AImers-6G: AI-Driven Region-temporal Resource Provisioning for 6G Immersive Services

With the breakthroughs of sixth-generation (6G), immersive services are beginning to receive a tremendous amount of interest, that is, 6G immersive services. The 6G immersive services involve various wearable devices to provide a high-quality perception of virtual scenes for users. The active participation of service users (SUs) and service providers (SPs) makes the rapid proliferation of wearable devices. Emerging technologies, such as cloud computing and edge computing, have also promoted the rapid development of the 6G immersive service market, making ubiquitous immersive services possible. However, the proliferation of wearable devices has brought severe challenges, including hierarchical resource provisioning, temporal dependencies between services and resources, as well as heterogeneous resource requirements. To fill this gap, we propose an AI-driven 6G immersive service resource provisioning approach, Almers-6G, from the perspective of large and small regions. In the large region, heterogeneous resources are allocated to satisfy the requirements of perception experience from SUs. The problem of resource provisioning is solved by a context-immersive learning-based Lyapunov optimization algorithm. While in the small region, the well-designed blockchain-based double dutch auction (SDDA) mechanism is used for heterogeneous resources matching and pricing determination. Finally, illustrative simulations are provided to show the effectiveness of the proposed scheme.

Automated summary

With the advancements of 6G technology, there is growing interest in 6G immersive services, which utilize wearable devices to provide high-quality virtual experiences for users. The active involvement of service users and providers has led to the rapid proliferation of wearable devices. Emerging technologies like cloud computing and edge computing have further facilitated the development of the 6G immersive service market. However, the widespread use of wearable devices poses challenges in resource provisioning and meeting diverse requirements. To address these challenges, an AI-driven approach called Almers-6G is proposed, focusing on large and small regions for resource allocation and matching using immersive learning and blockchain-based mechanisms.