A novel scheme for spectrum prediction in cognitive radio networks / Mehdi Askari and Rezvan Dastanian
An efficient spectrum prediction model is presented to improve the spectrum utilization in cognitive radio network. In this model, a novel improved version of Teaching-Learning-Based-Optimization algorithm, also referred to iTLBO algorithm, is proposed to train a feed forward artificial neural netwo...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Book |
| Published: |
Universiti Teknologi MARA,
2021-10.
|
| Subjects: | |
| Online Access: | Link Metadata |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | An efficient spectrum prediction model is presented to improve the spectrum utilization in cognitive radio network. In this model, a novel improved version of Teaching-Learning-Based-Optimization algorithm, also referred to iTLBO algorithm, is proposed to train a feed forward artificial neural network (ANN). The performance of the proposed iTLBO-ANN model is compared with some hybrid prediction models, including the genetic algorithm with ANN (GA-ANN), the firefly algorithm with ANN (FF-ANN), and the conventional TLBO algorithm with ANN (TLBO- ANN). Performance evaluation via a real-word spectrum data set (GSM-900) confirms that iTLBO-ANN outperforms other spectrum prediction schemes in terms of prediction error and prediction efficiency. |
|---|---|
| Item Description: | https://ir.uitm.edu.my/id/eprint/52056/1/52056.pdf |