# Resource Allocation and HARQ Optimization for URLLC Traffic in 5G Wireless Networks

arXiv: https://arxiv.org/abs/1804.09201 · HTML: https://mlsanity.com/paper/1804.09201/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Apr 2018.

## Built on by (most cited first, 4 of 4)

- [Guaranteed Dynamic Scheduling of Ultra-Reliable Low-Latency Traffic via Conformal Prediction](https://mlsanity.com/paper/2302.07675/) (2023)
- [Interference-Limited Ultra-Reliable and Low-Latency Communications: Graph Neural Networks or Stochastic Geometry?](https://mlsanity.com/paper/2207.06918/) (2022)
- [Deep Reinforcement Learning for URLLC data management on top of scheduled eMBB traffic](https://mlsanity.com/paper/2103.01801/) (2021)
- [Wideband and Entropy-Aware Deep Soft Bit Quantization](https://mlsanity.com/paper/2110.09541/) (2021)

## Abstract (arXiv)

5G wireless networks are expected to support Ultra Reliable Low Latency Communications (URLLC) traffic which requires very low packet delays ( < 1 msec.) and extremely high reliability (~99.999%). In this paper we focus on the design of a wireless system supporting downlink URLLC traffic. Using a queuing network based model for the wireless system we characterize the effect of various design choices on the maximum URLLC load it can support, including: 1) system parameters such as the bandwidth, link SINR , and QoS requirements; 2) resource allocation schemes in Orthogonal Frequency Division Multiple Access (OFDMA) based systems; and 3) Hybrid Automatic Repeat Request (HARQ) schemes. Key contributions of this paper which are of practical interest are: 1) study of how the the minimum required system bandwidth to support a given URLLC load scales with associated QoS constraints; 2) characterization of optimal OFDMA resource allocation schemes which maximize the admissible URLLC load; and 3) optimization of a repetition code based HARQ scheme which approximates Chase HARQ combining.