Iterative Receiver Design for ISI Channels Using Combined Belief- and Expectation-Propagation

Sun, Peng; Zhang, Chuanzong; Wang, Zhongyong; Manchón, Carles Navarro; Fleury, Bernard Henri

doi:10.1109/lsp.2015.2404822

Cited by 33 publications

(78 citation statements)

References 8 publications

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“…Note that the BEP and KSEP are depicted with the same marker as they exhibit the same BER [12]. Also, we simulate the BP-EP proposal [13] until convergence, resulting T " 8 (K " 9) for 64-QAM and T " 11 (K " 12) for 128-QAM, in dotted lines. Finally, we include (in solid) the BER for the double-EP solutions proposed: D-BEP (˝), D-FEP (˛) and D-KSEP (˝).…”

Section: Resultsmentioning

confidence: 99%

“…Furthermore, it exhibits a significant reduction in complexity. Finally, we include some experimental results to show the improvements of this novel double EP equalizer with respect to the others found in the literature [9]- [13]. These experiments also include a comparison between the three different implementations (block, WF and KS) of an EP-based equalizer after averaging over different random channels.…”

Section: Introductionmentioning

confidence: 97%

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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: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 97%

A Double EP-Based Proposal for Turbo Equalization

Santos

Murillo-Fuentes

Arias-de-Reyna

2020

IEEE Signal Process. Lett.

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“…Inputs: ppu k q for k " 1, ..., N and y k for k " 1, ..., N`L 1) Initialization: compute t r1s k pu k q " Proj G rppu k qs. for ℓ " 1, ..., S do 2) Run Algorithm 1 with t rℓs k pu k q to obtain q rℓs E pu k q, for k " 1, ..., N. pu k q to the decoder for k " 1, ..., N expectation propagation (BP-EP) [24] or SEP [11]. The BP-EP uses a window of size L and applies the EP to better approximate with Gaussians the discrete information at the output of the channel decoder.…”

Section: Algorithm 3 Kalman Smoothing Ep (Ksep) Equalizermentioning

confidence: 99%

“…In this framework of smoothing equalizers, in [24], [25] the EP was applied to better exploit the information fed back from the channel decoder in turbo equalization. However, this approach degrades when used for higher order modulations since no suitable control of negative variances is used, a minimum allowed variance is not set and no damping procedure is included.…”

Section: Introductionmentioning

confidence: 99%

“…Finally, we review the forgetting factor used at the damping procedure. As a result, better gains in terms of bit error rate (BER) are achieved, the convergence in turbo equalization is more robust compared to the one of the equalizers in [11], [24] and the computational complexity yields quadratic in the channel length, i.e., the one of the Kalman smoothing solution.…”

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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A low complexity OFDM receiver with combined GAMP and MF message passing

et al. 2018

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With a unified belief propagation (BP) and mean field (MF) framework, we propose an iterative message passing receiver, which performs joint channel state and noise precision (the reciprocal of noise variance) estimation and decoding for OFDM systems. The recently developed generalized approximate message passing (GAMP) is incorporated to the BP-MF framework, where MF is used to handle observation factor nodes with unknown noise precision and GAMP is used for channel estimation in the time-frequency domain. Compared to state-of-the-art algorithms in the literature, the proposed algorithm either delivers similar performance with much lower complexity, or delivers much better performance with similar complexity. In addition, the proposed algorithm exhibits fastest convergence.

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Iterative Receiver Design for ISI Channels Using Combined Belief- and Expectation-Propagation

Cited by 33 publications

References 8 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

A low complexity OFDM receiver with combined GAMP and MF message passing

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