When Wireless Communications Meet Computer Vision in Beyond 5G

Abstract

This article articulates the emerging paradigm, sitting at the confluence of computer vision and wireless communication, enabling beyond-5G/6G mission-critical applications (autonomous/ remote-controlled vehicles, visuo-haptic virtual reality, and other cyber-physical applications). First, drawing on recent advances in machine learning and the availability of non-radio-frequency (RF) data, vision-aided wireless networks have been shown to significantly enhance wireless communication reliability without sacrificing spectral efficiency. In particular, we demonstrate how computer vision enables look-ahead prediction in a millimeter-wave channel blockage scenario before the blockage actually occurs. From a computer vision perspective, we highlight how RF-based sensing and imaging are instrumental in robustifying computer vision applications against occlusion and failure. This is corroborated via an RF-based image reconstruction use case, showcasing a receiver-side image failure correction resulting in reduced retransmission and latency. Taken together, this article sheds light on the much needed convergence of RF and non-RF modalities to enable ultra-reliable communication and truly intelligent 6G networks.