Yapay Zeka Hızlı Bakış & Çıkarımlar
AI InsightIt is shown that signals transmitted from specific users can be differentiated by using cyclic autocorrelation and spectral density functions characteristics.
📌 3 Maddede Bu Makale
Abstract
Increasing need for efficient usage of frequency spectrum fosters the search of new methods. Network operators are forced to use their frequency band as efficiently as possible due to high subscriber demands. Blind identification of unauthorized users becomes necessary to obtain efficient usage of frequency bands. Like cyclic prefix (CP) length, the position of the zero padding in the frame has an impact on the cyclostationary characteristics of signal, that can be used for blind identification of unauthorized users. In this paper, it is shown that signals from two different users with the same CP lengths can be differentiated from each other via mesurement results. 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 measurements. It is shown that signals transmitted from specific users can be differentiated by using cyclic autocorrelation and spectral density functions characteristics.