# Intelligent Spectrum Management in Satellite Communications

arXiv: https://arxiv.org/abs/2509.00286 · HTML: https://mlsanity.com/paper/2509.00286/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 19 of its 206 references that are in the map.
- First posted on arXiv 30 Aug 2025.

## Builds on (most cited first, 19 of 19)

- [LLaMA: Open and Efficient Foundation Language Models](https://mlsanity.com/paper/2302.13971/) (2023)
- [Generative Adversarial Networks](https://mlsanity.com/paper/2203.00667/) (2022)
- [PaLM-E: An Embodied Multimodal Language Model](https://mlsanity.com/paper/2303.03378/) (2023)
- [An Introduction to Variational Autoencoders](https://mlsanity.com/paper/1906.02691/) (2019)
- [A Survey on Large Language Model (LLM) Security and Privacy: The Good, the Bad, and the Ugly](https://mlsanity.com/paper/2312.02003/) (2023)
- [A Survey on the Explainability of Supervised Machine Learning](https://mlsanity.com/paper/2011.07876/) (2020)
- [A Survey on Distributed Machine Learning](https://mlsanity.com/paper/1912.09789/) (2019)
- [NetLLM: Adapting Large Language Models for Networking](https://mlsanity.com/paper/2402.02338/) (2024)
- [Satellite Communications in the New Space Era: A Survey and Future Challenges](https://mlsanity.com/paper/2002.08811/) (2020)
- [Delay-Aware Model-Based Reinforcement Learning for Continuous Control](https://mlsanity.com/paper/2005.05440/) (2020)
- [Ground-Assisted Federated Learning in LEO Satellite Constellations](https://mlsanity.com/paper/2109.01348/) (2021)
- [Artificial Intelligence for Satellite Communication: A Review](https://mlsanity.com/paper/2101.10899/) (2021)
- [Spectrum Sensing Based on Deep Learning Classification for Cognitive Radios](https://mlsanity.com/paper/1909.06020/) (2019)
- [An Improved Apriori Algorithm for Association Rules](https://mlsanity.com/paper/1403.3948/) (2014)
- [Artificial Intelligence Techniques for Next-Generation Mega Satellite Networks](https://mlsanity.com/paper/2207.00414/) (2022)
- [Spectrum Prediction and Interference Detection for Satellite Communications](https://mlsanity.com/paper/1912.04716/) (2019)
- [Reinforcement Learning-Based Downlink Transmit Precoding for Mitigating the Impact of Delayed CSI in Satellite Systems](https://mlsanity.com/paper/2410.21489/) (2024)
- [Outage Constrained Robust Secure Beamforming in Cognitive Satellite-Aerial Networks](https://mlsanity.com/paper/2105.06272/) (2021)
- [A Comprehensive Survey on Spectrum Sharing Techniques for 5G/B5G Intelligent Wireless Networks: Opportunities, Challenges and Future Research Directions](https://mlsanity.com/paper/2211.08956/) (2022)

## Abstract (arXiv)

Satellite Communication (SatCom) networks represent a fundamental pillar in modern global connectivity, facilitating reliable service and extensive coverage across a plethora of applications. The expanding demand for high-bandwidth services and the proliferation of mega satellite constellations highlight the limitations of traditional exclusive satellite spectrum allocation approaches. Cognitive Radio (CR) leading to Cognitive Satellite (CogSat) networks through Dynamic Spectrum Management (DSM), which enables the dynamic adaptability of radio equipment to environmental conditions for optimal performance, presents a promising solution for the emerging spectrum scarcity. In this survey, we explore the adaptation of intelligent DSM methodologies to SatCom, leveraging satellite network integrations. We discuss contributions and hurdles in regulations and standardizations in realizing intelligent DSM in SatCom, and deep dive into DSM techniques, which enable CogSat networks. Furthermore, we extensively evaluate and categorize state-of-the-art Artificial Intelligence (AI)/Machine Learning (ML) methods leveraged for DSM while exploring operational resilience and robustness of such integrations. In addition, performance evaluation metrics critical for adaptive resource management and system optimization in CogSat networks are thoroughly investigated. This survey also identifies open challenges and outlines future research directions in regulatory frameworks, network architectures, and intelligent spectrum management, paving the way for sustainable and scalable SatCom networks for enhanced global connectivity.