Online Spectrum Sensing in Cognitive Radio
- https://doi.org/10.2991/cnct-16.2017.22How to use a DOI?
- PUs, Hidden Markov model, Particle filter, Bayesian filter, Mixed filter
Spectrum sensing is an essential part for cognitive radio which is used for directly or indirectly estimating the states of primary users (PUs) to find spectrum holes for second users (SUs). Nowadays, some online spectrum sensing algorithms have been proposed but most of them ignore the time complexity which influences the efficiency of spectrum sensing. In this paper we propose a new filter algorithm named Mixed filter to address this problem. Leveraged by the Hidden Markov model, this algorithm provides an alternative way to estimate parameters of the model online. Extensive simulations have been conducted and the simulation results show that the proposed method can reduce the computational complexity and shorten the executing time withoug out reducing the accuracy.
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Wen-xiao WANG AU - Xue-mei BAI AU - Zhi-jun WANG AU - Bin GUO PY - 2016/12 DA - 2016/12 TI - Online Spectrum Sensing in Cognitive Radio BT - Proceedings of the International Conference on Computer Networks and Communication Technology (CNCT 2016) PB - Atlantis Press SP - 164 EP - 170 SN - 2352-538X UR - https://doi.org/10.2991/cnct-16.2017.22 DO - https://doi.org/10.2991/cnct-16.2017.22 ID - WANG2016/12 ER -