Comparatative Analysis of Energy Detection Spectrum Sensing of Cognitive Radio Under Wireless Environment Using SEAMCAT
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2016, Vol 7, Issue 1
Abstract
In the recent years, the Cognitive Radio technology imposed itself as a good solution to enhance the utilization of unused spectrum and globalized the radio environment for different band users that utilize or require different techniques for transmission. In this paper, the energy detection spectrum sensing technique that is used to detect the presence of unknown deterministic signal is studied under the non-time dispersive fading environment using the Hata propagation model for picocell communication systems. The different aspects of non-time dispersive fading regions over energy detection spectrum sensing and impact of changing a detection threshold of the secondary user Cognitive Radio on interference at primary user for non-cooperative spectrum access have been studied in the terms of probability of interference. The entire Comparatative Analysis of Spectrum Sensing in Cognitive radio has been carried out with the aid of SEAMCAT software platform.
Authors and Affiliations
A. S. Kang, Renu Vig, Jasvir Singh, Jaisukh Singh
Keywords
Related Articles
- EP ID EP154002
- DOI 10.14569/IJACSA.2016.070167
- Views 68
- Downloads 0
Automatic Scheme for Fused Medical Image Segmentation with Nonsubsampled Contourlet Transform
Medical image segmentation has become an essential technique in clinical and research- oriented applications. Because manual segmentation methods are tedious, and semi-automatic segmentation lacks the flexibility, fully-...
Mobile Data Collector Routing Protocol Scheme for Scalable Dense Wireless Sensor Network to Optimize Node’s Life
Wireless Sensor Networks (WSN) is a special kind of network communication architecture which has a very wide range of application and the cost-effectiveness of this architecture boosts its adaptability and usability. The...
Multi-Valued Autoencoders and Classification of Large-Scale Multi-Class Problem
Two-layered neural networks are well known as autoencoders (AEs) in order to reduce the dimensionality of data. AEs are successfully employed as pre-trained layers of neural networks for classification tasks. Most of the...
Empirical Validation of Web Metrics for Improving the Quality of Web Page
Web page metrics is one of the key elements in measuring various attributes of web site. Metrics gives the concrete values to the attributes of web sites which may be used to compare different web pages .The web pages ca...
Learner Cognitive Behavior and Influencing Factors in Web-based Learning Environment
In educational institutions, to improve student learning outcome and performance, the information and communication technology has enabled us to embark web-based learning approaches. The traditional web-based learning en...