WiserVR: Semantic Communication Enabled Wireless Virtual Reality Delivery
Le Xia, Yao Sun, Chengsi Liang, Daquan Feng, Runze Cheng, Yang Yang,, and Muhammad Ali Imran

TL;DR
WiserVR introduces a semantic communication framework for wireless VR that reduces latency and enhances reliability by leveraging deep learning and joint semantic-channel coding, enabling efficient delivery of 360-degree videos.
Contribution
This work presents a novel semantic communication framework for wireless VR, utilizing deep learning modules and joint coding to improve transmission efficiency and robustness.
Findings
Significant latency reduction demonstrated in simulations.
Enhanced reliability under various channel conditions.
Effective semantic feature extraction for VR video delivery.
Abstract
Virtual reality (VR) over wireless is expected to be one of the killer applications in next-generation communication networks. Nevertheless, the huge data volume along with stringent requirements on latency and reliability under limited bandwidth resources makes untethered wireless VR delivery increasingly challenging. Such bottlenecks, therefore, motivate this work to seek the potential of using semantic communication, a new paradigm that promises to significantly ease the resource pressure, for efficient VR delivery. To this end, we propose a novel framework, namely WIreless SEmantic deliveRy for VR (WiserVR), for delivering consecutive 360{\deg} video frames to VR users. Specifically, deep learning-based multiple modules are well-devised for the transceiver in WiserVR to realize high-performance feature extraction and semantic recovery. Among them, we dedicatedly develop a concept of…
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Taxonomy
TopicsTelecommunications and Broadcasting Technologies · Wireless Signal Modulation Classification · Wireless Body Area Networks
