Dataset for testing the performance of a Cuckoo Search Optimization based Forward Consecutive Mean Excision model for threshold adaptation in Cognitive Radio

Published: 30 October 2018| Version 1 | DOI: 10.17632/jxpnhc43xr.1
Contributor:
Adeiza Onumanyi

Description

We present the dataset used to evaluate our newly proposed Cuckoo Search Optimization (CSO) based Forward Consecutive Mean Excision (FCME) model for threshold adaptation in Cognitive Radio (CR). Our CSO-FCME model is designed to effectively auto-tune the parameters of the FCME algorithm. Thus, instead of manually computing the parameter values of the FCME algorithm, which can be often error-prone, our model provides an automatic means to achieve this. Our model also achieves fully blind spectrum sensing in CR, which is highly desirable in the development of CR technologies. The dataset are provided in MATLAB format for future validation purposes and to spur global collaboration amongst researchers working on same or similar subject matter.

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