Spectrum Allocation in Cognitive Radio Networks Using Firefly Algorithm

In cognitive radio network, Spectrum Allocation SA problem is a NP-hard problem which needs to be solved in real time. In this work, a recent bio-inspired heuristic Firefly algorithm FA is used for solving SA problem. Three objective functions namely a Max-Sum-Reward MSR, b Max-Min-Reward MMR and c Max-Proportional-Fair MPF are optimized to maximize the network capacity. The performance of FA is compared with Particle Swarm Optimization PSO and Artificial Bee Colony ABC algorithms in terms of quality of solution network capacity and timing complexity. The simulation result reveals that the Firefly algorithm improved quality of solution and timing complexity by 17% and 100% respectively compared to PSO, in contrast to 13% and 103% compared to ABC algorithm. FA proved to give maximum utilization of network capacity by assigning conflict free channels to secondary users.

[1]  D. P. Kothari,et al.  Stochastic economic emission load dispatch , 1993 .

[2]  Xin-She Yang,et al.  Review of Metaheuristics and Generalized Evolutionary Walk Algorithm , 2011, 1105.3668.

[3]  Dervis Karaboga,et al.  A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm , 2007, J. Glob. Optim..

[4]  Hojjat Salehinejad,et al.  Cognitive radio networks spectrum allocation: An ACS perspective , 2012, Sci. Iran..

[5]  Pasura Aungkulanon,et al.  NATURE-INSPIRED ALGORITHMS OF BEES, FIREFLY AND BAT FOR NOISY NON-LINEAR OPTIMISATION PROBLEMS , 2012, IMECS 2012.

[6]  Xin-She Yang,et al.  Nature-Inspired Metaheuristic Algorithms , 2008 .

[7]  Xin-She Yang,et al.  Firefly Algorithms for Multimodal Optimization , 2009, SAGA.

[8]  Mingyan Jiang,et al.  Cognitive radio spectrum assignment based on artificial bee colony algorithm , 2011, 2011 IEEE 13th International Conference on Communication Technology.

[9]  Kathleen Steinhöfel,et al.  Stochastic Algorithms: Foundations and Applications , 2001, Lecture Notes in Computer Science.

[10]  Theofanis Apostolopoulos,et al.  Application of the Firefly Algorithm for Solving the Economic Emissions Load Dispatch Problem , 2011 .

[11]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[12]  D. Karaboga,et al.  On the performance of artificial bee colony (ABC) algorithm , 2008, Appl. Soft Comput..

[13]  Cristina Comaniciu,et al.  Adaptive channel allocation spectrum etiquette for cognitive radio networks , 2005 .

[14]  Ben Y. Zhao,et al.  Utilization and fairness in spectrum assignment for opportunistic spectrum access , 2006, Mob. Networks Appl..

[15]  Singiresu S. Rao.  Engineering Optimization : Theory and Practice , 2010 .

[16]  Xin-She Yang,et al.  Firefly algorithm, stochastic test functions and design optimisation , 2010, Int. J. Bio Inspired Comput..

[17]  Rui Yang,et al.  Genetic spectrum assignment model with constraints in cognitive radio networks , 2011 .

[18]  Haitao Zheng,et al.  Collaboration and fairness in opportunistic spectrum access , 2005, IEEE International Conference on Communications, 2005. ICC 2005. 2005.

[19]  Yue Shi,et al.  A modified particle swarm optimizer , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[20]  A. Gandomi,et al.  Mixed variable structural optimization using Firefly Algorithm , 2011 .

[21]  Amrit Pal Singh,et al.  Comparative Study of Firefly Algorithm and Particle Swarm Optimization for Noisy Non- Linear Optimization Problems , 2012 .

[22]  Dervis Karaboga,et al.  AN IDEA BASED ON HONEY BEE SWARM FOR NUMERICAL OPTIMIZATION , 2005 .

[23]  Haitao Zheng,et al.  Distributed spectrum allocation via local bargaining , 2005, 2005 Second Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks, 2005. IEEE SECON 2005..

[24]  Simon Haykin,et al.  Cognitive radio: brain-empowered wireless communications , 2005, IEEE Journal on Selected Areas in Communications.

[25]  James Kennedy,et al.  The particle swarm: social adaptation of knowledge , 1997, Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97).

[26]  Zhen Peng,et al.  Cognitive radio spectrum allocation using evolutionary algorithms , 2009, IEEE Transactions on Wireless Communications.

[27]  Jing J. Liang,et al.  Problem Definitions and Evaluation Criteria for the CEC 2005 Special Session on Real-Parameter Optimization , 2005 .

[28]  Michael L. Honig,et al.  Auction-Based Spectrum Sharing , 2006, Mob. Networks Appl..