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Cooperative Caching, Rendering, and Beamforming for RIS-Assisted Wireless Virtual Reality Networks | IEEE Journals & Magazine | IEEE Xplore

Cooperative Caching, Rendering, and Beamforming for RIS-Assisted Wireless Virtual Reality Networks


Abstract:

Wireless virtual reality networks(WVRNs) provide seamless connectivity between virtual reality devices with colossal application and commercial value. However, the main p...Show More

Abstract:

Wireless virtual reality networks(WVRNs) provide seamless connectivity between virtual reality devices with colossal application and commercial value. However, the main problem restricting its development is the high energy and computational consumption in 3D video rendering on VR devices. To address this issue, we propose a novel coordinated multi-point (CoMP) and reconfigurable intelligent surfaces (RISs) assisted system, where the video is rendered by multiple collaborative mobile edge computing (MEC) servers simultaneously. Besides, BSs associated with these MEC servers are formed as a CoMP cluster to achieve a high data rate. This paper aims to minimize long-term power consumption by jointly optimizing the video caching and rendering at the MEC servers and the beamforming for both BSs and RIS. We propose an online, hybrid learning framework that combines deep reinforcement learning (DRL) for video caching and rendering, and an alternating optimization for the beamforming of all BSs and the RIS. In particular, the reward of each action in the DRL algorithm is calculated by the proposed alternating optimization problem, thus reducing the action space and accelerating convergence speed. Numerical results and comparison experiments show that our proposed method can effectively reduce the long-term average power consumption of the system, satisfy the requirement of 3D video transmission with low computational complexity, and outperform that without CoMP and RIS techniques.
Published in: IEEE Transactions on Vehicular Technology ( Volume: 73, Issue: 5, May 2024)
Page(s): 6845 - 6860
Date of Publication: 21 December 2023

ISSN Information:

Funding Agency:

Author image of Jian Chen
School of Computer Science and Engineering, Northeastern University, Shenyang, China
Engineering Research Center of Security Technology of Complex Network System, Ministry of Education, Shenyang, China
Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Shenyang, China
Jian Chen (Member, IEEE) received the Ph.D. degree in computer science and technology from Northeastern University, Shenyang, China, in 2010. He is currently a Professor with Northeastern University. In 2016, he was a Visiting Research Associate with King's College London, London, USA. His research interests include intelligent reconfigurable surface (IRS), D2D communication, and signal and image processing.
Jian Chen (Member, IEEE) received the Ph.D. degree in computer science and technology from Northeastern University, Shenyang, China, in 2010. He is currently a Professor with Northeastern University. In 2016, he was a Visiting Research Associate with King's College London, London, USA. His research interests include intelligent reconfigurable surface (IRS), D2D communication, and signal and image processing.View more
Author image of Jiale Xia
School of Computer Science and Engineering, Northeastern University, Shenyang, China
Engineering Research Center of Security Technology of Complex Network System, Ministry of Education, Shenyang, China
Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Shenyang, China
Jiale Xia received the B.S. degree with the School of Computer Science and Technology, Heilongjiang University, Harbin, China, in 2021. He is currently working toward the M.S. degree with the School of Computer Science and Engineering, Northeastern University, Shenyang, China. His research interests include energy-efficient communication, machine learning, and reconfigurable intelligent surface (RIS).
