Abstract-Non-cooperative classification of the modulation type of communication signals finds application in both civilian and military contexts. Existing modulation classification methods for Multiple Input Multiple Output (MIMO) communication systems commonly require a-priori information on the number of transmit antennas employed by the multiantenna transmitter, which, in most of the non-cooperative scenarios involving modulation classification, is unknown and needs to be blindly extracted from the received signal. Since the problems of MIMO modulation classification and detection of the number of transmit antennas are highly coupled, we propose a decision theoretic approach for spatial multiplexing MIMO systems that considers these two tasks as a joint multiple hypothesis testing problem. The proposed method exhibits a high performance even in moderate to low SNR regimes while requiring no a-priori knowledge of the channel state information and the noise variance.
Özetçe-Bilinmeyen haberleşme sinyallerinin gözü kapalı ve işbirliksiz tanınması için geliştirilen teknikler, hem askeri hem de sivil uygulamalarda kullanım bulmuştur. Çok Girdili Çok Çıktılı (MIMO) haberleşme sistemleri, sinyal tanıma sistemleri için üstesinden gelinmesi gereken yeni problemler ortaya koymaktadır. MIMO haberleşmesinde kullanılan uzayzaman kodlarının gözükapalı tanınması bu problemlerin en önemlilerinden biri olarak görülebilir. Bu çalışmada uzayzaman blok kodlanmış sinyal vektörlerinin döngüsel-durağan (cyclostationary) karakteristiklerinin farklı uzay zaman blok kodlarını birbirinden ayırdetmek amacıyla kullanıldığı yenilikçi uzay-zaman kodu tanıma algoritmaları öneriyoruz. Anahtar Kelimeler -MIMO; Uzay zaman blok kodu; sinyal tanıma; klasifikasyon. Abstract-Signal identification techniques developed for the purpose of blind and noncooperative identification of the transmission parameters of unknown communication signals have been employed both in military and civilian applications. Blind identification of the Space-Time Block Codes (STBC) used in a multiantenna transmisson can be regarded as one of the new and most significant challenges presented to the signal identification systems by the Multiple-Input-Multiple-Output (MIMO) transmission systems. In this work, we present novel STBC classification algorithms that exploit the cyclostationary characteristics of the coded transmit signals as discriminating features.
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