# Joint Blocklength and Location Optimization for URLLC-enabled UAV Relay Systems

arXiv: https://arxiv.org/abs/1901.05413 · HTML: https://mlsanity.com/paper/1901.05413/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Jan 2019.

## Built on by (most cited first, 2 of 2)

- [Event-Triggered Reinforcement Learning Based Joint Resource Allocation for Ultra-Reliable Low-Latency V2X Communications](https://mlsanity.com/paper/2407.13947/) (2024)
- [Adaptive Cooperative Transmission Design for Ultra-Reliable Low-Latency Communications via Deep Reinforcement Learning](https://mlsanity.com/paper/2511.02216/) (2025)

## Abstract (arXiv)

This letter considers the unmanned aerial vehicle (UAV)-enabled relay system to deliver command information under ultra-reliable and low-latency communication (URLLC) requirements. We aim to jointly optimize the blocklength allocation and the UAV's location to minimize the decoding error probability subject to the latency requirement. The achievable data rate under finite blocklength regime is adopted. A novel perturbation-based iterative algorithm is proposed to solve this problem. Simulation results show that the proposed algorithm can achieve the same performance as the exhaustive search method, and significantly outperforms the existing algorithms.