Joint Nonlinear Channel Equalization and Soft LDPC Decoding With Gaussian Processes

Olmos, Pablo M.; Murillo-Fuentes, Juan José; Pérez-Cruz, Fernando

doi:10.1109/tsp.2009.2034941

Cited by 33 publications

(29 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Adaptive nonlinear equalizers have been proposed in [4], [5], where a-priori channel knowledge is not required. In [6], joint equalization and channel decoding is performed using Gaussian processes. To take advantage of the channel coding gain, iterative turboequalization structures have also been considered [7], [8].…”

Section: Introductionmentioning

confidence: 99%

Iterative Predistortion of the Nonlinear Satellite Channel

Deleu

Dervin

Kasai

et al. 2014

IEEE Trans. Commun.

View full text Add to dashboard Cite

Abstract-Digital Video Broadcasting -Satellite -Second Generation (DVB-S2) is the current European standard for satellite broadcast and broadband communications. It relies on high order modulations up to 32-amplitude/phase-shift-keying (APSK) in order to increase the system spectral efficiency. Unfortunately, as the modulation order increases, the receiver becomes more sensitive to physical layer impairments, and notably to the distortions induced by the power amplifier and the channelizing filters aboard the satellite. Pre-distortion of the non-linear satellite channel has been studied for many years. However, the performance of existing pre-distortion algorithms generally becomes poor when high-order modulations are used on a non-linear channel with a long memory. In this paper, we investigate a new iterative method that pre-distorts blocks of transmitted symbols so as to minimize the Euclidian distance between the transmitted and received symbols. We also propose approximations to relax the pre-distorter complexity while keeping its performance acceptable.

show abstract

Section: Introductionmentioning

confidence: 99%

Iterative Predistortion of the Nonlinear Satellite Channel

Deleu

Dervin

Kasai

et al. 2014

IEEE Trans. Commun.

View full text Add to dashboard Cite

show abstract

“…There, significant AM-AM and AM-PM nonlinear distortion occurs on the RF waveform, which can severely degrade the decoding performance at the receiver. Previously presented approaches include using nonequiprobable distribution of signal constellation [4], predistorting the signal before the nonlinear amplifier [5], and joint channel equalization and soft decoding [6]. Some of these imply significant increase in complexity, or incompatibility with DVB-S2.…”

Section: Introductionmentioning

confidence: 99%

Improving Decoding Performance of DVB-S2 Transmission on a Nonlinear Channel

Peng²,

Wilson³

et al. 2013

31st AIAA International Communications Satellite Systems Conference

View full text Add to dashboard Cite

Single-user coded 16-APSK transmission is studied from the perspective of achievable information rate and channel simulation, in the context of DVB-S2 over a nonlinear satellite channel. Achievable information rates are calculated as a function of downlink SNR and input backoff for the nonlinear amplifier, for both a memoryless end-to-end model and for a model with memory-order two. These provide benchmarks for real decoder simulations, and it is shown that achievable rate calculations are highly-predictive of actual performance and of proper IBO. We also show modification to the constellation ring ratio can provide significant savings in SNR, at least for the adopted nonlinear Saleh model. Finally, a two-pass decoding that employs hard-decision feedback from the LDPC decoder is able to gain another 0.4 dB in performance without significant complexity increase. This gain is predicted by our achievable rate analysis.

show abstract

“…Recently, Chi et al put forward a Bayesian blind detector that, considering only the channel distribution information, jointly faces the tasks of data detection and channel estimation in a MIMO system [21]. Finally, in [22] we introduce a nonlinear nonparametric equalizer to provide accurate symbol-by-symbol estimates with good performance at the output of a LDPC decoder.…”

Section: Introductionmentioning

confidence: 99%

“…Nevertheless, the proposed approach does not have an analytical description and cannot be computed in linear-time in the number of symbols as the BCJR algorithm, thus we also propose an approximation to the Bayesian solution, hereafter referred to as the approximate Bayesian equalizer (ABE), that presents the same complexity as the ML-BCJR solution, but it is able to retain most of the gain of the full Bayesian approach. Compared to the solution in [22], the BE is parametric, it provides the posterior probability for linear channels and, most important, its computational complexity is identical to the BCJR equalizer. Some preliminary results were presented in [24], [25].…”

Section: Introductionmentioning

confidence: 99%

Bayesian Equalization for LDPC Channel Decoding

Salamanca

Murillo-Fuentes

Pérez-Cruz

2012

IEEE Trans. Signal Process.

View full text Add to dashboard Cite

Abstract-We describe the channel equalization problem and its prior estimate of the channel estate information (CSI), as a joint Bayesian estimation problem to improve each symbol posterior estimates at the input of the channel decoder. Our solution takes into consideration not only the uncertainty due to the noise in the channel, but also the uncertainty in the CSI estimate. The marginalization to compute each posterior from the full posterior cannot be computed in linear time, because it depends on all the transmitted symbols. Hence, we also put forward an approximate posterior, inspired by the BCJR algorithm, which is optimal from the Kullback-Leibler divergence viewpoint and presents a complexity identical to the BCJR algorithm. We also use a graphical model representation of the full posterior, in which the proposed approximation can be readily understood. The proposed posterior estimates are more accurate than those computed using the ML estimate for the CSI. To illustrate this point, we measure the bit error rate at the output of a Low-Density Parity-Check decoder, which needs the exact posterior for each symbol to detect the incoming word and it is sensitive to a mismatch in those posterior estimates.

show abstract

Joint Nonlinear Channel Equalization and Soft LDPC Decoding With Gaussian Processes

Cited by 33 publications

References 29 publications

Iterative Predistortion of the Nonlinear Satellite Channel

Iterative Predistortion of the Nonlinear Satellite Channel

Improving Decoding Performance of DVB-S2 Transmission on a Nonlinear Channel

Bayesian Equalization for LDPC Channel Decoding

Contact Info

Product

Resources

About