# Through-the-Earth Magnetic Induction Communication and Networking: A Comprehensive Survey

arXiv: https://arxiv.org/abs/2510.14854 · HTML: https://mlsanity.com/paper/2510.14854/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 17 of its 227 references that are in the map.
- First posted on arXiv 16 Oct 2025.

## Builds on (most cited first, 17 of 17)

- [Deep Learning Enabled Semantic Communication Systems](https://mlsanity.com/paper/2006.10685/) (2020)
- [Deep Joint Source-Channel Coding for Adaptive Image Transmission over MIMO Channels](https://mlsanity.com/paper/2309.00470/) (2023)
- [Overview of AI and Communication for 6G Network: Fundamentals, Challenges, and Future Research Opportunities](https://mlsanity.com/paper/2412.14538/) (2024)
- [D2-JSCC: Digital Deep Joint Source-channel Coding for Semantic Communications](https://mlsanity.com/paper/2403.07338/) (2024)
- [Generative AI for Secure Physical Layer Communications: A Survey](https://mlsanity.com/paper/2402.13553/) (2024)
- [Semantics-Guided Diffusion for Deep Joint Source-Channel Coding in Wireless Image Transmission](https://mlsanity.com/paper/2501.01138/) (2025)
- [Edge Learning for 6G-enabled Internet of Things: A Comprehensive Survey of Vulnerabilities, Datasets, and Defenses](https://mlsanity.com/paper/2306.10309/) (2023)
- [Deep Joint Source-Channel Coding for Image Transmission with Visual Protection](https://mlsanity.com/paper/2111.03234/) (2021)
- [Towards the Internet of Underground Things: A Systematic Survey](https://mlsanity.com/paper/1902.03844/) (2019)
- [Joint Active and Passive Beamforming Design for Reconfigurable Intelligent Surface Enabled Integrated Sensing and Communication](https://mlsanity.com/paper/2206.00525/) (2022)
- [Statistical Modeling of the FSO Fronthaul Channel for UAV-based Communications](https://mlsanity.com/paper/1905.12424/) (2019)
- [Location Information Assisted Beamforming Design for Reconfigurable Intelligent Surface Aided Communication Systems](https://mlsanity.com/paper/2110.08980/) (2021)
- [A Testbed of Magnetic Induction-based Communication System for Underground Applications](https://mlsanity.com/paper/1503.02519/) (2015)
- [Magneto-Inductive Powering and Uplink of In-Body Microsensors: Feasibility and High-Density Effects](https://mlsanity.com/paper/1902.03989/) (2019)
- [Inter-Media Backscatter Communications with Magnetic Induction](https://mlsanity.com/paper/1903.10293/) (2019)
- [Fast-Fading Channel and Power Optimization of the Magnetic Inductive Cellular Network](https://mlsanity.com/paper/2406.04737/) (2024)
- [Multi-Frequency Resonant Circuit Based Multi-User Emergency Through-the-Earth Communication with Magnetic Induction](https://mlsanity.com/paper/2407.16972/) (2024)

## Abstract (arXiv)

Magnetic induction (MI) communication (MIC) has emerged as a promising candidate for underground communication networks due to its excellent penetration capabilities. Integration with Space-Air-Ground-Underground (SAGUI) networks in next-generation mobile communication systems requires a well-defined network architecture. A recent discovery in MIC research, MI fast fading, remains in its early stages and presents unique challenges. This paper provides a comprehensive survey on through-the-earth (TTE) MIC, covering MI applications, channel modeling, point-to-point MIC design, relay techniques, network frameworks, and emerging technologies. We compare various MIC applications to highlight TTE-specific challenges and review the principles of channel modeling, addressing both MI slow fading and MI fast fading, along with its potential impact on existing MIC theories. We conduct a fine-grained decomposition of MI channel power gain into four distinct physical parameters, and propose a novel geometric model to analyze MI fast fading. We also summarize MI relay techniques, examine crosstalk effects in relay and high-density networks, and explore key research tasks within the OSI framework for a holistic MI network protocol in SAGUI. To bridge the gaps identified, we propose a MIC framework that supports TCP/IP and Linux, enabling full implementation of existing and emerging MIC solutions. This framework empowers researchers to leverage Linux resources and deep learning platforms for accelerated development of MIC in SAGUI networks. Remaining research challenges, open issues, and promising novel techniques are further identified to advance MIC research.