Attention-based Reinforcement Learning for Real-Time UAV Semantic Communication

by   Won Joon Yun, et al.

In this article, we study the problem of air-to-ground ultra-reliable and low-latency communication (URLLC) for a moving ground user. This is done by controlling multiple unmanned aerial vehicles (UAVs) in real time while avoiding inter-UAV collisions. To this end, we propose a novel multi-agent deep reinforcement learning (MADRL) framework, coined a graph attention exchange network (GAXNet). In GAXNet, each UAV constructs an attention graph locally measuring the level of attention to its neighboring UAVs, while exchanging the attention weights with other UAVs so as to reduce the attention mismatch between them. Simulation results corroborates that GAXNet achieves up to 4.5x higher rewards during training. At execution, without incurring inter-UAV collisions, GAXNet achieves 6.5x lower latency with the target 0.0000001 error rate, compared to a state-of-the-art baseline framework.


page 2

page 6


Cellular-Connected UAVs over 5G: Deep Reinforcement Learning for Interference Management

In this paper, an interference-aware path planning scheme for a network ...

Integrating LEO Satellite and UAV Relaying via Reinforcement Learning for Non-Terrestrial Networks

A mega-constellation of low-earth orbit (LEO) satellites has the potenti...

Integrating LEO Satellites and Multi-UAV Reinforcement Learning for Hybrid FSO/RF Non-Terrestrial Networks

A mega-constellation of low-altitude earth orbit (LEO) satellites (SATs)...

Multi-UAV Conflict Resolution with Graph Convolutional Reinforcement Learning

Safety is the primary concern when it comes to air traffic. In-flight sa...

Cluster Head Detection for Hierarchical UAV Swarm With Graph Self-supervised Learning

In this paper, we study the cluster head detection problem of a two-leve...

Survivable Networks via UAV Swarms Guided by Decentralized Real-Time Evolutionary Computation

The survivable network concept refers to contexts where the wireless com...

Distributed Reinforcement Learning for Flexible and Efficient UAV Swarm Control

Over the past few years, the use of swarms of Unmanned Aerial Vehicles (...