Semantic-Aware Command and Control Transmission for Multi-UAVs

2026-01-29

AI Summary

This work addresses the challenge that conventional bit-oriented communication fails to meet the stringent quality-of-service requirements for ultra-reliable low-latency command and control in multi-UAV systems under limited wireless resources. To overcome this limitation, the paper pioneers the integration of semantic communication into this context by introducing a semantic similarity-based metric to quantify message relevance, designing a semantic importance-triggered function, and leveraging a proximal policy optimization (PPO) algorithm to dynamically determine transmission modes and allocate resource blocks. This joint optimization framework simultaneously enhances multicast opportunity exploitation and resource utilization efficiency. By shifting from bit-level to semantic-level transmission, the proposed approach transcends the capacity constraints of traditional communication paradigms, significantly improving both transmission efficiency and overall system effectiveness compared to existing methods.

Technology Category

• Multiagent Systems: Agent Communication
• Search and Optimization: Sampling/Simulation-based Search
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Economics, Online Markets and Human Computation: Cost models of using LLMs in production systems

Abstract

Uncrewed aerial vehicles (UAVs) have played an important role in the low-altitude economy and have been used in various applications. However, with the increasing number of UAVs and explosive wireless data, the existing bit-oriented communication network has approached the Shannon capacity, which cannot satisfy the quality of service (QoS) with ultra-reliable low-latency communication (URLLC) requirements for command and control (C\&C) transmission in bit-oriented UAV communication networks. To address this issue, we propose a novel semantic-aware C\&C transmission for multi-UAVs under limited wireless resources. Specifically, we leverage semantic similarity to measure the variation in C\&C messages for each UAV over continuous transmission time intervals (TTIs) and capture the correlation of C\&C messages among UAVs, enabling multicast transmission. Based on the semantic similarity and the importance of UAV commands, we design a trigger function to quantify the QoS of UAVs. Then, to maximize the long-term QoS and exploit multicast opportunities of C\&C messages induced by semantic similarity, we develop a proximal policy optimization (PPO) algorithm to jointly determine the transmission mode (unicast/multicast/idle) and the allocation of limited resource blocks (RBs) between a base station (BS) and UAVs. Experimental results show that our proposed semantic-aware framework significantly increases transmission efficiency and improves effectiveness compared with bit-oriented UAV transmission.

Problem

• UAV communication
• command and control
• ultra-reliable low-latency communication
• Shannon capacity
• quality of service

Innovation

• semantic-aware communication
• multi-UAV command and control
• semantic similarity
• multicast optimization
• proximal policy optimization (PPO)