- The paper demonstrates that UAV-enabled ISAC systems can overcome terrestrial limitations through dynamic trajectory planning and integrated protocol design.
- It details both single and multi-UAV strategies, introducing techniques like TDM-ISAC and Hybrid-ISAC to balance sensing accuracy with communication efficiency.
- The study explores cooperative sensing and communication benefits while outlining future research directions including IRS integration and AI-driven system enhancements.
UAV-Enabled Integrated Sensing and Communication: Opportunities and Challenges
This paper addresses the integration of unmanned aerial vehicles (UAVs) with integrated sensing and communication (ISAC) systems in the context of sixth-generation (6G) wireless networks. The introduction of UAVs as flexible, mobile platforms within ISAC networks holds potential for improving coverage and effectiveness of both sensing and communication services. The primary focus of the paper is on optimizing UAV-enabled ISAC systems to mitigate constraints posed by UAV's size, weight, and power (SWAP), as well as managing challenges arising from their mobility and line-of-sight (LoS) channels.
The discussion begins by exploring the implications of ISAC technologies, with advances in MIMO and mmWave/THz becoming central to delivering reliable, high-throughput communication and precise sensing capabilities. The paper underscores that traditional terrestrial ISAC systems often face significant limitations due to fixed coverage areas and obstruction by environmental obstacles, therefore UAV-enabled ISAC offers greater flexibility and adaptability in providing these services over dynamic areas.
The paper elucidates on both single and multi-UAV ISAC scenarios. For single-UAV systems, strategies such as protocol design, trajectory planning, and resource allocation are examined. Different protocols, namely Co-ISAC, TDM-ISAC, and Hybrid-ISAC, are proposed to optimize the joint operation of sensing and communication functions. The frameworks seek to balance sensing accuracy and communication efficiency by dynamically adapting the UAV's trajectory and resource distribution.
In contrast, multi-UAV systems introduce new cooperative opportunities and improve ISAC performance through coordinated interference management and collaborative sensing. These systems extend the coverage area and enhance the precision of sensed data by employing distributed MIMO radar concepts. However, they also necessitate the development of complex coordination mechanisms and pose synchronization and data exchange challenges.
The paper further explores the mutual benefits of joint S{content}C functionality. Sensing-assisted communication allows UAVs to utilize reflective signals for channel estimation and trajectory prediction, ultimately enhancing communication performance while reducing overhead. On the other hand, communication-assisted sensing benefits from the offloading of sensing tasks to edge servers, improving the efficiency and efficacy of ISAC services.
To guide future research, the paper suggests potential areas, including UAV-aided ISAC for managing UAV networks, synergies with intelligent reflecting surfaces (IRS), and addressing security concerns. Additionally, the integration of artificial intelligence and machine learning could advance the design of dynamic, adaptive systems, particularly in highly variable environments.
The paper concludes that UAV-enabled ISAC is still in its nascent stages, requiring further exploration to realize its full potential in 6G networks. By addressing the challenges outlined, future ISAC systems can transform connectivity and sensing paradigms, providing seamless service to a variety of applications in smart cities, autonomous vehicles, and beyond.