Extended Reality via Cooperative NOMA in Hybrid Cloud/Mobile-Edge Computing Networks
Robert-Jeron Reifert, Hayssam Dahrouj, Aydin Sezgin

TL;DR
This paper proposes a cooperative NOMA scheme in a hybrid cloud and edge computing network to enhance XR applications by optimizing resource allocation, link selection, and fairness, demonstrating improved performance over traditional methods.
Contribution
It introduces a novel cooperative NOMA framework for XR in hybrid cloud/edge networks, with an optimization approach for resource and link management that is practically implementable.
Findings
Improved log-rate performance and delay sensitivity.
Enhanced scalability and runtime efficiency.
Practical distributed implementation benefits.
Abstract
Extended reality (XR) applications often perform resource-intensive tasks, which are computed remotely, a process that prioritizes the latency criticality aspect. To this end, this paper shows that through leveraging the power of the central cloud (CC), the close proximity of edge computers (ECs), and the flexibility of uncrewed aerial vehicles (UAVs), a UAV-aided hybrid cloud/mobile-edge computing architecture promises to handle the intricate requirements of future XR applications. In this context, this paper distinguishes between two types of XR devices, namely, strong and weak devices. The paper then introduces a cooperative non-orthogonal multiple access (Co-NOMA) scheme, pairing strong and weak devices, so as to aid the XR devices quality-of-user experience by intelligently selecting either the direct or the relay links toward the weak XR devices. A sum logarithmic-rate…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Wireless Communication Technologies · UAV Applications and Optimization · IoT and Edge/Fog Computing
