Joint Space Time Block Code and Modulation Classification for MIMO Systems

Abstract

Abstract-Non-cooperative identification of unknown communication signals is a popular research area with widespread civilian and military applications. Multiple Input Multiple Output (MIMO) systems employing multi-antenna transmission pose new challenges to the signal identification systems, such as the classification of the employed space time block code (STBC) and the modulation in presence of the self-interference inherent to the multi-antenna transmission. In the existing literature, these two classification problems have been handled separately, despite the fact that they are interrelated. This work presents a novel approach to MIMO signal identification by considering the modulation type and the STBC classification tasks as a joint classification problem.

Automatic Modulation Classification Using Interacting Multiple Model Kalman Filter for Channel Estimation

“…Research on the JCEDD approach in the framework of blind AMC applications is extensive, and only a few notable studies are mentioned herein [10,[28][29][30][31][32][33][34]. The interest in JCEDD techniques is not new and growth is expected to continue, not only with AMC applications, but also with other pinnacle functions of CR systems like the SS and ACM.…”

“…The information exchange process is decomposed into two optimization loops, the outer and the inner. The outer loop is a global optimization algorithm, which searches for an optimal CSI estimate, while the inner loop is an ML algorithm that identifies the transmitted symbols [28][29][30][31][32][33]. These loops are interweaved, and sometimes called the upper level and the lower level, in tandem.…”

“…While at the inner loop, the optimized hierarchy reduced search algorithm aided detector, which is an advanced extension of the complex sphere decoder, was used [28]. The signal identification by classifying both the modulation type and the STBC scheme in MIMO systems was considered as a joint classification problem in [32]. The JCEDD was also extended to MIMO-OFDM systems in the framework of sparse Bayesian learning techniques in [10].…”

Blind coding classification in the presence of interference in MIMO systems using ML algorithm

“…7 Ma et al 8 generalized blind channel estimation to cover a much wider class of general linear STBCs. The modulation type and the STBC coding type are classified jointly in the study of Bayer and Öner.…”

“…The modulation type and the STBC coding type are classified jointly in the study of Bayer and Öner. 7 Ma et al 8 generalized blind channel estimation to cover a much wider class of general linear STBCs. The semi-defined relaxation (SDR) method was presented in the study of Via and Santamaria.…”