= Enabling Spectrum Coexistence of 5G mmWave and Passive Weather Sensing = **WINLAB Summer Internship 2024** **Advisors:** Narayan Mandayam, Ivan Seskar **Graduates:** Hariharan Venkat **Group Members:** Despoina Kosmopoulou, John Allen Manego, Mark Moroney, Prakshab Adhikari, Archisa Arora == Project Objective == The 5G data frequency is close to the weather band, which can result in spectral leakage affecting weather satellites and affecting weather prediction patterns. Our task is to develop an experimental pipeline to measure spectral leakage on weather satellites. We will use Phased Array Antenna Modules (PAAMs) to mimic the 5G satellite and a spectrum analyzer to mimic the weather satellite. == Week 1 == **[https://docs.google.com/presentation/d/1MFWeO6uIcfzo_Y8HGrUXmDwXF2JZ-CdCc0z5wKPLVec/edit?usp=sharing, Week 1 Presentation]** **Summary** * Read Papers on PAAMs, 5G data leakage onto satellites * Getting Familiar with devices such as PAAMs and Spectrum Analyzer == Week 2 == **[https://docs.google.com/presentation/d/1igbOZsoWknAUVzbHqOglDP0G4sMBrAYM/edit?usp=sharing&ouid=117226306871510691778&rtpof=true&sd=true, Week 2 Presentation]** **Summary** * Followed GNURadio OFDM Tutorial on Orbit Sandbox 1 and Sandbox 2 [[Image(OFDM image.png, 1000px)]] == Week 3 == **[https://docs.google.com/presentation/d/1UIEcRe1oQ7yj1cgtXg0betdXtv1dRVnY79gP6x3CWqU/edit?usp=sharing, Week 3 Presentation]** **Summary** * Used the sb1 PAAMs to transmit orthogonal frequency-division multiplexing (OFDM)signal to transmit our signal * Getting familiar with GNURadio and Sandbox 1(Cosmos) [[Image(week 3 image OFDM Signal.gif, 1000px)]] == Week 4 == **[https://docs.google.com/presentation/d/1NrCaT3jO8IK60_EahodhdsaCnH_IYhiuN9KkcebUoWY/edit?usp=sharing, Week 4 Presentation]** **Summary** * Measured the Oscillator error and the noise floor for practice * Followed the Spectrum visualization with Fosphor tutorial * Able to see the wifi in Winlab (big purple area) * Create a waterfall diagram with the OFDM signal tutorial [[Image(waterfall week 4.gif, 1000px)]] [[Image(wifi week 4.gif, 1000px)]] == Week 5 == **[https://docs.google.com/presentation/d/1YOt1zLKjE_o6EGXlFXscmSPfPdzpqfu8RJNqiCG-b0o/edit?usp=sharing, Week 5 Presentation]** **Summary** * Practiced Transmitting a OFDM Signal * Worked on using Foshphor with the different group * Found the Spectrum Mask on the FR2 Band [[Image(fosphorProgress1.png​, 1000px)]] [[Image(fosphorProg2.png,1000px)]] [[Image(fr2maskgraph.png​, 1000px)]] == Week 6 == **[https://docs.google.com/presentation/d/1lC-3q-RbM9CPEVoPPakmC7tCaTb1gbw2p7x6WFOby6U/edit?usp=sharing, Week 6 Presentation]** **Summary** * Practiced Transmitting a OFDM Signal * Started Testing the x,y movement controls of the PAAM device * Worked on the θ Theta and φ Fi directional beam forming with the PAAM device * Set up and used the spectrum analyzer to listen to the PAAM conversation [[Image(​PAAMMoving.gif, 1000px)]] == Week 7 == **[https://docs.google.com/presentation/d/1pqYkbwiNx2SB-al5SsER_7OuTOy6FSIDL3-7QpF1a_w/edit?usp=sharing, Week 7 Presentation]** **Summary** * Created a Ruby code to get raw data from a graph and send it onto an Excel sheet * Set up our station outside to mimic 5G transmission and weather satellites * Transmitted a simple sine wave and measured the relative power of the signal using spectrum analyzer * Used matlab to create a 2D and 3D graph of the data we received from the Spectrum Analyzer [[Image(week7Setup.png, 1000px)]] [[Image(week7Graph.png, 1000px)]] == Week 8 == **[https://docs.google.com/presentation/d/1FBBgpltdNo1lgab9m-ozrqgmURGMq0w4I4kKMGQJ6RI/edit?usp=sharing, Week 8 Presentation]** **Summary** * Processed and visualized measurements taken in the prior week * Planned our next experiment: Sensing Water Interference - Collect transmission data for various topologies (no jug obstructing, empty jug, full water jug) and apply simple ML algorithms to classify into Water Present/No Water Present * Set up and played with GNU Radio [[Image(rxspectrumgraph week 8.png, 500px)]] [[Image(visualization4outsideexperiements.jpg, 1000px)]] == Week 9 == **[https://docs.google.com/presentation/d/1Hjocs1lOVLn5MfFmp31QMTvJGThZ-fVjmXZmrodMPuw/edit?usp=sharing, Week 9 Presentation]** **Summary** * Executed the water interference experiments with 3 states aforementioned * Obtained output in binary data, which was converted to understandable data and visualized * Engaged in “Synchronization” and Pilot Carrier Data Extraction * Laid out the groundwork for ML [[Image(gnuradio week 9 actually.png, 750px)]] [[Image(week9 converting binary to legible.png, 750px)]] == Week 10 == **Summary** * Did some data processing based on previous week's measurements 1. Fixed some initial frequency shift that was not accounted for during measurements 2. Used file sinks after the FFT blocks for headers and payload data to collect fft vectors 3. Extracted pilot and sync word information from these blocks 4. Samples used in the dataset are groupings of the above information * Fed the data into various ML models * Created Error Estimation metric for previous week's measurements using autocorrelation * An F1-score of around 80% was achieved, while we tried to make sure the models generalized as much as possible Some example code for the simple ML model is included in the classification_example.ipynb attached file or at this link: [https://colab.research.google.com/drive/1aWDKQsqeMOn-kunOr3v1ZEu34r0lH0Cu?usp=sharing, Colab for ML Model]. Additionally, the data collected from the water experiment to determine whether water is an obstruction between the two PAAMs can be found here: [https://drive.google.com/drive/folders/1O5zxsR5NZfkNvinBgURpJiGfot8OLAI3?usp=sharing, Google Drive of Data]