In the upcoming B5G/6G era, virtual reality (VR) over wireless has become a typical application, which is an inevitable trend in the development of video. However, in immersive and interactive VR experiences, VR services typically exhibit high delay, while simultaneously posing challenges for the energy consumption of local devices. To address these issues, this paper aims to improve the performance of the VR service in the edge-terminal cooperative system. Specifically, we formulate a problem of joint caching, computing, and communication VR service policy, by optimizing the weighted sum of overall VR delivery delay and energy consumption of local devices. For the purpose of designing the optimal VR service policy, the optimization problem is decoupled into three independent subproblems to be solved separately. To enhance the caching efficiency within the network, a bidirectional encoder representations from transformers (Bert)-based user interest analysis method is first proposed to characterize the content requesting behavior accurately. On the basis of this, a service cost minimum-maximization problem is formulated with consideration of performance fairness among users. Thereafter, the joint caching and computing scheme is derived for each user with given allocation of communication resources while a bisection-based communication scheme is acquired with the given information on joint caching and computing policy. With alternative optimization, an optimal policy for joint caching, computing and communication based on user interest can be finally obtained. Simulation results are presented to demonstrate the superiority of the proposed user interest-aware caching scheme and the effective of the joint caching, computing and communication optimization policy with consideration of user fairness.

翻译：在即将到来的B5G/6G时代，无线虚拟现实（VR）已成为典型的应用场景，这是视频发展的必然趋势。然而，在沉浸式与交互式VR体验中，VR服务通常表现出高延迟特性，同时给本地设备能耗带来挑战。针对这些问题，本文旨在提升边缘-终端协同系统中VR服务的性能。具体而言，我们通过优化整体VR交付延迟与本地设备能耗的加权和，构建了联合缓存、计算与通信的VR服务策略优化问题。为设计最优VR服务策略，该优化问题被解耦为三个独立的子问题分别求解。为提升网络内缓存效率，首先提出一种基于双向编码器表征（Bert）的用户兴趣分析方法，以准确刻画内容请求行为。在此基础上，考虑用户间性能公平性，构建了服务成本最小-最大化问题。随后，在给定通信资源分配条件下推导每个用户的联合缓存与计算方案，并在给定联合缓存与计算策略信息条件下获取基于二分法的通信方案。通过交替优化，最终可得到基于用户兴趣的联合缓存、计算与通信最优策略。仿真结果验证了所提兴趣感知缓存方案的优越性，以及考虑用户公平性的联合缓存、计算与通信优化策略的有效性。