Publication Type : Conference Proceedings
Publisher : ICCSP
Source : 2020 International Conference on Communication and Signal Processing (ICCSP) (2020)
Url : https://ieeexplore.ieee.org/document/9182228
Keywords : Antenna, antenna radiation patterns, Bars, data driven approach, Delays, Estimation, Interference, Interference suppression, K-means clustering, model driven methods, Multipath, pattern clustering, power, Radiation pattern, radiofrequency interference, real-time communication systems, Receiving antennas, RF data acquisition, signal acquisition, Signal detection, signal disrupting phenomena, Signatures, Threshold
Campus : Coimbatore
School : School of Engineering
Department : Electronics and Communication
Year : 2020
Abstract : 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.
Cite this Research Publication : S. S. Natarajan, R. Varun, A., Shivasubramanian, G., Thamayandran, D., Dharani, M., Gandhiraj, R., Sundaram, G. A. Shanmug, Kumar, A. K. Pradeep, Binoy, N. B., Dr. T. Rajagopalan, and Ram, D. S. Harish, “Detection of Interference in C-Band Signals using K-Means Clustering”, 2020 International Conference on Communication and Signal Processing (ICCSP). 2020.