Classification of STBC Systems Over Frequency-Selective Channels

Space-time block code (STBC) classification algorithms have recently received growing attention in academia and industry. In addition to their use in the context of military operations, these algorithms found civilian applications in reconfigurable systems, such as software-defined and cognitive radios. The previously reported single-carrier-based STBC classification algorithms are limited to frequency-flat fading channels; however, the wireless channels are typically frequency selective. This paper exploits the dispersive nature of the frequency-selective fading channels to classify Alamouti (AL) and spatial multiplexing (SM) STBCs over such channels. We show that the cross-correlation function of two different received signals for AL exhibits peaks at a particular set of time lags, whereas that for SM does not. Furthermore, we develop a maximum-likelihood classification algorithm. This requires channel knowledge, which may be unavailable in some scenarios such as radio environment awareness in cognitive radios. To avoid this requirement, we also propose a new classification algorithm based on the false alarm rate. Monte Carlo simulations are conducted to demonstrate the performance of the proposed algorithms.