Generalized Radio Environment Monitoring for Next Generation Wireless Networks

Abstract

Enabling technologies of 5G and beyond wireless communication networks, such as millimeter-wave communication, beamforming, and multiple-input multiple-output (MIMO) antenna systems, are becoming increasingly dependent on accurate information of the physical environment for optimized communication performance. The acquisition of this information is a significant challenge, which can be eased by knowledge of the radio environment. Radio environment mapping (REM) has long been considered an enabler of cognitive radios (CRs). However, the limitations of radios effectively confined the application of REM to spectrum sensing and interference mapping. With the advent of more capable software-defined radios and advanced networks, the idea of a truly intelligent communication system empowered by enhanced REM can be realized. To this effect, we propose the generalized radio environment monitoring (G-REM) concept to include all aspects of the radio environment. We outline a general, self contained framework which enables radio environment monitoring in standalone devices. The presented G-REM framework comprises of different information sources, sensing methods, sensing modes, and mapping techniques to enable the realization of more reliable, secure, efficient, and faster future wireless networks. The accompanying challenges and future research direction are also provided.

Gaussian mixture model based radio environment mapping for an underlay Device‐to‐Device network

“…7 Additionally, and more specifically in the case of cognitive radio (CR) networks, it may also contain information pertaining to primary transmitter locations and the corresponding spectrum access policies for the secondary users. Initially envisioned to provide a better coverage estimate for television broadcasting to empower TV white space networks, 8 it was later adopted to empower other CR applications like spectrum occupancy modeling and measurement, 9 resource allocation 10 and channel characterization 11 and so on. Currently, a significant variety of contemporary and upcoming use-cases are being catered to by REMs for example, 5G and IoT network optimization, 12,13 wireless resource allocation, 14 cooperative communication, 15 transmitter localization, 16 UAV based access point placement, 17 network diagnostics, 18 Multi-hop routing, 19 and military applications.…”

6G Vision: An Ultra-Flexible Perspective

“…However, the use of sensing is not limited to V2X or autonomous driving. Rather, if there is any observable data that can be utilized for the optimization or enhancement of the communications systems, it should be leveraged in 6G [73]. The information pertaining to the radio environment can be utilized in improving the network deployment, optimizing user association, providing secure communication and so on.…”