Analog Least Mean Square Adaptive Filtering for Self-Interference Cancellation in Full Duplex Radios

Authors

Anh Tuyen Le, University of Technology Sydney
Le Chung Tran, University of Wollongong
Xiaojing Huang, University of Technology Sydney
Y. Jay Guo, University of Technology Sydney
Lajos Hanzo, University of Southampton

Publication Name

IEEE Wireless Communications

Abstract

In-band full duplex (IBFD) radio represents one of the key technologies for future wireless communication and radar applications. A major challenge of this technology is to mitigate the strong self-interfer-ence (SI) so that the residual SI level falls below the receiver's noise floor. Radio frequency (RF) self-inter-ference cancellation (SIC) is essential for preventing an IBFD receiver from becoming saturated by the SI. We commence with an in-depth review of the promising analog least mean square (ALMS) adaptive filtering architecture, conceived for RF SIC in the IBFD radio RF front-end. The cancellation circuits employing this architecture can be implemented purely by analog components without any involvement of more power-thirsty digital signal processing. The behaviors, performance, and implementation of the ALMS loop are presented. Finally, their applications in various IBFD radios are discussed, and future research directions are provided.

Open Access Status

This publication is not available as open access

Volume

28

Issue

1

Article Number

9363050

First Page

12

Last Page

18