Abstract
Prediction of future availability times of different
channels based on history information helps a cognitive
radio (CR) to select the best channels for control and
data transmission. Different prediction rules apply to
periodic and stochastic ON-OFF patterns. A CR can learn
the patterns in different channels over time. We propose
a simple classification and learning method to detect the
pattern type and to gather the needed information for
intelligent channel selection. Matlab simulations show
that the proposed method outperforms opportunistic random
channel selection both with stochastic and periodic
channel patterns. The amount of channel switches needed
over time reduces up to 55%, which reduces also the delay
and increases the throughput.
| Original language | English |
|---|---|
| Title of host publication | 2008 First International Workshop on Cognitive Radio and Advanced Spectrum Management |
| Publisher | IEEE Institute of Electrical and Electronic Engineers |
| Pages | 23-27 |
| ISBN (Electronic) | 978-1-4244-2140-4 |
| ISBN (Print) | 978-1-4244-2139-8 |
| DOIs | |
| Publication status | Published - 2008 |
| MoE publication type | A4 Article in a conference publication |
| Event | First IEEE International Workshop on Cognitive Radio and Advanced Spectrum Management, IEEE CogART'08 - Aalborg, Denmark Duration: 14 Feb 2008 → 14 Feb 2008 Conference number: 1 |
Workshop
| Workshop | First IEEE International Workshop on Cognitive Radio and Advanced Spectrum Management, IEEE CogART'08 |
|---|---|
| Abbreviated title | IEEE CogART'08 |
| Country/Territory | Denmark |
| City | Aalborg |
| Period | 14/02/08 → 14/02/08 |
Keywords
- prediction
- learning
- dynamic frequency management
- cognitive radio
- chromium
- learning systems
- stochastic processes
- switches
- history