Full-Duplex Self Cancellation Techniques Using Independent Component Analysis
Type
Conference PaperDate
2020Permanent link to this record
http://hdl.handle.net/10754/670948
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Independent component analysis (ICA) has been shown as a promising means for solving the self-interference cancellation (SIC) problem for in-band full duplex systems. This paper presents a detailed analysis of the interference suppression capability and computational complexity of several different ICA algorithms, operating at either real-valued or complex-valued domain. In addition, on the basis of the setup of the full-duplex system, we show that a much simplified complex-valued ICA algorithm that only performs whitening and decorrelation processes are sufficient to separate the signal of interest from the mixed signal. Extensive simulation results are presented in this paper to illustrate the performance and complexity of various ICA approaches applying to the full-duplex system.Citation
Lu, H.-H., Fouda, M. E., Shen, C.-A., & Eltawil, A. (2020). Full-Duplex Self Cancellation Techniques Using Independent Component Analysis. 2020 54th Asilomar Conference on Signals, Systems, and Computers. doi:10.1109/ieeeconf51394.2020.9443385Sponsors
The authors gratefully acknowledge support from the National Science Foundation under award number 1710746.Publisher
IEEEConference/Event name
54th Asilomar Conference on Signals, Systems and Computers, ACSSC 2020ISBN
9780738131269Additional Links
https://ieeexplore.ieee.org/document/9443385/ae974a485f413a2113503eed53cd6c53
10.1109/IEEECONF51394.2020.9443385