2014/10/01 by Walid A. Jerjawi, Yahia A. Eldemerdash, Octavia A. Dobre · 30 citations
Computer Science · Engineering · Mathematics · #Advanced Wireless Communication Techniques #Autocorrelation #Channel (broadcasting) #Cognitive Radio Networks and Spectrum Sensing #Cognitive radio #Detection theory #Orthogonal frequency-division multiplexing #PAPR reduction in OFDM #SIGNAL (programming language) #Signal-to-noise ratio (imaging) #Time–frequency analysis #cs.IT #math.IT
paper · pdf · doi:10.1109/tim.2014.2357592
published in IEEE Transactions on Instrumentation and Measurement 64(3), 823-833 (Institute of Electrical and Electronics Engineers)
openalex publication_date 2014/10/01 · openalex created_date 2016/06/24 · arxiv created 2016/12/12 · arxiv updated 2017/01/24 · openalex updated_date 2026/08/05
In this paper, we investigate the detection of long-term evolution (LTE) single carrier-frequency division multiple access (SC-FDMA) signals, with application to cognitive radio systems. We explore the second-order cyclostationarity of the LTE SC-FDMA signals and apply results obtained for the cyclic autocorrelation function to signal detection. The proposed detection algorithm provides a very good performance under various channel conditions, with a short observation time and at low signal-to-noise ratios, with reduced complexity. The validity of the proposed algorithm is verified using signals generated and acquired by laboratory instrumentation, and the experimental results show a good match with computer simulation results.