Trends, Advancements and Challenges in Intelligent Optimization in Satellite Communication

Philippe Krajsic, Viola Suess, Zehong Cao, Ryszard Kowalczyk, Bogdan Franczyk
9/17/2024
cs.NIcs.ITcs.LG

No confident code implementation found for this paper.

Abstract

Efficient satellite communications play an enormously important role in all of our daily lives. This includes the transmission of data for communication purposes, the operation of IoT applications or the provision of data for ground stations. More and more, AI-based methods are finding their way into these areas. This paper gives an overview of current research in the field of intelligent optimization of satellite communication. For this purpose, a text-mining based literature review was conducted and the identified papers were thematically clustered and analyzed. The identified clusters cover the main topics of routing, resource allocation and, load balancing. Through such a clustering of the literature in overarching topics, a structured analysis of the research papers was enabled, allowing the identification of latest technologies and approaches as well as research needs for intelligent optimization of satellite communication.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Intelligent Spectrum Management in Satellite Communications

83% match2025

Generative AI Agents with Large Language Model for Satellite Networks via a Mixture of Experts Transmission

80% match2024

On the Role of AI in Managing Satellite Constellations: Insights from the ConstellAI Project

80% match2025

Multi-Agent Reinforcement Learning for Heterogeneous Satellite Cluster Resources Optimization

77% match2025

Flexible Payload Configuration for Satellites using Machine Learning

77% match2023

Multi-Agent Reinforcement Learning Counteracts Delayed CSI in Multi-Satellite Systems

76% match2026

Cite this paper

@article{krajsic2024trends,
  title  = {Trends, Advancements and Challenges in Intelligent Optimization in Satellite Communication},
  author = {Philippe Krajsic and Viola Suess and Zehong Cao and Ryszard Kowalczyk and Bogdan Franczyk},
  year   = {2024},
  eprint = {2410.03674},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2410.03674v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2410.03674.svg)](https://codeofpaper.com/paper/2410.03674)

Discussion