Two simple stopping criteria for turbo decoding

Shao, Ran; Lin, Shu; Fossorier, M.P.C.

doi:10.1109/26.780444

Cited by 254 publications

(138 citation statements)

References 3 publications

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“…Therefore, fixing the number of decoding iterations is inefficient. Early termination schemes are widely used to accelerate the decoding process while maintaining a given BER performance [19][20][21]. As the average number of decoding iterations is reduced by using an early termination scheme, early termination can also reduce power consumption.…”

Section: Early Termination Schemementioning

confidence: 99%

Implementation of a High Throughput 3GPP Turbo Decoder on GPU

Sun

Wang

et al. 2011

J Sign Process Syst

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Turbo code is a computationally intensive channel code that is widely used in current and upcoming wireless standards. General-purpose graphics processor unit (GPGPU) is a programmable commodity processor that achieves high performance computation power by using many simple cores. In this paper, we present a 3GPP LTE compliant Turbo decoder accelerator that takes advantage of the processing power of GPU to offer fast Turbo decoding throughput. Several techniques are used to improve the performance of the decoder. To fully utilize the computational resources on GPU, our decoder can decode multiple codewords simultaneously, divide the workload for a single codeword across multiple cores, and pack multiple codewords to fit the single instruction multiple data (SIMD) instruction width. In addition, we use shared memory judiciously to enable hundreds of concurrent multiple threads while keeping frequently used data local to keep memory access fast. To improve efficiency of the decoder in the high SNR regime, we also present a low complexity early termination scheme based on average extrinsic LLR statistics. Finally, we examine how different workload partitioning choices affect the error correction performance and the decoder throughput.

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Section: Early Termination Schemementioning

confidence: 99%

Implementation of a High Throughput 3GPP Turbo Decoder on GPU

Sun

Wang

et al. 2011

J Sign Process Syst

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“…One of the first papers on stopping criteria is [11], which is based on cross entropy (CE) between the output distributions of the different decoder modules. Based on the same CE concept, Shao et al [12] introduced two simple methods called sign-change-ratio (SCR) criterion and hard-decision aided (HDA) criterion. In [13] , extending the SCR method, a new criterion named sign difference ratio (SDR) is proposed.…”

Section: Introductionmentioning

confidence: 99%

Error Rate Estimation Based on Soft Output Decoding and its Application to Turbo Coding

Strinati¹,

Simoens²,

Boutros³

2007

2007 IEEE Wireless Communications and Networking Conference

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Abstract-In this paper, we investigate reliable error rate estimation techniques for MAC layer adaptive mechanisms. In particular, we propose and analyze a novel error rate estimator based on soft output information available as output of receivers with turbo principle. Contrary to previous works on the subject, we relax the assumption of perfect knowledge of Signal-Noiseto-Ratio (SNR) at the receiver, and we analyze the impact of a SNR estimation error on the error rate estimate. We show that, differently to previous techniques, the proposed estimation method is insensitive to such SNR estimation error. Our analytical and simulation results validate the conclusion.Index Terms-Soft-output decoding, channel state estimation.

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“…Among these, the cross-entropy (CE) criterion [3,4] processes the decoder soft output, while its simpler versions sign change ratio (SCR) and harddecision aided (HDA) operate on hard decisions [4]. SCR counts the changes in sign of the estimated sequence between two consecutive iterations and declares convergence when it is less than a certain threshold.…”

mentioning

confidence: 99%

“…In practical implementations, decoders run for a fixed number of iterations: this number is determined on the basis of a worst-case analysis, although only a few frames need the entire number of iterations. An early stopping criterion would not only save unnecessary elaborations and reduce decoding latency, but increase the decoder throughput as well, or even reduce the chip complexity when the decoder architecture performs statistical multiplexing [2].Several stopping rules have been proposed in the past [3][4][5][6]. Among these, the cross-entropy (CE) criterion [3,4] processes the decoder soft output, while its simpler versions sign change ratio (SCR) and harddecision aided (HDA) operate on hard decisions [4].…”

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confidence: 99%

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Efficient stopping rule for turbo decoders

Rovini

Martinez

2006

Electron. Lett.

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A new stopping rule for turbo codes, the input-output consistency (IOC) check is presented. It is based on an extended maximum a posteriori algorithm that also outputs (hard) extrinsic estimates on the coded bits. In parallel, the hard decisions of the info bits are re-encoded and if the two sequences coincide, iterative decoding is stopped. Remarkably, IOC beats other known stopping rules in terms of error rate and convergence speed, closely approaching ideal 'Genie'-aided decoding.Introduction: Turbo codes [1] achieve low error probabilities at rates very close to Shannon's capacity limit thanks to iterative decoding. In practical implementations, decoders run for a fixed number of iterations: this number is determined on the basis of a worst-case analysis, although only a few frames need the entire number of iterations. An early stopping criterion would not only save unnecessary elaborations and reduce decoding latency, but increase the decoder throughput as well, or even reduce the chip complexity when the decoder architecture performs statistical multiplexing [2].Several stopping rules have been proposed in the past [3][4][5][6]. Among these, the cross-entropy (CE) criterion [3,4] processes the decoder soft output, while its simpler versions sign change ratio (SCR) and harddecision aided (HDA) operate on hard decisions [4]. SCR counts the changes in sign of the estimated sequence between two consecutive iterations and declares convergence when it is less than a certain threshold. Similarly, HDA terminates the iterative decoding when the hard decisions of two consecutive iterations coincide over the entire frame. A variation of SCR [5] monitors the Hamming distance of the hard decisions over two iterations to detect both early convergence and nonconvergence. In [6] the mean of the absolute log-likelihood ratio (LLR) of the info bits is monitored and decoding stops if it is greater than a preset threshold.In this Letter we present a new stopping criterion working with hard decisions and suitable for any generic iterative decoder. Crucial to this rule is the availability at the decoder of the maximum a posteriori (MAP) estimate of the channel code bits.

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Two simple stopping criteria for turbo decoding

Cited by 254 publications

References 3 publications

Implementation of a High Throughput 3GPP Turbo Decoder on GPU

Implementation of a High Throughput 3GPP Turbo Decoder on GPU

Error Rate Estimation Based on Soft Output Decoding and its Application to Turbo Coding

Efficient stopping rule for turbo decoders

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