Summary of best efficient algorithms on cognitive radio cooperative spectrum sensing to improve QoS

Akbari, M. and Reza, A.W. and Noordin, K.A. and Manesh, M.R. and Hindia, M.N. (2014) Summary of best efficient algorithms on cognitive radio cooperative spectrum sensing to improve QoS. In: Proceedings of the 3rd International Conference on Computer Engineering & Mathematical Sciences (ICCEMS 2014), 04-05 Dec 2014, Langkawi, Malaysia.

[img]
Preview
PDF
Summary_of_Best_Efficient_Algorithms.pdf - Published Version

Download (968kB)

Abstract

Cooperative spectrum sensing (CSS) in cognitive radio (CR) has been widely investigated to be considered as a spectrum scanning mechanism that allows secondary users or cognitive radio users (SUs) to use detected spectrum holes caused by primary users (PUs) absence. This paper focuses on optimality of analytical study on the common soft fusion (SDF) CSS based on different iterative algorithms which confirm low total probability of error and high probability of detection in details. In fact, all steps of genetic algorithm (GA), particle swarm optimization (PSO) and imperialistic competitive algorithm (ICA) will be well mentioned in details and investigated on cognitive radio cooperative spectrum sensing (CRCSS) method. Then, the performance of CRCSS employing GA, POS and ICA based scheme is analyzed in MATLAB simulation to show superiority of these schemes over other conventional schemes in terms of detection and error performance with very less complexity. In addition, the ICA-based scheme also indicates promising convergence and time running performance as compared to other schemes.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Cognitive radio, cooperative spectrum sensing, soft decision fusion, ICA, PSO, GA.
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Engineering
Depositing User: Mr. Mohd Samsul Ismail
Date Deposited: 11 Mar 2015 01:03
Last Modified: 11 Mar 2015 01:03
URI: http://eprints.um.edu.my/id/eprint/12992

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year