AI Summary & Key Takeaways
AI InsightIt is shown that signals transmitted from specific users can be detected by using cyclic autocorrelation and spectral density functions characteristics.
📌 3 Key Takeaways
Abstract
Increasing need for efficient usage of frequency spectrum causes to search new methods. Network operators are forced to use their frequency band as efficient as possible due to high subscriber demand. Blind recognition of unauthorized users became necessary to obtain efficient usage of frequency bands. It is found that the two different OFDMA signals with the same CP length show different cyclostationary characteristics. In this paper, it is shown that it is possible that signals from two different users with the same CP lengths can be separated from each other via mesurementS results. Moreover, cyclic autocorrelation function and spectral correlation density function are computed for each user. The differences between their cyclic properties are shown by software defined radio measurement results. It is shown that signals transmitted from specific users can be detected by using cyclic autocorrelation and spectral density functions characteristics.