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Padmavathi, G.
- Performance Analysis of Cooperative Spectrum Sensing Technique for Low SNR Regime over Fading Channels for Cognitive Radio Networks
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Authors
Affiliations
1 Department of Electronics and Communication Engineering, Sri Venkateswara College of Engineering, Sriperumbudur - 602117, Tamil Nadu, IN
2 Department of Electronics and Communication Engineering, National Engineering College, Kovilpatti - 628503, Tamil Nadu, IN
1 Department of Electronics and Communication Engineering, Sri Venkateswara College of Engineering, Sriperumbudur - 602117, Tamil Nadu, IN
2 Department of Electronics and Communication Engineering, National Engineering College, Kovilpatti - 628503, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 8, No 16 (2015), Pagination:Abstract
Cognitive Radio is a technology for Next Generation Wireless Networks to support Dynamic Spectrum Access which addresses the spectrum scarcity and under utilization problems experienced by today’s wireless communication networks. Spectrum Sensing is an important function of cognitive radio that identifies the unused licensed frequency bands of Primary Users for opportunistic access by Secondary Users. In this paper, we have proposed a sensing technique incorporating wavelet denoising to enhance the sensing performance at low SNR regime. The combination of wavelet denoising preceeding energy detector, hard decision for local sensing and OR fusion rule at the fusion center for cooperative sensing has improved the sensing performance. We have quantified the performance improvement of the proposed technique in fading environments and studied the effect of wavelet denoising. Probability of missed detection has been reduced by 38% over Rayleigh Fading channel and 52% over Nakagami Fading channel compared to conventional sensing technique for ten users cooperation. Sensing time has been reduced by 1 msec and throughput improved by 50 Mbits/Sec/Hz compared to conventional energy detection based sensing method.Keywords
Cognitive Radio, Cooperative Spectrum Sensing, Energy Detection, Hard Decision, Wavelet Denoising- Malicious Traffic Detection and Containment based on Connection Attempt Failures using Kernelized ELM with Automated Worm Containment Algorithm
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Authors
S. Divya
1,
G. Padmavathi
2
Affiliations
1 Faculty of Computer Science and Multimedia, Lincoln University College, Selangor, MY
2 Department of Computer Science, Avinashilingam Institute for Home Science and Higher Education for Women,University, Coimbatore - 641043, Tamil Nadu, IN
1 Faculty of Computer Science and Multimedia, Lincoln University College, Selangor, MY
2 Department of Computer Science, Avinashilingam Institute for Home Science and Higher Education for Women,University, Coimbatore - 641043, Tamil Nadu, IN