CNS Core: Small: Network Wide Sensing by Leveraging Cellular Communication Networks

5G通信网络密集部署，数据速率更高，覆盖范围更广。5G系统中使用的高频频段更容易受到环境的影响，如雨衰、阻塞、反射、风引起的收发器位移等。通信信号对环境的敏感性有利于传感任务：环境对通信信号的影响也传递给通信接收器，从中可以推断环境的信息。当基站或用户设备能够采集到通信信号所携带的全部环境信息时，通信网络就可以对这些信息进行推断，从而对环境进行监测。5G网络凭借其大带宽、广域覆盖、超密集部署、海量天线和网络切片等特点，进一步增强了4G蜂窝网络无法实现的传感能力。该研究为广域传感提供了一个平台，在现有通信基础设施的基础上增加了边际成本，有利于交通监控、天气监测、土木工程等各种应用。通信信号除了向接收器传递信息外，还可以照亮各种目标和区域。它节省了频率带宽和传输功率，利用通信信号进行传感。为此，确定了通信和感知之间的信息论权衡，从而提供了性能界限。然后，根据通信信号的特点，设计了环境成像和天气监测（包括测风和降水监测）的传感算法。通过结合各种实际问题，设计了传感协议。它们主要包括信令机制和软件定义感知，利用5G（或更高）网络中的网络功能虚拟化、网络切片和多址边缘计算。最后，在硬件和软件测试平台上对所提出的传感、信令和计算算法进行了评估。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。

5G communication networks are densely deployed to provide a higher data rate and wider coverage. The high-frequency bands used in 5G systems are more susceptible to the environment, such as rain fade, blockage, reflections, and transceiver displacement due to wind. The sensitivity of communication signals to the environment could benefit the task of sensing: the impact of the environment on the communication signal is also delivered to the communication receiver, from which the information of the environment can be inferred. When all the environmental information carried by the communication signal can be gleaned by base stations or user equipment, the communication network can infer the information and thus monitor the environment. The 5G networks further enhance the capability of sensing that cannot be achieved by 4G cellular networks, due to the features of large bandwidth, wide-area coverage, ultra-dense deployment, massive antennas, and network slicing. The proposed research serves as a platform for wide-area sensing, with a marginal cost added to existing communication infrastructure, which benefits various applications, such as traffic surveillance, weather monitoring, civil engineering, et al.Communication signals illuminate various targets and regions, besides conveying information to receivers. It saves frequency bandwidth and transmit power to leverage the communication signal for sensing. To this end, the information-theoretic trade-off between communications and sensing is identified, which provides performance bounds. Then, sensing algorithms are designed, including environment imaging and weather monitoring (including wind gauge and precipitation monitoring), based on the characteristic of communication signals. By incorporating various practical concerns, sensing protocols are devised. They mainly consist of the mechanism of signaling and the software-defined sensing using the network function virtualization, network slicing, and multiaccess edge computing in 5G (or beyond) networks. Finally, the proposed algorithms of sensing, signaling, and computing are evaluated in both hardware and software testbeds.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.