Automatic signal identification (ASI) has important applications to both commercial and military communications, such as software defined radio, cognitive radio, spectrum surveillance and monitoring, and electronic warfare. While ASI has been intensively studied for single-input single-output systems, only a few investigations have been recently presented for multiple-input multiple-output systems. This paper introduces a novel algorithm for the identification of spatial multiplexing (SM) and Alamouti coded (AL) orthogonal frequency division multiplexing (OFDM) signals, which relies on the second-order signal cyclostationarity. Analytical expressions for the second-order cyclic statistics of SM-OFDM and AL-OFDM signals are derived and further exploited for the algorithm development. The proposed algorithm provides a good identification performance with low sensitivity to impairments in the received signal, such as phase noise, timing offset, and channel conditions. Automatic signal identification (ASI), multiple-input multiple-output (MIMO), space-time block code (STBC), orthogonal frequency division multiplexing (OFDM), cyclostationarity, cyclic correlation function (CCF), cycle frequency (CF).
Karami et al. propose an algorithm to identify Spatial Multiplexing (SM) and Alamouti (AL)-coded Orthogonal Frequency Division Multiplexing (OFDM) signals for Multiple-Input and Multiple-Output (MIMO) systems based on second-order signal cyclostationarity REF .
Identification of SM-OFDM and AL-OFDM Signals Based on Their Second-Order Cyclostationarity
Computer Science Engineering