RINGS: Intelligent and Resilient Virtualization of Massive MIMO Physical Layer

NextG网络系统依靠虚拟化技术，从专门的专用设备转移到云和边缘数据中心，以降低成本并加速创新。到目前为止，这种虚拟化努力只取得了非常有限的成功，主要是在4G/LTE小型蜂窝中取得进展。这是因为5G及以后采用大规模多输入多输出（MIMO）和低密度奇偶校验（LDPC）代码等计算密集型技术来提供前所未有的网络性能。大规模MIMO不仅需要大量的计算能力，而且还会按比例增加LDPC的计算能力。不足为奇的是，现有的商业大规模MIMO解决方案都依赖于专门的、专用的硬件，如FPGA和专用集成电路。大规模MIMO仍然是虚拟化移动网络的最大障碍。该项目的目标是克服这一技术障碍，并为NextG网络系统虚拟化大规模MIMO物理层。通过这样做，该项目将加速大规模MIMO的采用，从而产生更强大、更高效和更具成本效益的移动网络。通过我们与行业领导者的持续合作，该项目将及时将技术转化为实践。它还为软件系统和无线通信研究提供了一个交汇点，并为计算机科学专业的无线物理层教学创造了及时的内容。该项目将为本科生和高中生提供一个参与计算机研究的平台，尤其是女性和代表性不足的少数族裔。该项目的目标是做出以下科学贡献。(1)在多核服务器上高效智能扩展的大规模MIMO物理层的设计与实现。我们将结合静态任务调度的效率和动态任务调度的弹性，设计延迟驱动的自动化方案，以实现最优的资源配置。(2)分布式设计和实现，可以利用局域网上集成的计算资源，而不是单个服务器。我们将利用可编程交换机来最大限度地减少网络的影响，并利用商品服务器和加速器来实现单个多核服务器无法达到的规模、成本效益和能源效率。(3)弹性设计和实现，匹配移动网络工作负载的动态变化，同时在多租户环境中实现高弹性、网络运营商低成本和云提供商高利用率。我们将探索无服务器计算并进一步发展它，以更好地满足大规模MIMO物理层严格的延迟要求。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.