Delay Violation Probability Modeling for 5G Systems with HARQ Operation

2026-07-07

AI Summary

Existing models for 5G HARQ delay violation probability (DVP) significantly underestimate the true DVP under stringent latency constraints, as they neglect critical delay components—including queuing, transmission, decoding, feedback, and control signaling—and fail to account for the practical HARQ behavior that allows new packets to be transmitted in parallel without waiting for ACKs. This work presents the first DVP model that fully incorporates the timing characteristics and parallel transmission mechanisms of 5G HARQ. By integrating queueing theory with Markovian analysis and adhering to 3GPP-specified timing assumptions, we derive a tight upper bound on DVP. Extensive ns-3 simulations using the 5G-LENA framework demonstrate that this bound substantially outperforms existing simplified models in low-latency scenarios, accurately capturing the system’s real-world performance.

Abstract

Meeting the growing demand for quality-of-service (QoS) guarantees in 5G networks requires an accurate characterization of delay performance, commonly captured by the delay violation probability (DVP) at a specified delay target. Although hybrid automatic repeat request (HARQ) is a fundamental reliability mechanism in wireless systems and is central to supporting QoS, many existing approaches to DVP prediction for HARQ remain overly simplified. In particular, they omit important delay components and adopt assumptions that do not reflect the operation of HARQ in slot-based systems such as 5G. Consequently, these models can substantially underestimate the DVP, especially under stringent latency requirements, where the contribution of the neglected components becomes critical. To address this gap, we develop a tractable DVP characterization for 5G HARQ that accounts for queueing, transmission, decoding, and feedback delay, as well as the contribution of Control Signaling (CS) transmissions to the overall delay, under practical timing assumptions consistent with 3GPP operation. Moreover, we incorporate parallel packet transmissions that proceed without waiting for earlier packets to succeed, an essential HARQ behavior frequently overlooked in prior work. Using tools from queueing theory and Markov analysis, we then derive upper bounds on the DVP and validate them against ns-3 5G-LENA simulations.

Problem

• Delay Violation Probability
• 5G
• HARQ
• Quality-of-Service
• Latency

Innovation

• Delay Violation Probability
• HARQ
• 5G
• Queueing Theory
• Control Signaling