  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.
