2014/05/21 by Ebrahim Karami, Octavia A. Dobre, Octavia Dobre · 48 citations
Computer Science · Engineering · #Advanced Wireless Communication Techniques #Channel (broadcasting) #Cognitive radio #Detection theory #Identification (biology) #Multiplexing #Orthogonal frequency-division multiplexing #PAPR reduction in OFDM #SIGNAL (programming language) #Sensitivity (control systems) #Signal processing #Wireless Signal Modulation Classification #eess.SP
paper · pdf · doi:10.1109/tvt.2014.2326107
published in IEEE Transactions on Vehicular Technology 64(3), 942-953 (Institute of Electrical and Electronics Engineers) · 36 pages, 14 figures, TVT2015
openalex publication_date 2014/05/21 · openalex created_date 2016/06/24 · arxiv created 2018/03/11 · arxiv updated 2018/03/13 · openalex updated_date 2026/08/05
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 (MIMO) systems. This paper introduces a novel algorithm for the identification of spatial multiplexing (SM) and Alamouti (AL)-coded orthogonal frequency-division multiplexing (OFDM) signals, which relies on second-order signal cyclostationarity. Analytical expressions for the second-order cyclic statistics of the SM-OFDM and AL-OFDM signals are derived and further exploited for 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.