# Wireless Access in Ultra-Reliable Low-Latency Communication (URLLC)

arXiv: https://arxiv.org/abs/1810.06938 · HTML: https://mlsanity.com/paper/1810.06938/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Oct 2018.

## Built on by (most cited first, 13 of 13)

- [Time-Series JEPA for Predictive Remote Control under Capacity-Limited Networks](https://mlsanity.com/paper/2406.04853/) (2024)
- [A Learning-Based Fast Uplink Grant for Massive IoT via Support Vector Machines and Long Short-Term Memory](https://mlsanity.com/paper/2108.10070/) (2021)
- [Deep Learning for Wireless Networked Systems: a joint Estimation-Control-Scheduling Approach](https://mlsanity.com/paper/2210.00673/) (2022)
- [Network-Aware 5G Edge Computing for Object Detection: Augmenting Wearables to "See" More, Farther and Faster](https://mlsanity.com/paper/2112.13194/) (2021)
- [Event-Triggered Reinforcement Learning Based Joint Resource Allocation for Ultra-Reliable Low-Latency V2X Communications](https://mlsanity.com/paper/2407.13947/) (2024)
- [Latency-Distortion Tradeoffs in Communicating Classification Results over Noisy Channels](https://mlsanity.com/paper/2404.14586/) (2024)
- [BSAC-CoEx: Coexistence of URLLC and Distributed Learning Services via Device Selection](https://mlsanity.com/paper/2212.11805/) (2022)
- [AI-Powered CPS-Enabled Vulnerable-User-Aware Urban Transportation Digital Twin: Methods and Applications](https://mlsanity.com/paper/2501.10396/) (2024)
- [LUCID: An Agentic AI Framework on Digital-Twin in the Loop for QoS-Guaranteeing Robotic Control](https://mlsanity.com/paper/2608.28437/) (2026)
- [Computer Vision Aided URLL Communications: Proactive Service Identification and Coexistence](https://mlsanity.com/paper/2103.10419/) (2021)
- [Communication-Efficient Orchestrations for URLLC Service via Hierarchical Reinforcement Learning](https://mlsanity.com/paper/2307.13415/) (2023)
- [Deep Reinforcement Learning for Uplink Scheduling in NOMA-URLLC Networks](https://mlsanity.com/paper/2308.14523/) (2023)
- [SABER: Symbolic Regression-based Angle of Arrival and Beam Pattern Estimator](https://mlsanity.com/paper/2510.26340/) (2025)

## Abstract (arXiv)

The future connectivity landscape and, notably, the 5G wireless systems will feature Ultra-Reliable Low Latency Communication (URLLC). The coupling of high reliability and low latency requirements in URLLC use cases makes the wireless access design very challenging, in terms of both the protocol design and of the associated transmission techniques. This paper aims to provide a broad perspective on the fundamental tradeoffs in URLLC as well as the principles used in building access protocols. Two specific technologies are considered in the context of URLLC: massive MIMO and multi-connectivity, also termed interface diversity. The paper also touches upon the important question of the proper statistical methodology for designing and assessing extremely high reliability levels.