Collaborative Research: CNS Core: Medium: Softwarizing Millimeter-wave Radio Access Networks (RANs) at the Edge

增强现实、联网自动驾驶汽车和工业物联网系统中的新兴应用对下一代移动网络提出了苛刻的要求，仅靠 7 GHz 以下的无线电资源很难满足这些要求。因此，5G 及其他网络已经采用了在毫米波 (mmWave) 频段运行的无线电，该频段在全球范围内提供 25 倍或更多的带宽。另一方面，毫米波无线电网络需要密集部署基础设施节点才能实现理想的覆盖范围，因为毫米波无线电信号传播损耗较高，并且容易受到阻塞和移动性的影响。不幸的是，毫米波基础设施节点（例如 5G 中的 gNodeB）是由专门的专用硬件制成的，因此，它们的密集部署将产生巨大的资本和运营成本。该项目的目标是通过软件化无线接入网络（RAN）功能并从靠近最终用户的数据中心（即边缘数据中心）为其提供服务来降低毫米波无线基础设施节点的成本，从而促进网络致密化。更重要的是，它将实现以前不可能实现的网络实施和配置灵活性，以及​​跨网络和边缘数据中心的资源分配效率。在社会层面，该项目将推动移动网络虚拟化的持续革命，并加速下一代网络系统的开发和部署。解决与边缘毫米波 RAN 软件化相关的挑战的关键见解是利用毫米波基带及其固有结构内部的海量数据并行性，并在所有领域使用可编程硬件。该项目的目标是在三个相互关联的研究方向上做出以下科学贡献。 (i) 适用于边缘部署的商用服务器集群的毫米波物理层的低延迟软件实现。 (ii) 自适应 RAN 配置和网内压缩方案，可应对实践中有限的前传容量，而不会大幅增加毫米波基础设施节点的成本。 (iii) 基于用于通信的毫米波无线电信号的新颖传感和成像方案。其中包括使用单个毫米波基础设施节点进行传感，以及利用多个协调的毫米波节点来实现以前不可能的覆盖范围和分辨率。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点和更广泛的影响审查标准进行评估，被认为值得支持。

Emerging applications in augmented reality, connected autonomous vehicles, and industrial IoT systems impose demanding requirements on next-generation mobile networks that can hardly be met alone with radio resources below 7 GHz. Therefore, 5G and beyond networks have embraced radios operating in millimeter-wave (mmWave) frequency bands, which offer 25 times or more bandwidth worldwide. On the other hand, mmWave radio networks require the dense deployment of infrastructure nodes to achieve desirable coverage, because mmWave radio signals suffer from high propagation loss and are vulnerable to blockage and mobility. Unfortunately, mmWave infrastructure nodes, e.g., gNodeB in 5G, are made of specialized, dedicated hardware and as a result, their dense deployment would incur formidable capital and operational cost. The goal of the proposed project is to reduce the cost of mmWave radio infrastructure nodes by softwarizing their radio access network (RAN) functions and serving them from data centers close to end users, i.e., edge data centers, therefore facilitating network densification. More importantly, it will allow for previously impossible flexibility in network implementation and configuration as well as efficiency in resource allocation across the network and the edge data center. At the societal level, this project will fuel the ongoing revolution of mobile network virtualization and accelerate the development and deployment of next-generation network systems.The key insight toward addressing the challenges associated with softwarizing mmWave RANs at the edge is to exploit the massive data parallelism inside the mmWave baseband and its inherent structures, with programmable hardware in all domains. The project targets the following scientific contributions in three interrelated research thrusts. (i) A low-latency software realization of the mmWave physical layer for commodity server clusters suitable for edge deployment. (ii) Adaptive RAN configuration and in-network compression schemes that cope with the limited fronthaul capacity in practice, without substantially increasing the cost of mmWave infrastructure nodes. (iii) Novel sensing and imaging schemes based on mmWave radio signals intended for communications. These include sensing with a single mmWave infrastructure node and sensing that leverages multiple coordinated mmWave nodes to achieve previously impossible coverage and resolution.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.