KAUST DepartmentComputer Science Program
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Networks Laboratory (NetLab)
Permanent link to this recordhttp://hdl.handle.net/10754/362476
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AbstractRadio resource management becomes an important aspect of the current wireless networks because of spectrum scarcity and applications heterogeneity. Cognitive radio is a potential candidate for resource management because of its capability to satisfy the growing wireless demand and improve network efficiency. Decision-making is the main function of the radio resources management process as it determines the radio parameters that control the use of these resources. In this paper, we propose an adaptive decision-making scheme (ADMS) for radio resources management of different types of network applications including: power consuming, emergency, multimedia, and spectrum sharing. ADMS exploits genetic algorithm (GA) as an optimization tool for decision-making. It consists of the several objective functions for the decision-making process such as minimizing power consumption, packet error rate (PER), delay, and interference. On the other hand, maximizing throughput and spectral efficiency. Simulation results and test bed evaluation demonstrate ADMS functionality and efficiency.
CitationAlqerm, I., & Shihada, B. (2014). Adaptive Decision-Making Scheme for Cognitive Radio Networks. 2014 IEEE 28th International Conference on Advanced Information Networking and Applications. doi:10.1109/aina.2014.41
Conference/Event name28th IEEE International Conference on Advanced Information Networking and Applications, IEEE AINA 2014