| | 66 | |
| | 67 | **Week 5 (6/24 - 6/27)** |
| | 68 | |
| | 69 | This week, we made significant progress in developing and validating our SNR Sensor. The sensor effectively differentiates the original signal from noise, allowing for accurate SNR value calculations. To ensure the sensor's accuracy, we also used FOSPHOR to verify its performance, which alleviated our initial skepticism about the readings. Now we have to test it for our 3 experiments. |
| | 70 | |
| | 71 | We successfully implemented a Satellite Transmitter (DVBT) and a Satellite Receiver in GNU Radio. For the receiver, we developed and integrated a new block that converts stream data into vectors, uploading them as text files within the node. These files serve as collected data to train our machine learning model to predict SINR values, which are our target labels. |
| | 72 | |
| | 73 | During our first experiment, we encountered an issue where the connected UHD devices did not correspond to the physical location of the nodes. To address this, we are planning to connect to nodes using SDRs at different grid locations. |
| | 74 | |
| | 75 | We also working in a stage for automating the entire process to eliminate the need for the GNU Radio GUI. The following steps were taken: |
| | 76 | |
| | 77 | - Extracted Python files and parameterized them, varying the transmitter gain. |
| | 78 | - Created functions to log into different nodes. |
| | 79 | - Streamlined the emulation process, including running time and data storage. |
| | 80 | - Conducted one experiment every three seconds. |
| | 81 | |
| | 82 | This automation would enhance our efficiency and consistency in data collection and analysis in the future. |
| | 83 | |
