A Spectrum Anomalies Diagnosis Method Based on Two - Dimensional Hidden Markov Model
- DOI
- 10.2991/fmsmt-17.2017.159How to use a DOI?
- Keywords
- Spectrum, Diagnosis, Hidden, Markov, Model
- Abstract
Radio monitoring system can cover a range of area, where we can obtain the electromagnetic mode information, and the information we get is the result of a mixture of various radio transmission signals. We can't get the intrinsic characteristics of the electromagnetic spectrum. It cannot determine whether the spectrum interferes, and the interference type. This paper studied the two-dimensional spectrum occupancy modeling based on the two-dimensional hidden Markov (2D-HMM). The usual HMM method is unable to fully express and reveal the relationship between different time and frequencies. We proposed to construct a two-dimensional hidden Markov based model library of the electromagnetic spectrum to achieve the self-identification of abnormal electromagnetic spectrum method; Through simulations and experiments, we have verified the feasibility of the spectral abnormalities identification method based on two-dimensional hidden Markov model, it can recognize the co-channel interference, the source super level emission, the ultra-high-power adjacent channel emission and other typical type of exception in a large change interval and with a rather high accuracy.
- Copyright
- © 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 - Cheng Cheng AU - Yunfeng Jia PY - 2017/04 DA - 2017/04 TI - A Spectrum Anomalies Diagnosis Method Based on Two - Dimensional Hidden Markov Model BT - Proceedings of the 2017 5th International Conference on Frontiers of Manufacturing Science and Measuring Technology (FMSMT 2017) PB - Atlantis Press SP - 822 EP - 827 SN - 2352-5401 UR - https://doi.org/10.2991/fmsmt-17.2017.159 DO - 10.2991/fmsmt-17.2017.159 ID - Cheng2017/04 ER -