ICTACT Journal on Communication Technology

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Gated Dual-path Rnn Empowered Adaptive Dimensional Search for Cognitive Radio in Software-defined Networks


Affiliations
1 Department of Electronics and Communication Engineering, Sri Eshwar College of Engineering, India
2 Department of Electronics and Communication Engineering, PSG Institute of Technology and Applied Research, India
3 Department of Biomedical Engineering, Hindusthan College of Engineering and Technology, India
     

   Subscribe/Renew Journal


In the ever-evolving landscape of wireless communication, the demand for efficient spectrum utilization is paramount. The research begins by acknowledging the existing challenges in CR within SDNs, particularly the need for adaptive strategies to dynamically allocate spectrum resources. A critical research gap lies in the absence of an approach that seamlessly integrates Gated Dual-Path RNNs and Adaptive Dimensional Search to enhance the adaptability and efficiency of CR systems. The proposed methodology leverages the power of Gated Dual-Path RNNs for real-time learning and decision-making, coupled with an Adaptive Dimensional Search algorithm for dynamic spectrum allocation. This study introduces a novel approach, the Gated Dual-Path Recurrent Neural Network (RNN) Empowered Adaptive Dimensional Search, tailored for Cognitive Radio (CR) in Software-Defined Networks (SDNs). The escalating proliferation of wireless devices and applications has exacerbated the spectrum scarcity problem, necessitating intelligent solutions to optimize spectrum utilization. This dual-path architecture enables the CR system to capture temporal dependencies in the spectrum environment and adaptively adjust its parameters for optimal performance. The experimental results demonstrate the efficacy of the proposed approach, showcasing significant improvements in spectrum utilization efficiency, throughput, and adaptability compared to traditional methods. The Gated Dual-Path RNN Empowered Adaptive Dimensional Search proves to be a robust solution for enhancing CR capabilities in SDNs, paving the way for more intelligent and adaptive wireless communication systems.

Keywords

Cognitive Radio, Software-Defined Networks, Gated Dual-Path RNN, Adaptive Dimensional Search, Spectrum Utilization.
Subscription Login to verify subscription
User
Notifications
Font Size

  • M. Bkassiny, Y. Li and S. Jayaweera, “A Survey on Machine-Learning Techniques in Cognitive Radios”, IEEE Communications Surveys and Tutorials, Vol. 15, No. 3, pp. 1136-1159, 2013.

  • S. Akhila and S. Kumar, “Analysis of Handover Algorithms based on Wrong Decision Probability Model”, International Journal of Wireless Networks and Communications, Vol. 2, No. 1, pp. 165-173, 2010.

  • R. Kaniezhil and C. Chandrasekar, “Multiple Service Providers sharing Spectrum using Cognitive Radio”, International Journal of Scientific and Engineering Research, Vol. 3, No. 3, pp. 1-7, 2012.

  • H. Urkowitz, “Energy Detection of Unknown Deterministic Signals”, Proceedings of the IEEE, Vol. 55, No. 4, pp. 523- 531, 1967.

  • Chetan R. Dongarsane and A.N. Jadhav, “Simulation Study on DOA Estimation using Music Algorithm”, International Journal of Technology and Engineering System, Vol. 2, No. 1, pp. 54-57, 2011.

  • N. Muchandi and R. Khanai, “Cognitive Radio Spectrum Sensing: A Survey”, Proceedings of International Conference on Electrical, Electronics, and Optimization Techniques, pp. 3233-3237, 2016.

  • J.C.I. Chuang, “Performance Issues and Algorithms for Dynamic Channel Assignment”, IEEE Journal on Selected Areas in Communications, Vol. 11, No. 6, pp. 955-963, 1993.

  • J. Manco and H.B. Thameur, “Spectrum Sensing using Software Defined Radio for Cognitive Radio Networks: A Survey”, IEEE Access, Vol. 10, pp. 131887-131908, 2022.

  • S.H. Alnabelsi and K.A. Darabkh, “A Comparative Study for Half-duplex and Full-duplex Multi-hop Routing in Software Defined Networks”, Proceedings of International Conference on Software Defined Systems, pp. 1-5, 2022.

  • J.C. Clement, “GRU-SVM Based Threat Detection in Cognitive Radio Network”, Sensors, Vol. 23, No. 3, pp. 1326-1335, 2023.

  • M. Cicioğlu, S. Cicioğlu and A. Çalhan, “SDN‐Enabled Cognitive Radio Network Architecture”, IET Communications, Vol. 14, No. 18, pp. 3153-3160, 2020.


Abstract Views: 120

PDF Views: 1




  • Gated Dual-path Rnn Empowered Adaptive Dimensional Search for Cognitive Radio in Software-defined Networks

Abstract Views: 120  |  PDF Views: 1

Authors

V. Kiruthika
Department of Electronics and Communication Engineering, Sri Eshwar College of Engineering, India
S. Padmapriya
Department of Electronics and Communication Engineering, PSG Institute of Technology and Applied Research, India
M. Ganga
Department of Biomedical Engineering, Hindusthan College of Engineering and Technology, India

Abstract


In the ever-evolving landscape of wireless communication, the demand for efficient spectrum utilization is paramount. The research begins by acknowledging the existing challenges in CR within SDNs, particularly the need for adaptive strategies to dynamically allocate spectrum resources. A critical research gap lies in the absence of an approach that seamlessly integrates Gated Dual-Path RNNs and Adaptive Dimensional Search to enhance the adaptability and efficiency of CR systems. The proposed methodology leverages the power of Gated Dual-Path RNNs for real-time learning and decision-making, coupled with an Adaptive Dimensional Search algorithm for dynamic spectrum allocation. This study introduces a novel approach, the Gated Dual-Path Recurrent Neural Network (RNN) Empowered Adaptive Dimensional Search, tailored for Cognitive Radio (CR) in Software-Defined Networks (SDNs). The escalating proliferation of wireless devices and applications has exacerbated the spectrum scarcity problem, necessitating intelligent solutions to optimize spectrum utilization. This dual-path architecture enables the CR system to capture temporal dependencies in the spectrum environment and adaptively adjust its parameters for optimal performance. The experimental results demonstrate the efficacy of the proposed approach, showcasing significant improvements in spectrum utilization efficiency, throughput, and adaptability compared to traditional methods. The Gated Dual-Path RNN Empowered Adaptive Dimensional Search proves to be a robust solution for enhancing CR capabilities in SDNs, paving the way for more intelligent and adaptive wireless communication systems.

Keywords


Cognitive Radio, Software-Defined Networks, Gated Dual-Path RNN, Adaptive Dimensional Search, Spectrum Utilization.

References