# Submissions for: Signal Coverage Maps Using Measurements and Machine Learning
|#| Submission | Links |
|-|-|-------------------------------------------|
|1|[Advanced Machine Learning for RSRP Coverage Map Prediction](https://github.com/anandr16910/Signal-Coverage-Maps-Using-Interpolation-techniques-and-ML/tree/main)
This project predicts RSRP values to create signal coverage maps by comparing channel propagation models, geostatistical methods like Kriging, and diverse machine learning techniques, with top performance from optimized GPR in MATLAB.
**Authors:** Anand Rajgopalan
**Affiliation:** IISc Bangalore
**Submission Date:** 2025-03-19|![]()
[](https://github.com/anandr16910/Signal-Coverage-Maps-Using-Interpolation-techniques-and-ML/tree/main)
[](https://matlab.mathworks.com/open/github/v1?repo=anandr16910/Signal-Coverage-Maps-Using-Interpolation-techniques-and-ML)
[](https://github.com/mathworks/MathWorks-Excellence-in-Innovation/blob/main/megatrends/Artificial%20Intelligence.md) [](https://github.com/mathworks/MathWorks-Excellence-in-Innovation/blob/main/megatrends/Wireless%20Communication.md)|
|2|[Signal Coverage Maps Using Measurements and Machine Learning](https://github.com/OxygenFunction/coverageMap)
This project generates signal coverage maps using Log-Distance Path Loss, Ordinary Kriging, and Kriging with Drift models, alongside machine learning regression techniques, evaluating performance with MSE/RMSE.
**Authors:** Jiaxun Fang, Yuanhan Ye
**Affiliation:** Shanghai Jiaotong University
**Submission Date:** 2022-01-09|![]()
[](https://github.com/OxygenFunction/coverageMap)
[](https://matlab.mathworks.com/open/github/v1?repo=OxygenFunction/coverageMap)
[](https://github.com/mathworks/MathWorks-Excellence-in-Innovation/blob/main/megatrends/Artificial%20Intelligence.md) [](https://github.com/mathworks/MathWorks-Excellence-in-Innovation/blob/main/megatrends/Wireless%20Communication.md)|