Wireless Channel Dynamics for Relay Selection under Ultra-Reliable Low-Latency Communication

Ultra-reliable, low-latency communication (URLLC) is being developed to support critical control applications over wireless networks. Exploiting spatial diversity through relays is a promising technique for achieving the stringent requirements of URLLC, but coordinating relays reliably and with low overhead is a challenge. Adaptive relay selection techniques have been proposed as a way to simplify implementation while still achieving the requirements of URLLC. Identifying good relays with low overhead and high confidence is critical for such adaptive relay selection techniques.Channel dynamics must be taken into account by adaptive relay selection algorithms because channel quality may degrade in the time it takes to estimate the relay's channel and schedule a transmission. Spatial channel dynamics are well studied in many settings such as RADAR and the fast-fading wireless channels, but less so in the URLLC context where rare events neglected in other models may be important. In this work, we perform measurements to validate channel models in the slow fading regime of interest. We compare measurements to Jakes's model and discuss the appropriateness of Jakes's model for URLLC relay selection. This is further applied to demonstrate that easily implementable relay selection techniques perform well in practical settings.Polynomial interpolation and neural-net-based algorithms were evaluated as channel prediction algorithms. These techniques perform orders of magnitude better than relay selection on average (nominal) SNR.