LatencyScope: A System-Level Mathematical Framework for 5G RAN Latency

TL;DR

LatencyScope is a comprehensive mathematical framework that accurately models and analyzes 5G RAN latency, enabling configuration optimization to meet ultra-reliable low-latency communication targets.

Contribution

It introduces a novel system-level latency modeling framework for 5G RAN, validated on real testbeds, outperforming existing models and simulators.

Findings

Latencyscope closely matches empirical latency distributions.

It captures observed latency bounds effectively.

It outperforms prior models and simulators.

Abstract

This paper presents LatencyScope, a mathematical framework for computing one-way uplink and downlink latency in fifth-generation radio access networks across diverse system configurations. LatencyScope models latency sources across the protocol stack, including radio interfaces, scheduling decisions, processing delays, frame structures, and hardware and software constraints, while capturing dependencies among configuration parameters and stochastic sources of delay. The framework also includes a configuration analyzer that uses these models to search billions of candidate settings and identify those that satisfy latency-reliability targets under user-specified constraints. We validate LatencyScope on two open-source fifth-generation radio access network testbeds, as well as on measurements from a public commercial fifth-generation network. The results show that LatencyScope closely matches empirical latency distributions, captures observed lower and upper latency bounds, and substantially outperforms prior analytical models and widely used fifth-generation network simulators. LatencyScope can determine whether ultra-reliable low-latency communication targets are feasible for a given deployment and, when they are feasible, efficiently find satisfying configurations, helping network operators reason about latency modeling, configuration analysis, and system-level bottlenecks.