Jiale Xia received the B.S. degree with the School of Computer Science and Technology, Heilongjiang University, Harbin, China, in 2021. He is currently working toward the M.S. degree with the School of Computer Science and Engineering, Northeastern University, Shenyang, China. His research interests include energy-efficient communication, machine learning, and reconfigurable intelligent surface (RIS).View more
Author image of Jie Jia
School of Computer Science and Engineering, Northeastern University, Shenyang, China
Engineering Research Center of Security Technology of Complex Network System, Ministry of Education, Shenyang, China
Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Shenyang, China
Jie Jia (Member, IEEE) received the Ph.D. degree in computer science and technology from Northeastern University, Shenyang, China, in 2009. In 2016, she was a Visiting Research Associate with King's College London, London, U.K. She is currently a Professor with Northeastern University. She has authored or coauthored more than 100 technical papers on various aspects of wireless networks. Her research interests mainly inclu...Show More
Jie Jia (Member, IEEE) received the Ph.D. degree in computer science and technology from Northeastern University, Shenyang, China, in 2009. In 2016, she was a Visiting Research Associate with King's College London, London, U.K. She is currently a Professor with Northeastern University. She has authored or coauthored more than 100 technical papers on various aspects of wireless networks. Her research interests mainly inclu...View more
Author image of Leyou Yang
School of Computer Science and Engineering, Northeastern University, Shenyang, China
Engineering Research Center of Security Technology of Complex Network System, Ministry of Education, Shenyang, China
Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Shenyang, China
Leyou Yang received the B.S. and M.S. degrees in software engineering in 2015 and 2018, respectively, from Northeastern University, Shenyang, China, where he is currently working toward the Ph.D. degree in computer application technology with the School of Computer Science and Engineering. From 2021 to 2022, he was a Visiting Ph.D. Student with the School of Computer Science and Engineering, Nanyang Technological Universi...Show More
Leyou Yang received the B.S. and M.S. degrees in software engineering in 2015 and 2018, respectively, from Northeastern University, Shenyang, China, where he is currently working toward the Ph.D. degree in computer application technology with the School of Computer Science and Engineering. From 2021 to 2022, he was a Visiting Ph.D. Student with the School of Computer Science and Engineering, Nanyang Technological Universi...View more
Author image of Xingwei Wang
School of Computer Science and Engineering, Northeastern University, Shenyang, China
Engineering Research Center of Security Technology of Complex Network System, Ministry of Education, Shenyang, China
Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Shenyang, China
Xingwei Wang (Member, IEEE) received the B.S., M.S., and Ph.D. degrees in computer science from Northeastern University, Shenyang, China, in 1989, 1992, and 1998, respectively. He is currently a Professor with the School of Computer Science and Engineering, Northeastern University. He has authored or coauthored more than 100 journal articles, books and book chapters, and refereed conference papers. He was the recipient of...Show More
Xingwei Wang (Member, IEEE) received the B.S., M.S., and Ph.D. degrees in computer science from Northeastern University, Shenyang, China, in 1989, 1992, and 1998, respectively. He is currently a Professor with the School of Computer Science and Engineering, Northeastern University. He has authored or coauthored more than 100 journal articles, books and book chapters, and refereed conference papers. He was the recipient of...View more

