Approximation of the Effective Capacity for Multi-Server URLLC Systems With Batch Arrivals

IEEE Transactions on Network Science and Engineering. 2026. P. 1–18.

Anton Karamyshev, Artem Krasilov, Evgeny Khorov

Modern communication networks shall support mission-critical and real-time applications that demand high data rates, low latency, and ultra-high reliability, which is known as Ultra-reliable Low-latency Communications (URLLC). In URLLC systems, the effective capacity, i.e., the maximum traffic rate at which latency and reliability constraints are satisfied, is a key metric for resource management. Its estimations are usually obtained from analytical tools, which, importantly, shall be accurate, generalizable, and easily computable to adapt to diverse and rapidly changing scenarios. However, existing analytical tools, often rooted in queueing theory, rely on unrealistic assumptions, neglect essential traffic features like batch arrivals or unique URLLC constraints, or incur high computational costs, limiting their practical use. To fill this gap, the paper proposes an approximation framework to estimate the delay violation probabilities and the effective capacity for general multi-server queues with batch arrivals (i.e., G^B/G/s). Rooted in queueing and stochastic process theories, the framework yields low-complexity, closed-form solutions suitable for online analysis, providing critical insights into the relationship between URLLC constraints and the effective capacity. Extensive simulations confirm the framework's accuracy across diverse URLLC-relevant settings. Finally, the paper illustrates its practical relevance in a modern cellular system with URLLC traffic.

Keywords: approximation, URLLC, Quality of Service (QoS), Effective capacity, queueing model with batch arrivals