Universiti Teknologi Malaysia Institutional Repository

Genetic algorithm application in optimizing transmission parameters on adaptive mechanism of cognitive radio

Tan, Jui Ang (2009) Genetic algorithm application in optimizing transmission parameters on adaptive mechanism of cognitive radio. Masters thesis, Universiti Teknologi Malaysia, Faculty of Electrical Engineering.

[img] PDF - Submitted Version
Restricted to Repository staff only

1436Kb
[img] PDF
69Kb
[img] PDF
190Kb
[img] PDF
62Kb

Abstract

Cognitive radio (CR) technology introduces a revolutionary in wireless communication network and it is capable to operate in a continuously varying radio frequency (RF) environment that depends on multiple parameters. CR has the capability to sense, learn the environment and adapt intelligently to the most appropriate way for providing the optimize service that suit to the user’s requirements. Recent researches show that Genetic algorithms (GAs) that rooted in biological inspired are viable implementation technique for CR engine to optimize transmission parameters in a given wireless environment. In this work, GA is applied in adaptive mechanism of CR to perform optimization on transmitter parameters for physical (PHY) layer. The objective of optimization is to obtained optimum set of transmission parameters in order to meet quality of service (QoS) that defined by user in term of minimum transmit power, minimum bit error rate (BER) and maximum throughput. Fitness functions are developed to evaluate the performance of the GA in relation to transmission parameters that characterized. The characterization involves deriving chromosome structure that consists of transmission parameters gene. Finally, a MATLAB® code is developed for simulating the GA operations to achieve optimum set of transmission parameters for optimal radio communications. Simulation results show fitness score for minimum transmit power is 0.927174 with optimum transmit power 0.1768 mW and modulation 64 QAM. While the fitness score for minimum BER is 0.852842 with optimum transmit power 0.74 mW and modulation 8 QAM. Lastly, the fitness score for maximum throughput is 0.952603 with optimum transmit power 0.7144 mW and modulation 64 QAM.

Item Type:Thesis (Masters)
Additional Information:Thesis (Sarjana Kejuruteraan (Elektrik - Elektronik dan Telekomunikasi)) - Universiti Teknologi Malaysia, 2009; Supervisor : Dr. Sharifah Kamilah Syed Yusof
Uncontrolled Keywords:cognitive radio networks, genetic algorithms
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Electrical Engineering
ID Code:12424
Deposited By: Ms Zalinda Shuratman
Deposited On:01 Jun 2011 02:37
Last Modified:03 Aug 2012 00:29

Repository Staff Only: item control page