QoS-Guaranteed Resource Allocation in Mobile Communications: A Stochastic Network Calculus Approach

Abstract

Deterministic mobile networks are essential for advanced applications that demand strict quality of service (QoS) assurances under limited resource availability. Though network slicing can optimize average performance metrics to offer best-effort services, it often fails to meet the high-reliability requirements of deterministic communication scenarios. In this paper, we introduce a novel QoS-guaranteed inter-slice radio resource allocation scheme for mobile networks to deliver deterministic services over the long term. First, we develop an analytical martingale-based stochastic network calculus framework, which yields stochastic bounds for transmission delays and queue backlogs across various traffic arrival patterns. These bounds produce robust interval estimations that guide resource allocation decisions, effectively addressing channel variability and long-tail QoS effects. Then, an efficient resource allocation algorithm is proposed to approach the derived performance bounds while ensuring fairness across different radio slices with diverse QoS needs. The framework also incorporates an adaptive traffic predictor, enabling our algorithm to track and respond to network dynamics. Numerical results demonstrate that our proposed scheme achieves a promising trade-off between resource utilization and QoS guarantees.