMO 物理层的智能、弹性虚拟化

• 批准号: 2147946
• 负责人: Lin Zhong
• 金额: $ 99.99万
• 依托单位: Yale University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-05-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2147946&HistoricalAwards=false
• 关键词: RINGS; Intelligent; Resilient; Virtualization; Massive

NextG network systems rely on virtualization to move away from specialized, dedicated equipment to cloud and edge datacenters, to reduce cost and accelerate innovation. So far such virtualization efforts have met with very limited success, making inroads largely with 4G/LTE small cells. This is because 5G and beyond employ compute-intensive technologies such as massive multiple-input, multiple output (MIMO) and low-density parity-check (LDPC) code to deliver the unprecedented network performance. Massive MIMO not only demands massive computational power itself, but also proportionally increases that of LDPC. Not surprisingly, existing commercial massive MIMO solutions all rely on specialized, dedicated hardware such as FPGA and application-specific integrated circuits. Massive MIMO remains the largest barrier toward virtualized mobile networks. The goal of the proposed project is to overcome this technical barrier and virtualize the massive MIMO physical layer for NextG network systems. In doing so, the project will expedite the adoption of massive MIMO, resulting in more capable, more efficient, and more cost-effective mobile networks. Through our ongoing collaborations with industry leaders, the project will timely transfer technologies into practice. It also provides a meeting ground for software systems and wireless communication research and creates timely content for teaching Computer Science majors about the wireless physical layer. The project will provide a platform to engage undergraduate students and high-school students in computing research, especially women and underrepresented minorities.The project targets the following scientific contributions. (1) Design and implementation of the massive MIMO physical layer that scales up on a many-core server efficiently and intelligently. We will combine the efficiency of static and elasticity of dynamic task scheduling and devise latency-driven, automated schemes for optimal resource provisioning. (2) Distributed design and implementation that can utilize compute resources integrated over a local-area network, beyond a single server. We will leverage programmable switches to minimize the impact of the network and to utilize commodity servers as well as accelerators to achieve scale, cost effectiveness and energy efficiency beyond the reach of a single many-core server. (3) Elastic design and implementation that match up to dynamics in mobile network workload, simultaneously achieving high resilience, low cost for the network operator, and high utilization for the cloud provider, in a multi-tenant environment. We will explore serverless computing and develop it further to better meet the stringent latency requirement of the massive MIMO physical layer.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.

NextG网络系统依靠虚拟化从专门的专用设备转移到云和边缘数据中心，以降低成本和加速创新。到目前为止，这样的虚拟化工作已经取得了非常有限的成功，这在很大程度上与4G/LTE的小细胞相连。这是因为5G及以后采用了计算密集型技术，例如大量多输入，多重输出（MIMO）和低密度均衡检查（LDPC）代码来提供前所未有的网络性能。大规模的MIMO不仅需要大量的计算能力本身，而且还需要按比例增加LDPC的计算能力。毫不奇怪，现有的商业大型MIMO解决方案都依赖于专业的专用硬件，例如FPGA和特定于应用程序的集成电路。大型MIMO仍然是虚拟化移动网络的最大障碍。拟议项目的目的是克服这一技术障碍，并为NextG网络系统虚拟化大规模的MIMO物理层。通过这样做，该项目将加快采用大量的MIMO，从而产生更有能力，更高效，更具成本效益的移动网络。通过我们与行业领导者进行的持续合作，该项目将及时将技术转移到实践中。它还为软件系统和无线通信研究提供了一个会议场，并创建了及时的内容，以教授有关无线物理层的计算机科学专业。该项目将为本科生和高中生参与计算研究，尤其是妇女和代表性不足的少数民族的平台。该项目针对以下科学贡献。 （1）设计和实现大量的MIMO物理层，该物理层有效，智能地在多核服务器上扩展。我们将结合动态任务调度的静态和弹性的效率，并设计以延迟驱动的自动化方案来进行最佳资源提供。 （2）分布式设计和实现，可以利用通过单个服务器以外的本地区域网络集成的计算资源。我们将利用可编程开关来最大程度地减少网络的影响，并利用商品服务器以及加速器来实现单个多核服务器范围的规模，成本效益和能源效率。 （3）与移动网络工作负载中的动态相匹配的弹性设计和实现，同时实现了高弹性，网络运营商的低成本以及在多租户环境中对云提供商的高利用率。我们将探索无服务器计算并进一步开发它，以更好地满足大型MIMO物理层的严格潜伏期需求。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子和更广泛影响的评估评估评估的评估来支持的。

项目成果

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• 发表时间: 2024-04
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Prefetching Using Principles of Hippocampal-Neocortical Interaction

• DOI: 10.1145/3593856.3595901
• 发表时间: 2023-06
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Karma: Resource Allocation for Dynamic Demands

• DOI: 10.48550/arxiv.2305.17222
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