Coordinating Communication and Computing for Wireless VR in Open Radio Access Networks

Driven by diverse applications, radio access networks (RAN) are expected to embrace built-in computing and intelligence, forming a versatile wireless computing platform that closely integrates communication and computing. To fully unleash the potential of such a synergistic system, it is essential to coordinate communication and computing with intelligence unlocked by the radio intelligent controllers (RICs) in O-RAN. Building on the groundwork established by existing theoretical studies and simulations, we develop a platform that can emulate the events in the real-world system in more detail, bringing theoretical works closer to practical implementation. In this paper, we first introduce <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ns-GP-O-RAN</i>, a software simulation platform developed over ns-3, enabling communication, computation task processing, large-scale data collection, and testing of system-level orchestration policies through user-level control. Taking virtual reality (VR) as an example, we formulate the computation offloading problem and develop a prediction-based computation offloading xAPP, which contains a prediction phase to predict users’ end-to-end (E2E) performance with the deep neural network and a system-level decision-making phase for global orchestration with the differential evolution algorithm. We evaluate the system capacity and E2E latency over the developed ns-GP-O-RAN, which is more effective than existing approaches.

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Publication Details

Journal
IEEE Transactions on Mobile Computing
Published
2025-02-10
DOI
https://doi.org/10.1109/tmc.2025.3540111
Citations
1
Primary Topic
Cloud Computing and Remote Desktop Technologies
Type
article
Field-Weighted Citation Impact
2.27
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article

Coordinating Communication and Computing for Wireless VR in Open Radio Access Networks

Yaohua Sun, Ziqi Chen, Mugen Peng, Yuanwei Liu et al.
1 citations
IEEE Transactions on Mobile Computing
Cloud Computing and Remote Desktop Technologies
2.27
article

Coordinating Communication and Computing for Wireless VR in Open Radio Access Networks

Yaohua Sun, Ziqi Chen, Mugen Peng, Yuanwei Liu, Fengxian Guo, Hongtao Li, Nan Li
article en
1 citations

Abstract

Driven by diverse applications, radio access networks (RAN) are expected to embrace built-in computing and intelligence, forming a versatile wireless computing platform that closely integrates communication and computing. To fully unleash the potential of such a synergistic system, it is essential to coordinate communication and computing with intelligence unlocked by the radio intelligent controllers (RICs) in O-RAN. Building on the groundwork established by existing theoretical studies and simulations, we develop a platform that can emulate the events in the real-world system in more detail, bringing theoretical works closer to practical implementation. In this paper, we first introduce <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ns-GP-O-RAN</i>, a software simulation platform developed over ns-3, enabling communication, computation task processing, large-scale data collection, and testing of system-level orchestration policies through user-level control. Taking virtual reality (VR) as an example, we formulate the computation offloading problem and develop a prediction-based computation offloading xAPP, which contains a prediction phase to predict users’ end-to-end (E2E) performance with the deep neural network and a system-level decision-making phase for global orchestration with the differential evolution algorithm. We evaluate the system capacity and E2E latency over the developed ns-GP-O-RAN, which is more effective than existing approaches.

IEEE Transactions on Mobile ComputingVol. 24(7)
Beijing University of Posts and Telecommunications (CN), China Mobile (China) (CN), University of Hong Kong (HK)
Openalex Percentile: Top 18%
Cloud Computing and Remote Desktop Technologies
2.27
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