Resource Management in Multi-Cell Collaborative Transmission for Long-Term URLLC Services

Ultra-reliable low-latency communication (URLLC) is a critical type of service that imposes stringent latency requirements. Considering the random and burst URLLC packets arrival characteristics, incorporating spatial frequency reuse into multi-cell networks can significantly improve the system performance. Nevertheless, how to design the frequency refuse strategy for such a multi-cell URLLC system remains technically challenging. In this article, we investigate an online dynamic resource scheduling problem in a multi-cell downlink system with URLLC services. The long-term time-averaged effective throughput is maximized while guaranteeing the instantaneous transmission reliability and prolonged network stability. The formulated problem is a mixed integer nonlinear stochastic optimization problem, in which the Lyapunov optimization is first leveraged to transform the long-term maximization problem into sequential short-term online ones. To tackle the deterministic problem in each time-slot, we further propose a distributed algorithm that delegates computational processes to corresponding base stations for collaborative execution. In this framework, the user association is abstracted as a cooperative game model. Subsequently, each base station exploits alternating optimization and convex optimization approximation algorithms to address the remaining resource allocation problem. Simulation results validate the effectiveness of the proposed algorithm in throughput-backlog trade-off, showcasing that the multi-cell collaborative transmission can attain better performance compared with existing schemes.