AI Integration in Tactical Communication Systems and Networks: A Survey and Future Research Directions
Nowadays, integrating Artificial Intelligence (AI) in military communication systems is reshaping current defense strategies by enhancing secure data exchange, situational awareness, and autonomous decision-making. This survey examines advancements of AI in tactical communication networks, including UAV networks, radar-based transmission, and electronic warfare resilience, thereby addressing a key gap in the existing literature. This is the first comprehensive review of AI applied exclusively to current tactical communication systems, synthesizing fragmented literature into a unified defense-oriented framework. A key contribution of this survey is its cross-sectoral perspective, exploring how civilian AI techniques are applied in military contexts to enhance resilient and secure communication networks. We analyze state-of-the-art research, industry initiatives, and real-world implementations. Additionally, we introduce a three-criteria evaluation methodology to systematically assess AI applications based on system objectives, military communication constraints, and tactical environmental factors, enabling a study of AI strategies for multidomain interoperability. Finally, we draft future research directions, emphasizing the need for AI standardization, enhanced adversarial resilience, and AI-powered self-healing networks. This survey provides key insights into the evolving role of AI in modern military communications for researchers, policymakers, and defense professionals.
Authors
- Víctor Monzón Baeza (ORCID: https://orcid.org/0000-0002-0035-3944)
- Raúl Parada (ORCID: https://orcid.org/0000-0002-1899-5881)
- Carlos Monzó (ORCID: https://orcid.org/0000-0003-3883-3588)
Institutions
- Universitat Oberta de Catalunya (ES)
- Centre Tecnologic de Telecomunicacions de Catalunya (ES)
Publication Details
- Journal
- Systems
- Published
- 2025-08-30
- DOI
- https://doi.org/10.3390/systems13090752
- Citations
- 1
- Primary Topic
- Robotics and Automated Systems
- Type
- article
- Field-Weighted Citation Impact
- 1.21