GeneticCrn

Simulation source code for the paper "Genetic Algorithm Aided Transmit Power Control in Cognitive Radio Networks".

Abstract

We address the power control problem in cognitive radio networks where secondary users exploit spatial spectrum opportunities without causing unacceptable interference to primary users. An optimization problem is formulated aiming at maximizing the utility of secondary users and to ensure the QoS for both primary and secondary users. To solve the power allocation problem a genetic algorithm is developed, and two fitness functions are proposed. The first is oriented towards minimizing the total transmit power consumption of the secondary network. The second is a multi-objective function and is oriented to the joint optimization of total capacity and transmit power consumption of the secondary network. Results show a near-optimum performance of the genetic algorithm aided power control scheme based on the multi-objective fitness function.

Getting Started

In order to run the simulations you need Matlab 2015a or higher and a C compiler compatible with the installed Matlab version. From the command line type:

git clone https://github.com/raikel/GeneticCrn

Open Matlab and add the source directory src (and all its subfolders) to the Matlab search path. In the Matlab workspace, open the directory src\lib\mex and type in the command window:

compile

This will compile all the source mex files. To run the simulation with default parameters values, type in the Matlab command window:

stats = netsim()

Cite

Please cite this work as

Bordón, R., Sánchez, S. M., Fernandez, E. M., Souza, R. D., & Alves, H. (2014, June). Genetic algorithm aided transmit power control in cognitive radio networks. In 2014 9th International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM) (pp. 61-66). IEEE.