I. Introduction

Virtual reality (VR) technology has been viewed as a promising solution for creating highly immersive virtual worlds and breaking geographical boundaries. The new features have endowed tremendous interest from various fields, such as treating mental diseases, manufacturing, education, sales, and consumer-oriented applications [1]. It is predicted that the market for the VR ecosystem will reach 80 billion by the end of 2025, which is almost the exact size of the desktop PC market nowadays [2]. However, the main disadvantage of recent VR technologies lies in the wired connection between VR users and servers. As a result, the mobility of VR users is severely constrained. To overcome this issue, VR devices with wireless connections have been proposed. As such, VR users can get rid of power and video transmission cables, thus bringing an immersive experience from anywhere at any time. However, it is worth pointing out that leveraging wireless technology for VR applications is still very challenging. First, due to the high resolution of 360-degree VR video, VR applications require significantly higher data rates than conventional data-orientated applications. According to the report by Qualcomm [3], the overall capacity requirement for VR applications can reach 22 Tbps, which can hardly be satisfied with existing wireless techniques. Besides, VR applications require low interaction latency and seamless connectivity to avoid VR vertigo [4], which poses a massive challenge for existing wireless networks.

Author image of Jian Chen
School of Computer Science and Engineering, Northeastern University, Shenyang, China
Engineering Research Center of Security Technology of Complex Network System, Ministry of Education, Shenyang, China
Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Shenyang, China
Jian Chen (Member, IEEE) received the Ph.D. degree in computer science and technology from Northeastern University, Shenyang, China, in 2010. He is currently a Professor with Northeastern University. In 2016, he was a Visiting Research Associate with King's College London, London, USA. His research interests include intelligent reconfigurable surface (IRS), D2D communication, and signal and image processing.
Jian Chen (Member, IEEE) received the Ph.D. degree in computer science and technology from Northeastern University, Shenyang, China, in 2010. He is currently a Professor with Northeastern University. In 2016, he was a Visiting Research Associate with King's College London, London, USA. His research interests include intelligent reconfigurable surface (IRS), D2D communication, and signal and image processing.View more
Author image of Jiale Xia
School of Computer Science and Engineering, Northeastern University, Shenyang, China
Engineering Research Center of Security Technology of Complex Network System, Ministry of Education, Shenyang, China
Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Shenyang, China
Jiale Xia received the B.S. degree with the School of Computer Science and Technology, Heilongjiang University, Harbin, China, in 2021. He is currently working toward the M.S. degree with the School of Computer Science and Engineering, Northeastern University, Shenyang, China. His research interests include energy-efficient communication, machine learning, and reconfigurable intelligent surface (RIS).
Jiale Xia received the B.S. degree with the School of Computer Science and Technology, Heilongjiang University, Harbin, China, in 2021. He is currently working toward the M.S. degree with the School of Computer Science and Engineering, Northeastern University, Shenyang, China. His research interests include energy-efficient communication, machine learning, and reconfigurable intelligent surface (RIS).View more
Author image of Jie Jia
School of Computer Science and Engineering, Northeastern University, Shenyang, China
Engineering Research Center of Security Technology of Complex Network System, Ministry of Education, Shenyang, China
Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Shenyang, China
Jie Jia (Member, IEEE) received the Ph.D. degree in computer science and technology from Northeastern University, Shenyang, China, in 2009. In 2016, she was a Visiting Research Associate with King's College London, London, U.K. She is currently a Professor with Northeastern University. She has authored or coauthored more than 100 technical papers on various aspects of wireless networks. Her research interests mainly include HetNets, IoT, and cognitive radio networks. She is also the Member of various international societies, such as the IEEE and China Computer Federation (CCF).
Jie Jia (Member, IEEE) received the Ph.D. degree in computer science and technology from Northeastern University, Shenyang, China, in 2009. In 2016, she was a Visiting Research Associate with King's College London, London, U.K. She is currently a Professor with Northeastern University. She has authored or coauthored more than 100 technical papers on various aspects of wireless networks. Her research interests mainly include HetNets, IoT, and cognitive radio networks. She is also the Member of various international societies, such as the IEEE and China Computer Federation (CCF).View more
Author image of Leyou Yang
School of Computer Science and Engineering, Northeastern University, Shenyang, China
Engineering Research Center of Security Technology of Complex Network System, Ministry of Education, Shenyang, China
Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Shenyang, China
Leyou Yang received the B.S. and M.S. degrees in software engineering in 2015 and 2018, respectively, from Northeastern University, Shenyang, China, where he is currently working toward the Ph.D. degree in computer application technology with the School of Computer Science and Engineering. From 2021 to 2022, he was a Visiting Ph.D. Student with the School of Computer Science and Engineering, Nanyang Technological University, Singapore. His research interests include wireless communications, optimization theory, reinforcement learning, and indoor localization.
Leyou Yang received the B.S. and M.S. degrees in software engineering in 2015 and 2018, respectively, from Northeastern University, Shenyang, China, where he is currently working toward the Ph.D. degree in computer application technology with the School of Computer Science and Engineering. From 2021 to 2022, he was a Visiting Ph.D. Student with the School of Computer Science and Engineering, Nanyang Technological University, Singapore. His research interests include wireless communications, optimization theory, reinforcement learning, and indoor localization.View more
Author image of Xingwei Wang
School of Computer Science and Engineering, Northeastern University, Shenyang, China
Engineering Research Center of Security Technology of Complex Network System, Ministry of Education, Shenyang, China
Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Shenyang, China
Xingwei Wang (Member, IEEE) received the B.S., M.S., and Ph.D. degrees in computer science from Northeastern University, Shenyang, China, in 1989, 1992, and 1998, respectively. He is currently a Professor with the School of Computer Science and Engineering, Northeastern University. He has authored or coauthored more than 100 journal articles, books and book chapters, and refereed conference papers. He was the recipient of the several Best Paper awards. His research interests include cloud computing and future Internet among others.
Xingwei Wang (Member, IEEE) received the B.S., M.S., and Ph.D. degrees in computer science from Northeastern University, Shenyang, China, in 1989, 1992, and 1998, respectively. He is currently a Professor with the School of Computer Science and Engineering, Northeastern University. He has authored or coauthored more than 100 journal articles, books and book chapters, and refereed conference papers. He was the recipient of the several Best Paper awards. His research interests include cloud computing and future Internet among others.View more

References

References is not available for this document.