GitHub repository: Kodhandarama/Spectrum-Sensing
Primary language: Jupyter Notebook
Description: This project aims to use signal processing based features to train and validate machine-learning algorithms to improve spectrum sensing and related problems in cognitive radios. We used differential entropy, geometric power and LP- norm based features to train supervised ML algorithms and various deep neural networks. The noise process is assumed to follow a generalized Gaussian distribution, which is of practical relevance. Through experimental results based on real-world captured datasets, we show that the proposed method outperforms the energy-based approach in terms of probability of detection. The proposed technique is particularly useful under low signal-to-noise ratio conditions, and when the noise distribution has heavier tails.