Paper Info
Title
Adaptive Self-Interference Cancellation for Full Duplex Systems with Auxiliary Receiver
Abstract
Full-duplex communication promises to double the spectral efficiency over half-duplex communication. The main obstacle in the use of full-duplex in signal transmission is the self-interference. In this paper, we propose a system model where a copy of the transmitted signal is obtained by an auxiliary receiver and afterwards subtracted from the signal at the ordinary receiver in the same User Equipment. This requires the knowledge of the correlation in between the channels of the two receivers. We propose to use a Kalman filter for channel estimation, which is derived to estimate the correlated channels of both receivers in the presence of two types of noise. The first one is the additive Gaussian noise, while the second one is the transceiver noise which results from impurities of the transmitter and receiver components. This scenario allows for a more comprehensive analysis of self-interference cancellation. We utilize the bit error rate of the transmission to study its performance in the cases of perfect channel state information, Kalman filter channel estimation and Least Square Estimation (LSE). It is shown that, the bit error rate when using Kalman filter is lower than when using LSE. The combination of using a Kalman filter as the channel estimator together with an auxiliary receiver also enhances the data rate.
Year
DOI
Venue
2019
10.1109/COMMNET.2019.8742358
2019 International Conference on Advanced Communication Technologies and Networking (CommNet)
Keywords
Field
DocType
Digital Communications,Full-Duplex Communications,Digital Self-Interference Cancellation,Kalman Filter,Transceiver Noise
Transmission (telecommunications),Computer science,Single antenna interference cancellation,Algorithm,Communication channel,Kalman filter,Spectral efficiency,Gaussian noise,Bit error rate,Channel state information
Conference
ISBN
Citations 
PageRank 
978-1-5386-8318-7
0
0.34
References 
Authors
6
4
Name
Order
Citations
PageRank
Maggie Shammaa100.34
Hendrik Vogt283.90
Ahmed El-Mahdy35213.89
Aydin Sezgin459675.27