Primary User Channel State Prediction Based on Markov Switching Model
Ahmed Mohammed Mikaeil, Bin Guo, Xuemei Bai, Zhijun Wang
Ahmed Mohammed Mikaeil
Available Online November 2015.
- https://doi.org/10.2991/itms-15.2015.172How to use a DOI?
- Channel state prediction; Channel occupancy status; Markov switching model; Maximum likelihood estimation; Primary users
- The most important challenge of the spectrum sensing is to find a way to share the licensed spectrum without interfering with the licensed users transmission. Therefore, predicting the licensed or primary users (PU) channel occupancy status has been investigated extensively in recent years, this study introduce a novel approach for predicting the PU channel state based on Markov switching model. In this approach we model the detected primary user channel state, which can be represented by two states; PU channel “idle” or “occupied” as a time series changing “switching” over the time between two Gaussian distribution according to the detection sequence. Then we fed this time series into the Markov switching model to predict these switching “changes” before they happen so that the secondary user (SU) can adjust their transmission strategies accordingly .The experimental results show the efficiency of the new approach for predicting the PU channel occupancy status.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Ahmed Mohammed Mikaeil AU - Bin Guo AU - Xuemei Bai AU - Zhijun Wang PY - 2015/11 DA - 2015/11 TI - Primary User Channel State Prediction Based on Markov Switching Model BT - 2015 International Conference on Industrial Technology and Management Science PB - Atlantis Press SN - 2352-538X UR - https://doi.org/10.2991/itms-15.2015.172 DO - https://doi.org/10.2991/itms-15.2015.172 ID - Mikaeil2015/11 ER -