Blind Source Separation for Full-Duplex Systems: Potential and Challenges

Mohamed E. Fouda, Chung An Shen, Ahmed E. Eltawil

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


Full-duplex communications systems that transmit and receive simultaneously suffer self-interference due to the mixing of the transmitted signal and the weaker received signal at the same node. The problem becomes compounded in Multi-Input Multi-Output (MIMO) systems, where considerable overhead is dedicated to training. In this article, we discuss using blind source separation techniques, namely Independent Component Analysis (ICA) to reduce training overhead in MIMO in-band full-duplex wireless communication systems. Practical limitations are discussed and experimental results that compare ICA to traditional Least Square approaches are presented, showing the superiority of ICA, especially in low SNR regimes.
Original languageEnglish (US)
Pages (from-to)1379-1389
Number of pages11
JournalIEEE Open Journal of the Communications Society
StatePublished - 2021

Bibliographical note

KAUST Repository Item: Exported on 2022-01-18
Acknowledgements: This work was support in part by National Science Foundation under Award 1710746.


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