Turbo EP-Based Equalization: A Filter-Type Implementation

Santos, Irene; Murillo-Fuentes, Juan José; Arias-de-Reyna, Eva; Olmos, Pablo M.

doi:10.1109/tcomm.2018.2832202

Cited by 29 publications

(52 citation statements)

References 31 publications

(137 reference statements)

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“…This novel approach can be exploited in block, WF and KS implementations of the equalizer. The experimental results included show that the proposed equalizer improves or achieves the same performance of FEP, BEP and KSEP equalizers [10], [12] with half their computational complexity. It also outperforms the LMMSE, with just twice its complexity, and other EP-based solutions, such as the BP-EP [13].…”

Section: Discussionmentioning

confidence: 90%

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A Double EP-Based Proposal for Turbo Equalization

Santos

Murillo-Fuentes

Arias-de-Reyna

2020

IEEE Signal Process. Lett.

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This letter deals with the application of the expectation propagation (EP) algorithm to turbo equalization. The EP has been successfully applied to obtain either a better approximation at the output of the equalizer or at the output of the channel decoder to better initialize the Gaussian prior used by the equalizer. In this letter we combine both trends to propose a novel double EP-based equalizer that is able to decrease the number of iterations needed, reducing the computational complexity to twice that of the linear MMSE. This novel equalizer is developed in three different implementations: a block design that exploits the whole vector of observations, a Wiener filter-type approach that just uses the observations within a predefined window and a Kalman smoothing filter-type approach that emulates the BCJR behavior. Finally, we include some experimental results to compare the three different implementations and to detail their improvements with respect to other EP-based proposals in the literature.

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Section: Discussionmentioning

confidence: 90%

“…Finally, a WF approach can be exploited to reduce the computational complexity to be quadratic in the length of a to-be-predefined window, W, i.e., ε eq " NW 2 , yielding a complexity OpKNW 2 q [10]. However, its performance degrades in comparison to the block or KS designs since it just uses W observations [14].…”

Section: Three Different Implementationsmentioning

confidence: 99%

A Double EP-Based Proposal for Turbo Equalization

Santos

Murillo-Fuentes

Arias-de-Reyna

2020

IEEE Signal Process. Lett.

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“…The EP computes the mean and variance of these Gaussians by matching the moments of the approximated posterior with the ones of the true posterior, including the discrete probability mass functions (pmf) of the priors. The EP has already been applied to multiple-input multiple-output (MIMO) detection [17]- [20], low-density parity-check (LDPC) channel decoding [21], [22] and standalone/turbo equalization [10], [11], [23]- [25], among others.…”

Section: Introductionmentioning

confidence: 99%

“…In [10], a block implementation of an EP-based equalizer is proposed, whose complexity is quadratic in the frame length. This implementation is revised in [23] to propose an optimized version for turbo equalization. Since the block implementation can be intractable for long frames, a filtered implementation based on the Wiener-filter behavior is also proposed in [23] for turbo equalization.…”

Section: Introductionmentioning

confidence: 99%

“…This implementation is revised in [23] to propose an optimized version for turbo equalization. Since the block implementation can be intractable for long frames, a filtered implementation based on the Wiener-filter behavior is also proposed in [23] for turbo equalization. It allows a reduction in complexity which is linear in the frame length and quadratic in the size of the window used.…”

Section: Introductionmentioning

confidence: 99%

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Channel Equalization With Expectation Propagation at Smoothing Level

Santos

Murillo-Fuentes

Aradillas

et al. 2020

IEEE Trans. Commun.

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In this paper we propose a smoothing turbo equalizer based on the expectation propagation (EP) algorithm with quite improved performance compared to the Kalman smoother, at similar complexity. In scenarios where high-order modulations or/and large memory channels are employed, the optimal BCJR algorithm is computationally unfeasible. In this situation, lowcost but suboptimal solutions, such as the linear minimum mean square error (LMMSE), are commonly used. Recently, EP has been proposed as a tool to improve the Kalman smoothing performance. In this paper we review these solutions to apply the EP at the smoothing level, rather than at the forward and backwards stages. Also, we better exploit the information coming from the channel decoder in the turbo equalization schemes. With these improvements we reduce the computational complexity, speed up convergence and outperform previous approaches. We included some simulation results to show the robust behavior of the proposed method regardless of the scenario, and its improvement in terms of performance in comparison with other EP-based solutions in the literature.

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Performance Analysis and Improvement for VAMP Soft Frequency-Domain Equalizers

Tao

et al. 2019

IEEE Access

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The vector approximate message passing (VAMP) soft frequency-domain equalizer (SFDE) has been proposed for turbo equalization. It consists of an inner soft equalizer (ISE) and an inner soft slicer (ISS), which iteratively exchange block-wise extrinsic information to improve the equalization performance, analogous to the outer turbo iteration between a soft equalizer and a soft decoder. However, a comparison of the VAMP-SFDE with other types of self-iterative SFDEs, including the self-iterative block-wise soft interference cancellation (SI-BSIC) SFDE and the generalized approximate message passing (GAMP) SFDE, is lacking. Moreover, comprehensive performance analysis for the VAMP-SFDE is yet to be performed. In this paper, relations among the VAMP-SFDE, the SI-BSIC-SFDE, and the GAMP-SFDE are first revealed. After that, the performance analysis is provided for the VAMP-SFDE and it leads to an improved semi-adaptive damping (SAD) scheme for maintaining the independence between the ISS and ISE. The resulting SAD-VAMP-SFDE shows improved mean square error (MSE) evolution curves compared with the original VAMP-SFDE. The SAD-VAMP-SFDE-based turbo equalization outperforms those using the SI-BSIC-SFDE or GAMP-SFDE and approaches the matched filter bound (MFB) over low signal-to-noise ratio region. To further demonstrate its superiority, the SAD-VAMP-SFDE is employed to enable a near-capacity transceiver design, which adopts the serial concatenation of an irregular convolutional code and a unity-rate code on the transmitter side.INDEX TERMS Frequency-domain turbo equalization, self-iterative soft equalizer (SISE), state evolution, vector approximate message passing (VAMP).

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Turbo EP-Based Equalization: A Filter-Type Implementation

Cited by 29 publications

References 31 publications

A Double EP-Based Proposal for Turbo Equalization

A Double EP-Based Proposal for Turbo Equalization

Channel Equalization With Expectation Propagation at Smoothing Level

Performance Analysis and Improvement for VAMP Soft Frequency-Domain Equalizers

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