A comparative study on the modified Max-Log-MAP turbo decoding by extrinsic information scaling

Taskaldiran, Mustafa; Morling, R.C.S.; Kale, I.

doi:10.1109/wts.2007.4563294

Cited by 13 publications

(2 citation statements)

References 8 publications

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“…Since, practical Turbo codes rely on finite blocks, extrinsic and intrinsic pieces of information become more and more correlated with successive iterations. It has been proposed in [12], [13], [14] that a reasonable gain can be achieved in the waterfall region just by scaling the extrinsic information. Proper scaling yields enhanced extrinsic information thereby improving the error rate performance in the waterfall region.…”

Section: B Fast Forced Symbol Methods (Ffsm)mentioning

confidence: 99%

Space Time Turbo Codes assisted by Fast Forced Symbol Method

Sattar

Ould-Cheikh-Mouhamedou

Alsanie

et al. 2011

2011 50th FITCE Congress - "ICT: Bridging an Ever Shifting Digital Divide"

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The recent advancement in the computational power made it possible to use the powerful error correcting codes such as the turbo codes with the Space-Time Coding (STC) to provide both coding gain and diversity gain to the wireless communication systems to improve the error rate performance at very low signal-to-noise ratios (SNRs). In this paper, we propose a technique to improve the error rate performance of the SpaceTime Turbo Codes (ST-TCs) which does not require any significant change in the design of the existing encoder and the decoder. Usually, to improve the error rate performance of the ST-TC, an increase in diversity order (i.e., increase in the number of antennas) of the communication system is required. Unfortunately, this does not only increase the decoding complexity exponentially but also it requires major changes in the design of the encoder and the decoder. The proposed ST-TC is assisted by a novel Fast Forced Symbol Method (FFSM) which significantly improves the coding gain of the standard ST-TC.

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Section: B Fast Forced Symbol Methods (Ffsm)mentioning

confidence: 99%

Space Time Turbo Codes assisted by Fast Forced Symbol Method

Sattar

Ould-Cheikh-Mouhamedou

Alsanie

et al. 2011

2011 50th FITCE Congress - "ICT: Bridging an Ever Shifting Digital Divide"

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“…As a simple and highly effective solution to mitigate such potential issues, belief damping [19], [44], which prevents the algorithm from converging to local minima and belief scaling [25], [26], [45], which controls convergence speed, have been proposed. In this subsection, we propose an extension of ASB [25], [26], a belief scaling method designed for the Bayesian linear inference via low-complexity MP algorithms, to BIPs to further improve the convergence property of the JCDE algorithm via BiGaBP.…”

Section: Design Of Asb For Jcde Via Bigabpmentioning

confidence: 99%

Bilinear Gaussian Belief Propagation for Massive MIMO Detection With Non-Orthogonal Pilots

Ito,

Takahashi,

Ibi

et al. 2024

IEEE Trans. Commun.

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We propose a novel joint channel and data estimation (JCDE) algorithm via bilinear Gaussian belief propagation (BiGaBP) for massive multi-user MIMO (MU-MIMO) systems with non-orthogonal pilot sequences. The contribution aims to reduce significantly the communication overhead required for channel acquisition by enabling the use of short non-orthogonal pilots, while maintaining multi-user detection (MUD) capability. Bilinear generalized approximate message passing (BiGAMP), which is systematically derived by extending approximate message passing (AMP) to the bilinear inference problem (BIP), provides computationally efficient approximate implementations of large-scale JCDE via sum-product algorithm (SPA); however, as the pilot length decreases, the estimation accuracy is severely degraded. To tackle this issue, the proposed BiGaBP algorithm generalizes BiGAMP by relaxing its dependence on the largesystem limit approximation and leveraging the belief propagation (BP) concept. In addition, a novel belief scaling method complying with the data detection accuracy for each iteration step is designed to avoid the divergence behavior of iterative estimation in the early iterations due to the use of non-orthogonal pilots, especially in insufficient large-system conditions. Simulation results show that the proposed method outperforms the state-of-the-art schemes and approaches the performance of idealized (genieaided) scheme in terms of mean square error (MSE) and bit error rate (BER) performances.

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