A Novel Algorithm For Mimo Signal Classification Using Higher-Order Cumulants
| Autor: | Holger Jakel, Menguc Oner, Octavia A. Dobre, Michael S. Mühlhaus, Friedrich K. Jondral |
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| Přispěvatelé: | Işık Üniversitesi, Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümü, Işık University, Faculty of Engineering, Department of Electrical-Electronics Engineering, Öner, Mustafa Mengüç |
| Rok vydání: | 2013 |
| Předmět: |
Feature vector
MIMO Higher-order statistics Independent component analysis Higher-order cumulants Blind signal separation Cognitive radio Channel state information Likelihood-ratio test Automatic modulation classification Blind source separation Multiple-input multiple-output Algorithm Mathematics Computer Science::Information Theory |
| Zdroj: | RWS |
| Popis: | Automatic modulation classification (AMC) of unknown communications signals is employed in both commercial and military applications, such as cognitive radio, spectrum surveillance, and electronic warfare. Most of the AMC methods proposed in the literature are developed for systems with a single transmit antenna. In this paper, an AMC algorithm for multiple-input multiple-output (MIMO) signals is proposed, which is based on higher-order cumulants. The use of cumulants with different orders, as well as their combinations as feature vectors are investigated. The ideal case of a priori knowledge of the channel state information (CSI) is considered, along with a setting of practical relevance, where the channel matrix is blindly estimated through independent component analysis. The performance of the proposed algorithm with different features is evaluated through simulations and compared with that of the average likelihood ratio test (ALRT). This work was partially supported by the TUBITAK (The Scientific and Technological Research Council of Turkey) grant no: 112E020 Publisher's Version |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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