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

Published in IEEE Wireless Communications, 2023

In this work, we propose AImers-6G, a novel AI-powered framework for efficient region-temporal resource provisioning in 6G immersive services. The method integrates a context-immersive learning-based Lyapunov optimization for task offloading in large regions and a blockchain-based double Dutch auction (BDDA) mechanism for fine-grained, small-region resource pricing and allocation.

AImers-6G enables both latency reduction and energy efficiency while maintaining secure, decentralized control over heterogeneous resource markets. Simulation results demonstrate significant performance improvements in service delay, energy consumption, and social welfare compared with baseline approaches.

This work is part of a collaborative effort involving Tianjin University, Tianjin University of Finance and Economics, and the Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ).

Recommended citation: Qiu Chao, Zheyuan Chen, Xiaoxu Ren, Ziming Dai, Cheng Zhang, and Xiaofei Wang. "AImers-6G: AI-driven region-temporal resource provisioning for 6G immersive services." IEEE Wireless Communications 30, no. 3 (2023): 196-203.
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