Spectrum Allocation in Next Generation Radio Networks using Emerging Nature-inspired Algorithms

Spectrum Allocation in Next Generation Radio Networks using Emerging Nature-inspired Algorithms. Tegou, T., I., Siakavara, K., Nikolaidis, S., Goudos, S., K., Vergados, D., D., Sarigiannidis, P., & Obaidat, M. In 2018 11th International Symposium on Communication Systems, Networks and Digital Signal Processing, CSNDSP 2018, 2018.
doi abstract bibtex

The key task of a cognitive radio network (CRN) is the effective allocation of spectrum resources according to user needs and requirements. In order to maximize the utilization of the available spectrum, a dynamic allocation of available channels to secondary users is needed. This problem is known as the spectrum allocation problem and it is a combinatorial optimization problem. A possible optimization algorithm that can be applied is chaotic biogeography-based optimization (CBBO). In this paper, a thorough assessment of CBBO is performed in the sense of comparing CBBO with other popular algorithms. According to the simulation results, the CBBO algorithm outperforms competing algorithms in terms of average convergence rate and accuracy.

@inproceedings{
 title = {Spectrum Allocation in Next Generation Radio Networks using Emerging Nature-inspired Algorithms},
 type = {inproceedings},
 year = {2018},
 id = {aa855703-fefd-3b95-a5d3-3dbf27d3d593},
 created = {2020-02-29T16:57:45.265Z},
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 last_modified = {2023-02-11T18:54:04.240Z},
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 citation_key = {Tegou2018a},
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 abstract = {The key task of a cognitive radio network (CRN) is the effective allocation of spectrum resources according to user needs and requirements. In order to maximize the utilization of the available spectrum, a dynamic allocation of available channels to secondary users is needed. This problem is known as the spectrum allocation problem and it is a combinatorial optimization problem. A possible optimization algorithm that can be applied is chaotic biogeography-based optimization (CBBO). In this paper, a thorough assessment of CBBO is performed in the sense of comparing CBBO with other popular algorithms. According to the simulation results, the CBBO algorithm outperforms competing algorithms in terms of average convergence rate and accuracy.},
 bibtype = {inproceedings},
 author = {Tegou, Thomas I. and Siakavara, Katherine and Nikolaidis, Spiros and Goudos, Sotirios K. and Vergados, Dimitrios D. and Sarigiannidis, Panagiotis and Obaidat, Mohammad},
 doi = {10.1109/CSNDSP.2018.8471797},
 booktitle = {2018 11th International Symposium on Communication Systems, Networks and Digital Signal Processing, CSNDSP 2018}
}

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