Feeling of Presence Maximization: mmWave-Enabled Virtual Reality Meets Deep Reinforcement Learning

by   Peng Yang, et al.

This paper investigates the problem of providing ultra-reliable and energy-efficient virtual reality (VR) experiences for wireless mobile users. To ensure reliable ultra-high-definition (UHD) video frame delivery to mobile users and enhance their immersive visual experiences, a coordinated multipoint (CoMP) transmission technique and millimeter wave (mmWave) communications are exploited. Owing to user movement and time-varying wireless channels, the wireless VR experience enhancement problem is formulated as a sequence-dependent and mixed-integer problem with a goal of maximizing users' feeling of presence (FoP) in the virtual world, subject to power consumption constraints on access points (APs) and users' head-mounted displays (HMDs). The problem, however, is hard to be directly solved due to the lack of users' accurate tracking information and the sequence-dependent and mixed-integer characteristics. To overcome this challenge, we develop a parallel echo state network (ESN) learning method to predict users' tracking information by training fresh and historical tracking samples separately collected by APs. With the learnt results, we propose a deep reinforcement learning (DRL) based optimization algorithm to solve the formulated problem. In this algorithm, we implement deep neural networks (DNNs) as a scalable solution to produce integer decision variables and solving a continuous power control problem to criticize the integer decision variables. Finally, the performance of the proposed algorithm is compared with various benchmark algorithms, and the impact of different design parameters is also discussed. Simulation results demonstrate that the proposed algorithm is more 4.14 algorithms.


Edge Computing Meets Millimeter-wave Enabled VR: Paving the Way to Cutting the Cord

In this paper, a novel proactive computing and mmWave communication for ...

User-centric Heterogeneous-action Deep Reinforcement Learning for Virtual Reality in the Metaverse over Wireless Networks

The Metaverse is emerging as maturing technologies are empowering the di...

Federated Echo State Learning for Minimizing Breaks in Presence in Wireless Virtual Reality Networks

In this paper, the problem of enhancing the virtual reality (VR) experie...

Meta-Reinforcement Learning for Reliable Communication in THz/VLC Wireless VR Networks

In this paper, the problem of enhancing the quality of virtual reality (...

Taming the latency in multi-user VR 360^∘: A QoE-aware deep learning-aided multicast framework

Immersive virtual reality (VR) applications are known to require ultra-h...

Millimeter-Wave Beamforming with Continuous Coverage for Mobile Interactive Virtual Reality

Contemporary Virtual Reality (VR) setups commonly consist of a Head-Moun...

Human-Centric Resource Allocation in the Metaverse over Wireless Communications

The Metaverse will provide numerous immersive applications for human use...

Please sign up or login with your details

Forgot password? Click here to reset