Target Channel Visiting Order Design Using Particle Swarm Optimization for Spectrum Handoff in Cognitive Radio Networks
Abstract
:1. Introduction
2. Problem Formulation
Distribution | ρi | |
---|---|---|
Uniform ( ) | ||
Exponential ( ) | ||
Generalized Pareto ( , ) | ||
Rayleigh ( ) | ||
Weibull ( , ) |
3. Proposed Target Channel Visiting Order Design Algorithm
3.1. Introduction of PSO
3.2. Proposed PSO Based Algorithm for Target Channel Visiting Order Design
Steps | Procedures |
---|---|
1 | Swarm initialization. Set k = 0, and randomly generate and , where , , and 1 ≤ i ≤ S. Apply “position correction” procedure to all particles in the swarm. |
2 | Fitness evaluation. Compute the fitness value of each particle according to (2). Set and , where g is the index of the particle which has the highest fitness value. |
3 | Velocity updating. Set k = k + 1, and update the velocity of the particle according to (6). If , set ; if , set . |
4 | Position updating. Update the position of the particle according to (7). Apply “position correction” procedure to all particles in the swarm. |
5 | Fitness evaluation. Compute the fitness value of each particle according to (2). For particle i, if it’s fitness value is greater than the fitness value of , then set ; if it’s fitness value is greater than the fitness value of , then set . |
6 | Stop criteria evaluation. If k equals to the predefined maximum iteration, the algorithm is terminated; otherwise, go to step 3. |
4. Simulation Results
Distribution | Uniform | Exponential | Pareto | Rayleigh | Weibull | |
---|---|---|---|---|---|---|
Mean | Random | 47.1070 | 50.5568 | 43.1053 | 42.9436 | 44.4931 |
Optimal | 40.4067 | 40.9428 | 40.3052 | 40.0660 | 40.0651 | |
Proposed10 | 40.4411 | 41.0199 | 40.3109 | 40.0062 | 40.0694 | |
Proposed50 | 40.4159 | 40.9638 | 40.3063 | 40.0060 | 40.0660 | |
Standard Deviation | Random | 13.6106 | 16.2251 | 4.8572 | 8.5445 | 11.0222 |
Proposed10 | 0.0269 | 0.0483 | 0.0048 | 1.2614 × 10−4 | 0.0035 | |
Proposed50 | 0.0119 | 0.0255 | 0.0011 | 3.0954 × 10−5 | 0.0012 |
Distribution | Uniform | Exponential | Pareto | Rayleigh | Weibull | |
---|---|---|---|---|---|---|
Mean | Random | 60.8031 | 70.3932 | 46.3667 | 49.4641 | 54.7102 |
Optimal | 41.2141 | 43.0155 | 40.6554 | 40.0270 | 40.2594 | |
Proposed10 | 41.2141 | 43.0481 | 40.6614 | 40.0270 | 40.2604 | |
Proposed50 | 41.2141 | 43.0222 | 40.6568 | 40.0270 | 40.2595 | |
Standard Deviation | Random | 31.9083 | 35.4822 | 7.3149 | 22.8160 | 27.3215 |
Proposed10 | 7.1776 × 10−15 | 0.0449 | 0.0061 | 1.9842 × 10−5 | 0.0021 | |
Proposed50 | 7.1776 × 10−15 | 0.0125 | 0.0022 | 1.8236 × 10−6 | 3.6255 × 10−4 |
5. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
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Zheng, S.; Zhao, Z.; Luo, C.; Yang, X. Target Channel Visiting Order Design Using Particle Swarm Optimization for Spectrum Handoff in Cognitive Radio Networks. Algorithms 2014, 7, 418-428. https://doi.org/10.3390/a7030418
Zheng S, Zhao Z, Luo C, Yang X. Target Channel Visiting Order Design Using Particle Swarm Optimization for Spectrum Handoff in Cognitive Radio Networks. Algorithms. 2014; 7(3):418-428. https://doi.org/10.3390/a7030418
Chicago/Turabian StyleZheng, Shilian, Zhijin Zhao, Changlin Luo, and Xiaoniu Yang. 2014. "Target Channel Visiting Order Design Using Particle Swarm Optimization for Spectrum Handoff in Cognitive Radio Networks" Algorithms 7, no. 3: 418-428. https://doi.org/10.3390/a7030418
APA StyleZheng, S., Zhao, Z., Luo, C., & Yang, X. (2014). Target Channel Visiting Order Design Using Particle Swarm Optimization for Spectrum Handoff in Cognitive Radio Networks. Algorithms, 7(3), 418-428. https://doi.org/10.3390/a7030418