TY - GEN
T1 - Full-Duplex Self Cancellation Techniques Using Independent Component Analysis
AU - Lu, Hsi-Hung
AU - Fouda, Mohammed E.
AU - Shen, Chung-An
AU - Eltawil, A.
N1 - KAUST Repository Item: Exported on 2021-09-07
Acknowledgements: The authors gratefully acknowledge support from the National Science Foundation under award number 1710746.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
UR - http://hdl.handle.net/10754/670948
UR - https://ieeexplore.ieee.org/document/9443385/
UR - http://www.scopus.com/inward/record.url?scp=85107771395&partnerID=8YFLogxK
U2 - 10.1109/IEEECONF51394.2020.9443385
DO - 10.1109/IEEECONF51394.2020.9443385
M3 - Conference contribution
SN - 9780738131269
SP - 900
EP - 904
BT - 2020 54th Asilomar Conference on Signals, Systems, and Computers
PB - IEEE
ER -