Abstract
In this paper, we propose a utility-based spectrum aggregation algorithm to enhance the performance of a cognitive radio network considering multiple objectives: (i) maximization of overall throughput, (ii) reduction of channel switching, (iii) reducing the number of sub-channels comprising the aggregate channel, aimed at opportunistic spectrum use by secondary users (SUs). These three objectives are integrated into a weighted sum utility function. The weight associated with each objective can be set differently (typically done manually) depending on the metric to be optimized. In this article however, we propose and evaluate an automatic mechanism for setting weights. The proposed algorithm including the learning module allows for automated (no manual intervention) adaptable setting of objective- function weights depending on the environment changes and its performance is also shown via the simulation results.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
