Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Uniform Crossover in Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Dynamic bandwidth allocation for 3G wireless systems-A fuzzy approach
Applied Soft Computing
Using a genetic algorithm approach to solve the dynamic channel-assignment problem
International Journal of Mobile Communications
Harmony search based algorithms for bandwidth-delay-constrained least-cost multicast routing
Computer Communications
PSO-based OFDM adaptive power and bit allocation for multiuser cognitive radio system
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
Exploring simulated annealing and graphical models for optimization in cognitive wireless networks
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Two hybrid differential evolution algorithms for engineering design optimization
Applied Soft Computing
A scalable dynamic spectrum access solution for large wireless networks
ISWPC'10 Proceedings of the 5th IEEE international conference on Wireless pervasive computing
Computationally efficient bandwidth allocation and power control for OFDMA
IEEE Transactions on Wireless Communications
Rate and Power Allocation for Multiuser OFDM: An Effective Heuristic Verified by Branch-and-Bound
IEEE Transactions on Wireless Communications
Fuzzy logic for cross-layer optimization in cognitive radio networks
IEEE Communications Magazine
Expert Systems with Applications: An International Journal
Engineering Applications of Artificial Intelligence
A hybrid harmony search algorithm for the flexible job shop scheduling problem
Applied Soft Computing
Survey A survey on applications of the harmony search algorithm
Engineering Applications of Artificial Intelligence
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This paper gravitates on the spectrum channel allocation problem where each compounding node of a cognitive radio network is assigned a frequency channel for transmission over a given outgoing link, based on optimizing an overall network performance metric dependant on the level of interference among nearby nodes. In this context, genetically inspired algorithms have been extensively used so far for solving this optimization problem in a computationally efficient manner. This work extends previous preliminary research carried out by the authors on the application of the heuristic Harmony Search (HS) algorithm to this scenario by presenting further results and derivations on both HS-based centralized and distributed spectrum allocation techniques. Among such advances, a novel adaptive island-like distributed allocation procedure is presented, which dramatically decreases the transmission rate required for exchanging control traffic among nodes at a quantifiable yet negligible performance penalty. Extensive simulation results executed over networks of increasing size verify, on one hand, that our proposed technique achieves near-optimum spectral channel assignments at a low computational complexity. On the other hand, the obtained results assess that HS vastly outperforms genetically inspired allocation algorithms for the set of simulated scenarios. Finally, the proposed adaptive distributed allocation approach is shown to attain a control traffic bandwidth saving of more than 90% with respect to the naive implementation of a HS-based island allocation procedure.