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

密集部署5G通信网络，提供更高的数据速率和更广的覆盖范围。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、反射和收发机因风而移动。通信信号对环境的敏感性可以帮助感知任务：环境对通信信号的影响也被传递到通信接收器，从通信接收器可以推断环境的信息。当基站或用户设备可以收集到通信信号携带的所有环境信息时，通信网络可以推断该信息，从而对环境进行监测。5G网络由于具有大带宽、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感知能力。该研究为广域传感提供了一个平台，增加了现有通信基础设施的边际成本，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者传递信息外，还可以照亮各种目标和区域。它节省了频率带宽和发射功率，以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，这提供了性能界限。然后根据通信信号的特点，设计了包括环境成像和天气监测(包括测风仪和降雨量监测)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5G(或更高)网络中的信令机制和使用网络功能虚拟化、网络切片和多路访问边缘计算的软件定义的感知。最后，建议的感知、信令和计算算法在硬件和软件测试平台上进行了评估。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.