# IMNet: Interference-Aware Channel Knowledge Map Construction and Localization

arXiv: https://arxiv.org/abs/2412.01279 · HTML: https://mlsanity.com/paper/2412.01279/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Dec 2024.

## Built on by (most cited first, 5 of 5)

- [CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors](https://mlsanity.com/paper/2504.17323/) (2025)
- [BeamCKMDiff: Beam-Aware Channel Knowledge Map Construction via Diffusion Transformer](https://mlsanity.com/paper/2601.10207/) (2026)
- [CF-CGN: Channel Fingerprints Extrapolation for Multi-band Massive MIMO Transmission based on Cycle-Consistent Generative Networks](https://mlsanity.com/paper/2412.20885/) (2024)
- [CSI-tuples-based 3D Channel Fingerprints Construction Assisted by MultiModal Learning](https://mlsanity.com/paper/2603.25288/) (2026)
- [RadioTrace: Transmitter-Aware Diffusion for Radio Map Estimation without Deployment-Time Fine-Tuning](https://mlsanity.com/paper/2607.20909/) (2026)

## Abstract (arXiv)

This paper presents a novel two-stage method for constructing channel knowledge maps (CKMs) specifically for A2G (Aerial-to-Ground) channels in the presence of non-cooperative interfering nodes (INs). We first estimate the interfering signal strength (ISS) at sampling locations based on total received signal strength measurements and the desired communication signal strength (DSS) map constructed with environmental topology. Next, an ISS map construction network (IMNet) is proposed, where a negative value correction module is included to enable precise reconstruction. Subsequently, we further execute signal-to-interference-plus-noise ratio map construction and IN localization. Simulation results demonstrate lower construction error of the proposed IMNet compared to baselines in the presence of interference.