== Machine Learning for Enabling 5G and Satellite Network Coexistence in FR3 Spectrum 
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**WINLAB Summer Internship 2025** 

**Group Member:** Audrey Wang
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=== Week 1 (5/27 - 5/29): ===
**Slides:** [https://docs.google.com/presentation/d/1hvr30TzM7EJ0IWJ53jkBN7Zxs11MewyA62KL5Y6unOM/edit?usp=drive_link Week 1 Presentation] 

**Progress:** 
- Conducted literature review on relevant research papers
 1. [https://www.winlab.rutgers.edu/~narayan/PAPERS/5GWF_Conf_Paper_Final.pdf Modeling the Impact of 5G Leakage on Weather Prediction]
 2. [https://ieeexplore.ieee.org/document/10195226 Will Emerging Millimeter-Wave Cellular Networks Cause Harmful Interference to Weather Satellites?] 
 3. [https://ieeexplore.ieee.org/document/10632798 How Does the Growth of 5G mmWave Deployment Affect the Accuracy of Numerical Weather Forecasting?]  
- Understood the high level idea of what **Radio Frequency Interference(RFI)** and **frequency allocations** are 
- Explored how ML can be implemented to minimize the interference between satellite and 5G in different spectrums 
[[Image(https://www.orbit-lab.org/raw-attachment/wiki/Other/Summer/2025/mlCoexist/5G%20Interference.png, 31%)]]
[[Image(https://www.orbit-lab.org/raw-attachment/wiki/Other/Summer/2025/mlCoexist/Spectrum%20Diagram.png, 45%)]]
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=== Week 2 (6/2 - 6/5): ===
**Slides:** [https://docs.google.com/presentation/d/1PqrNeu_GJZgtgby3EKuNGA3qdGhwVvmpP4UPYoz4LJg/edit?usp=drive_link Week 2 Presentation]

**Progress:** 
- Familiar with the pros and cons of the different approaches to beam-forming, especially the benefits of ML application
- Read research papers related to a physical-testbed-generated RFI dataset, and got familiar with the data generation process: 
 1. [http://ieeexplore.ieee.org/document/10663400 A Physical Testbed and Open Dataset for Passive Sensing and Wireless Communication Spectrum Coexistence]
 2. [https://ieeexplore.ieee.org/document/10318952 Microwave Radiometer Calibration Using Deep Learning With Reduced Reference Information and 2-D Spectral Features]
 3. [https://ieeexplore.ieee.org/document/9954900 Radio Frequency Interference Detection for SMAP Radiometer Using Convolutional Neural Networks]
[[Image(https://www.orbit-lab.org/raw-attachment/wiki/Other/Summer/2025/mlCoexist/Data%20Generation%20Schematic.png, 80%)]]
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=== Week 3 (6/9 - 6/12): ===
**Slides:** [https://docs.google.com/presentation/d/159CiF4dxDeX_jZNkPRP5pg5ZLAY3BmdEWMqAPmpjnsc/edit?usp=drive_link Week 3 Presentation]
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=== Week 4 (6/16 - 6/19): ===
**Slides:** [https://docs.google.com/presentation/d/1jEWhbv100Qa9WNsY0GvR3G3Omjuydsg9Gobl5K-tQQ4/edit?usp=sharing Week 4 Presentation]
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=== Week 5 (6/23 - 6/26): ===

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