Fair Computation Offloading for RSMA-Assisted Mobile Edge Computing Networks
Ding Xu, Lingjie Duan, Haitao Zhao, Hongbo Zhu

TL;DR
This paper proposes a novel RSMA-assisted MEC system that optimizes fairness among devices through a joint resource allocation framework, employing advanced optimization techniques to improve computation offloading performance.
Contribution
It introduces a new fairness-oriented resource allocation scheme for RSMA-assisted MEC systems with multiple servers and channels, including a hypergraph matching approach.
Findings
Proposed algorithm achieves near-optimal fairness in computation offloading.
System outperforms existing MEC systems in simulation scenarios.
Joint optimization improves resource utilization and fairness.
Abstract
Rate splitting multiple access (RSMA) provides a flexible transmission framework that can be applied in mobile edge computing (MEC) systems. However, the research work on RSMA-assisted MEC systems is still at the infancy and many design issues remain unsolved, such as the MEC server and channel allocation problem in general multi-server and multi-channel scenarios as well as the user fairness issues. In this regard, we study an RSMA-assisted MEC system with multiple MEC servers, channels and devices, and consider the fairness among devices. A max-min fairness computation offloading problem to maximize the minimum computation offloading rate is investigated. Since the problem is difficult to solve optimally, we develop an efficient algorithm to obtain a suboptimal solution. Particularly, the time allocation and the computing frequency allocation are derived as closed-form functions of…
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
TopicsIoT and Edge/Fog Computing · Advanced Wireless Communication Technologies · Age of Information Optimization
