Detection of Interference in C-Band Signals using K-Means Clustering

Interference is a main disruptive phenomenon which degrades the performance of communication systems and in general the quality of signal acquisition. Real-time communication through a channel is never free from signal disrupting phenomena like interference, distortion and noise. Hence it is essenti...

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Bibliographic Details
Published in:	2020 International Conference on Communication and Signal Processing (ICCSP) pp. 1521 - 1526
Main Authors:	Surya Natarajan, S, Ateesh Varun, R, Shivasubramanian, G, Thamayandran, D, Dharani, M, Gandhiraj, R, Shanmugha Sundaram, G A, Pradeep Kumar, A K, Binoy, N B, Thiruvengadathan, R, Harish Ram, D S
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01-07-2020
Subjects:	Antenna Antenna radiation patterns Bars Delays Estimation Interference k-means clustering Multipath Power Radiation pattern Receiving antennas Signatures Threshold
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Summary:	Interference is a main disruptive phenomenon which degrades the performance of communication systems and in general the quality of signal acquisition. Real-time communication through a channel is never free from signal disrupting phenomena like interference, distortion and noise. Hence it is essential to study their effects and methods of identifying them. Conventional methods to identify, estimate and mitigate interference are model driven. A data driven approach is far more efficient and adaptable than model driven methods. In this paper, we exemplify the use of a data driven approach to identify signatures of interference based on analysis of the acquired RF data.
DOI:	10.1109/ICCSP48568.2020.9182228