Deep Learning-Based Spectrum Management to Enhance the Performance of Cognitive Radio Network Using MobileNet

• Author(s): M. V. S. Sairam ; Raju Egala ; Hanumanthu Rajasekhar ; Killada Sai Nohith
• Paper ID: 1706640
• Page: 274-279
• Published Date: 20-12-2024
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 8 Issue 6 December-2024

Abstract

Cognitive radio (CR) is a leading-edge technology in fifth-generation (5G) network. CR network (CRN) performance can be augmented by effective implementation of spectrum management, which is a decisive function. Signal classification plays a critical role in enhancing spectrum management. Deep learning-based spectrum management (DLSM) is a transformative technology to enhance the performance of CRN. The present work proposes a DLSM using a predefined convolutional neural network (CNN) architecture, MobileNet. The proposed DLSM was developed using a dataset with 1000 constellation diagrams of several digital modulation schemes at a signal to noise ratio (SNR) = 10 dB. The dataset was divided in to 60% for training, 20% for validation, and 20% for testing. In the proposed DL model, the dataset is pre-processed, and feature extraction is conducted using convolution layers; then, classification of images is accomplished using fully connected layers. The results outperformed with 89.4% accuracy, 90% precision, 89% recall, and 89% F1 score. The proposed DLSM exhibits substantial waveform classification performance; hence, it can be recommended for spectrum management in CRN. The dataset was generated and the work implemented using the open-source Python programming language and the licensed Colab Pro platform.

Keywords

Cognitive radio network, deep learning- based spectrum sensing, CNN, accuracy, confusion matrix, AUC.

Citations

IRE Journals:
M. V. S. Sairam , Raju Egala , Hanumanthu Rajasekhar , Killada Sai Nohith "Deep Learning-Based Spectrum Management to Enhance the Performance of Cognitive Radio Network Using MobileNet" Iconic Research And Engineering Journals Volume 8 Issue 6 2024 Page 274-279

IEEE:
M. V. S. Sairam , Raju Egala , Hanumanthu Rajasekhar , Killada Sai Nohith "Deep Learning-Based Spectrum Management to Enhance the Performance of Cognitive Radio Network Using MobileNet" Iconic Research And Engineering Journals, 8(6)