26-05-2012, 10:39 AM
SPECTRUM MANAGEMENT OF COGNITIVE RADIO USING GENETIC ALGORITHM
[attachment=23092]
INTRODUCTION
1.Cognitive engine decision making process is highly dependant upon parameters
1. Radio transmission parameters
2. Environmental measurements
3. Performance Objectives
2.How can these parameters be related to radio objectives analytically?
Engine must understand how parameters affect the environment.
Multiple parameters must be related to multiple objectives.
3. Cognitive engine implementations
Genetic algorithm based cognitive engine
Cognitive Radio Parameter Range
In IEEE 802.22 a CR terminal is allowed to use a radio communication channel with a bandwidth B(channel) = 6 to 8 MHz in the frequency range between 41 MHz and 910 MHz so, the overall system bandwidth is BW= 869 MHz.
For the simplicity of frequency gene, we assumed BW=800 MHz and B(channel) = 8 MHz frequency band is able to transmit and receive for a particular CR network.
Parameter in concern we are using Frequency, Power, BER, Modulation for simulation
PROPOSED SOLUTION AND ASSUMPTION
GA- genetic algorithm is a search heuristic that explain the process of natural evolution. which generate solutions to optimization problems using techniques inspired by natural evolution, such as inheritance, mutation, selection, and crossover.
The main advantage of genetic algorithms over the other methods is their multi-objective handling capability.
For this system various assumption must be in concern.
Advantage of heuristic approach
Heuristic Methods (genetic algorithm.)
Advantages
Lower complexity than exact methods – less resource usage
Increased flexibility with regards to changes in the fitness equation
Disadvantages
Sub-optimal solutions
summary
Cognition within a radio is much more than a flexible parameters
Intelligence is the ability to make decisions when many apparent options are available
Several cognition algorithms have been studied
Expert Systems, Genetic Algorithms
[attachment=23092]
INTRODUCTION
1.Cognitive engine decision making process is highly dependant upon parameters
1. Radio transmission parameters
2. Environmental measurements
3. Performance Objectives
2.How can these parameters be related to radio objectives analytically?
Engine must understand how parameters affect the environment.
Multiple parameters must be related to multiple objectives.
3. Cognitive engine implementations
Genetic algorithm based cognitive engine
Cognitive Radio Parameter Range
In IEEE 802.22 a CR terminal is allowed to use a radio communication channel with a bandwidth B(channel) = 6 to 8 MHz in the frequency range between 41 MHz and 910 MHz so, the overall system bandwidth is BW= 869 MHz.
For the simplicity of frequency gene, we assumed BW=800 MHz and B(channel) = 8 MHz frequency band is able to transmit and receive for a particular CR network.
Parameter in concern we are using Frequency, Power, BER, Modulation for simulation
PROPOSED SOLUTION AND ASSUMPTION
GA- genetic algorithm is a search heuristic that explain the process of natural evolution. which generate solutions to optimization problems using techniques inspired by natural evolution, such as inheritance, mutation, selection, and crossover.
The main advantage of genetic algorithms over the other methods is their multi-objective handling capability.
For this system various assumption must be in concern.
Advantage of heuristic approach
Heuristic Methods (genetic algorithm.)
Advantages
Lower complexity than exact methods – less resource usage
Increased flexibility with regards to changes in the fitness equation
Disadvantages
Sub-optimal solutions
summary
Cognition within a radio is much more than a flexible parameters
Intelligence is the ability to make decisions when many apparent options are available
Several cognition algorithms have been studied
Expert Systems, Genetic Algorithms