Amplitude Symmetry Detection for Interfering Signals in CNC Satellite Communications

Subject Areas : Majlesi Journal of Telecommunication Devices

Habib Alizadeh ¹ , Mohsen Rezaee ² , Morteza Babaei ³

1 - PhD Candidate Faculty of Electrical Engineering Department, Imam Hossein University, Tehran,Iran
2 - Assistant Professor ICT Research Institute, Tehran, Iran
3 - Assistant Professor Faculty of Electrical Engineering Department, Imam Hossein University, Tehran, Iran

Received: 2023-06-11 Accepted : 2023-08-13 Published : 2023-09-01

Keywords: Symmetric CNC, CNC satellite Communication, High-Order Statistics,

Abstract :

Satellite communications technology developed rapidly and plays important role in communication networks. In the meantime, CNC satellite communication has received much attention due to its high spectral efficiency. However, the analysis of this type of communication signal in non-cooperative receivers is associated with many challenges due to the nature of time-frequency overlap. The proposed methods in this field have been developed assuming either symmetry or asymmetry in the amplitude of the two interfering signals. However, a reliable method to detect the amplitude symmetry in the non-cooperative receivers is missing in the literature. Thus, in this article, the symmetry or asymmetry of the amplitude of time-frequency overlapping signals of these type of communications has been analyzed using higher-order statistics. For this purpose, the mathematical relationships of higher-order statistics for the model of time-frequency interfering signals received in the non-cooperative receiver have been developed. Then, the appropriate decision function is defined based on different ratios of higher-order statistics of the received signal. This decision function is used to detect amplitude symmetry or asymmetry in time-frequency overlapping signals for CNC communication. The simulations show that the decision-making function based on the sixth and fourth ratio cumulants is a reliable metric, such that the probability of correct classification at signal-to-noise levels higher than 25dB for BPSK modulation is more than 80%, and for QPSK modulation is more than 90%.

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