Supun Karunarathna, Shalitha Wijethilaka, Pasika Ranaweera, Kasun T. Hemachandra, Tharaka Samarasinghe, Madhusanka Liyanage
Journal
IEEE Access , vol. 11 , pp. 25502-25530 · 2023 · Cited by 77
Mobile and Next-Generation NetworksNetwork Optimization and Intelligence
Abstract
Metaverse is the latest technological hype in the modern world due to its potential for revolutionizing the digital visual perspective. With the COVID-19 pandemic, most industries have moved towards digitization, and the metaverse is identified as one of the most promising platforms for such a transition, as it provides a three-dimensional (3D) immersive experience for the users. Currently, most digital service providers and organizations are actively working on metaverse- based applications. In addition, there has been a rapid increase on research work involving metaverse realization. Launching a large scale metaverse in the real world is a challenging task. However, fifth-generation (5G) and beyond 5G (B5G) technologies are envisioned to improve the feasibility of pragmatic deployments. Although, there are several conceptual designs available, actual adaptations of the concepts are still limited. This survey …
Chamath Divarathne, Tharaka Samarasinghe, Sithamparanathan Kandeepan, Ke Wang
Conference
APCC 2023 28th Asia Pacific Conference on Communications (APCC) , pp. 279-284 · 2023 · Cited by 1
Wireless CommunicationsNetwork Optimization and Intelligence
Abstract
Dynamic spectrum access is recognized as a potential solution to the problem of spectrum scarcity. Consequently, a significant amount of research has been conducted on spectrum allocation. In this study, we present a multi-traffic class queue-based spectrum allocation solution. The proposed solution is designed for a scenario where communication and other systems do not necessarily require agility in the frequency bands they operate in. The spectrum sensing and forecasting processes are carried out over relatively long time periods compared to the actual transmission rates. The study considers two traffic classes: priority and non-priority. Three packet handling strategies are presented and their average queuing delay performances are compared. While all three strategies yield satisfactory results under low/medium traffic conditions, Strategy 3 exhibits the greatest flexibility in terms of delay performance …