Nguyen, V.T. and Hoang, M.K. and Vo, K. and Nguyen, H.D. (2016) HMM based spectrum sensing in the presence of censored data. In: 9th International Conference on Advanced Technologies for Communications, ATC 2016, 12 October 2016 through 14 October 2016.
HMM based spectrum sensing in the presence of censored data.pdf
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Abstract
Spectrum Sensing (SS) techniques play an important role in the Cognitive Radio (CR) systems. In recent years, many spectrum sensing techniques have been proposed in the literature to identify the state of the Primary Users (PUs) in the temporal domain. However, these techniques are usually interested in the current state of channel without consideration to their status in the past. In this paper, we applied Hidden Markov Model (HMM) for SS in Cognitive Radio Network (CRN) and employ an Expectation-Maximization (EM) method to estimate parameters of the HMMin the presence of censored data. Further, we present an optimal likelihood computation for censored data during the online channel status estimation procedure. Simulation results show the effectiveness of the proposed algorithm. © 2016 IEEE.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Divisions: | Faculties > Faculty of Radio-Electronic Engineering |
| Identification Number: | 10.1109/ATC.2016.7764767 |
| Uncontrolled Keywords: | Cognitive systems; Hidden Markov models; Markov processes; Maximum principle; Cognitive radio network (CRN); Estimation procedures; Expectation-maximization method; Likelihood computation; Online channels; Spectrum sensing; Spectrum sensing techniques; Temporal domain; Cognitive radio |
| Additional Information: | Conference code: 125210. Language of original document: English. |
| URI: | http://eprints.lqdtu.edu.vn/id/eprint/9773 |
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