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Single-carrier frequency-domain equalization with hybrid decision feedback equalizer for Hammerstein channels containing nonlinear transmit amplifier

Single-carrier frequency-domain equalization with hybrid decision feedback equalizer for Hammerstein channels containing nonlinear transmit amplifier
Single-carrier frequency-domain equalization with hybrid decision feedback equalizer for Hammerstein channels containing nonlinear transmit amplifier
We propose a nonlinear hybrid decision feedback equalizer (NHDFE) for single-carrier (SC) block transmission systems with nonlinear transmit high power amplifier (HPA), which significantly outperforms our previous nonlinear SC frequency-domain equalization (NFDE) design. To obtain the coefficients of the channel impulse response (CIR) as well as to estimate the nonlinear mapping and the inverse nonlinear mapping of the HPA, we adopt a complex-valued (CV) B-spline neural network approach. Specifically, we use a CV B-spline neural network to model the nonlinear HPA, and we develop an efficient alternating least squares scheme for estimating the parameters of the Hammerstein channel, including both the CIR coefficients and the parameters of the CV B-spline model. We also adopt another CV B-spline neural network to model the inversion of the nonlinear HPA, and the parameters of this inverting B-spline model can be estimated using the least squares algorithm based on the pseudo training data obtained as a natural by product of the Hammerstein channel identification. The effectiveness of our NHDFE design is demonstrated in a simulation study, which shows that the NHDFE achieves a signal-to-noise ratio gain of 4dB over the NFDE at the bit error rate level of 10−4
3341-3354
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Hong, Xia
e2869895-2015-4f79-a624-f994027ed12a
Khalaf, Emad
59e9f403-9f13-4871-b19b-ba3368080644
Morfeq, Ali
6b0c5100-6a16-421a-ac69-7ddc2f177dd8
Alotaibi, Naif
4c140c57-3885-4e26-af10-7ac8a5e85954
Harris, Chris
51c03a32-46b3-4e6a-939e-c623ca86a633
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Hong, Xia
e2869895-2015-4f79-a624-f994027ed12a
Khalaf, Emad
59e9f403-9f13-4871-b19b-ba3368080644
Morfeq, Ali
6b0c5100-6a16-421a-ac69-7ddc2f177dd8
Alotaibi, Naif
4c140c57-3885-4e26-af10-7ac8a5e85954
Harris, Chris
51c03a32-46b3-4e6a-939e-c623ca86a633

Chen, Sheng, Hong, Xia, Khalaf, Emad, Morfeq, Ali, Alotaibi, Naif and Harris, Chris (2017) Single-carrier frequency-domain equalization with hybrid decision feedback equalizer for Hammerstein channels containing nonlinear transmit amplifier. IEEE Transactions on Wireless Communications, 16 (5), 3341-3354. (doi:10.1109/TWC.2017.2681083).

Record type: Article

Abstract

We propose a nonlinear hybrid decision feedback equalizer (NHDFE) for single-carrier (SC) block transmission systems with nonlinear transmit high power amplifier (HPA), which significantly outperforms our previous nonlinear SC frequency-domain equalization (NFDE) design. To obtain the coefficients of the channel impulse response (CIR) as well as to estimate the nonlinear mapping and the inverse nonlinear mapping of the HPA, we adopt a complex-valued (CV) B-spline neural network approach. Specifically, we use a CV B-spline neural network to model the nonlinear HPA, and we develop an efficient alternating least squares scheme for estimating the parameters of the Hammerstein channel, including both the CIR coefficients and the parameters of the CV B-spline model. We also adopt another CV B-spline neural network to model the inversion of the nonlinear HPA, and the parameters of this inverting B-spline model can be estimated using the least squares algorithm based on the pseudo training data obtained as a natural by product of the Hammerstein channel identification. The effectiveness of our NHDFE design is demonstrated in a simulation study, which shows that the NHDFE achieves a signal-to-noise ratio gain of 4dB over the NFDE at the bit error rate level of 10−4

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Accepted/In Press date: 8 March 2017
Published date: 8 May 2017
Organisations: Southampton Wireless Group

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Local EPrints ID: 410129
URI: https://eprints.soton.ac.uk/id/eprint/410129
PURE UUID: b3243515-1fb7-4e24-bd23-4ca830c82715

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Date deposited: 03 Jun 2017 04:03
Last modified: 13 Mar 2019 19:57

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Contributors

Author: Sheng Chen
Author: Xia Hong
Author: Emad Khalaf
Author: Ali Morfeq
Author: Naif Alotaibi
Author: Chris Harris

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