When Wireless Communications Meet Computer Vision in Beyond 5G

• URL: http://arxiv.org/abs/2010.06188v1
• Date: Tue, 13 Oct 2020 05:25:35 GMT
• Title: When Wireless Communications Meet Computer Vision in Beyond 5G
• Authors: Takayuki Nishio, Yusuke Koda, Jihong Park, Mehdi Bennis, Klaus Doppler
• Abstract summary: This article articulates the emerging paradigm, sitting at the confluence of computer vision and wireless communication. From a computer vision perspective, we highlight how radio frequency (RF) based sensing and imaging are instrumental in robustifying computer vision applications. 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.
• Score: 43.95612222496595
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This article articulates the emerging paradigm, sitting at the confluence of computer vision and wireless communication, to enable beyond-5G/6G mission-critical applications (autonomous/remote-controlled vehicles, visuo-haptic VR, and other cyber-physical applications). First, drawing on recent advances in machine learning and the availability of non-RF data, vision-aided wireless networks are shown to significantly enhance the reliability of wireless communication 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 happens. From a computer vision perspective, we highlight how radio frequency (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.

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