# AI-Driven Tactical Communications and Networking for Defense: A Survey and Emerging Trends

arXiv: https://arxiv.org/abs/2504.05071 · HTML: https://mlsanity.com/paper/2504.05071/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 15 of its 39 references that are in the map.
- First posted on arXiv 7 Apr 2025.

## Builds on (most cited first, 15 of 15)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Mamba: Linear-Time Sequence Modeling with Selective State Spaces](https://mlsanity.com/paper/2312.00752/) (2023)
- [CBAM: Convolutional Block Attention Module](https://mlsanity.com/paper/1807.06521/) (2018)
- [Efficiently Modeling Long Sequences with Structured State Spaces](https://mlsanity.com/paper/2111.00396/) (2021)
- [Fully Convolutional Siamese Networks for Change Detection](https://mlsanity.com/paper/1810.08462/) (2018)
- [Remote Sensing Image Change Detection with Transformers](https://mlsanity.com/paper/2103.00208/) (2021)
- [A Transformer-Based Siamese Network for Change Detection](https://mlsanity.com/paper/2201.01293/) (2022)
- [Activation Functions: Comparison of trends in Practice and Research for Deep Learning](https://mlsanity.com/paper/1811.03378/) (2018)
- [Building Change Detection for Remote Sensing Images Using a Dual Task Constrained Deep Siamese Convolutional Network Model](https://mlsanity.com/paper/1909.07726/) (2019)
- [LSKNet: A Foundation Lightweight Backbone for Remote Sensing](https://mlsanity.com/paper/2403.11735/) (2024)
- [Change Detection Methods for Remote Sensing in the Last Decade: A Comprehensive Review](https://mlsanity.com/paper/2305.05813/) (2023)
- [Unsupervised Change Detection in Multi-temporal VHR Images Based on Deep Kernel PCA Convolutional Mapping Network](https://mlsanity.com/paper/1912.08628/) (2019)
- [Exchange means change: an unsupervised single-temporal change detection framework based on intra- and inter-image patch exchange](https://mlsanity.com/paper/2310.00689/) (2023)
- [LCD-Net: A Lightweight Remote Sensing Change Detection Network Combining Feature Fusion and Gating Mechanism](https://mlsanity.com/paper/2410.11580/) (2024)

## Abstract (arXiv)

The integration of Artificial Intelligence (AI) in military communications and networking is reshaping modern defense strategies, enhancing secure data exchange, real-time situational awareness, and autonomous decision-making. This survey explores how AI-driven technologies improve tactical communication networks, radar-based data transmission, UAV-assisted relay systems, and electronic warfare resilience. The study highlights AI applications in adaptive signal processing, multi-agent coordination for network optimization, radar-assisted target tracking, and AI-driven electronic countermeasures. Our work introduces a novel three-criteria evaluation methodology. It systematically assesses AI applications based on general system objectives, communications constraints in the military domain, and critical tactical environmental factors. We analyze key AI techniques for different types of learning applied to multi-domain network interoperability and distributed data information fusion in military operations. We also address challenges such as adversarial AI threats, the real-time adaptability of autonomous communication networks, and the limitations of current AI models under battlefield conditions. Finally, we discuss emerging trends in self-healing networks, AI-augmented decision support systems, and intelligent spectrum allocation. We provide a structured roadmap for future AI-driven defense communications and networking research.