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Model-Driven DNN Decoder for Turbo Codes: Design, Simulation, and Experimental Results

IEEE TRANSACTIONS ON COMMUNICATIONS 2020年第10期68卷 6127-6140页

作者： He, Yunfeng Zhang, Jing Jin, Shi Wen, Chao-Kai Li, Geoffrey Ye Southeast Univ Natl Mobile Commun Res Lab Nanjing 210096 Peoples R China Natl Sun Yat Sen Univ Inst Commun Engn Kaohsiung 80424 Taiwan Georgia Inst Technol Sch Elect & Comp Engn Atlanta GA 30332 USA

This paper presents a novel model-driven deep learning (DL) architecture, called TurboNet, for turbo decoding that integrates DL into the traditional max-log-maximum a posteriori (map) algorithm. The TurboNet inherits the superiority of the max-log-map algorithm and DL tools and thus presents excellent error-correction capability with low training cost. To design the TurboNet, the original iterative structure is unfolded as deep neural network (DNN) decoding units, where trainable weights are introduced to the max-log-map algorithm and optimized through supervised learning. To efficiently train the TurboNet, a loss function is carefully designed to prevent tricky gradient vanishing issue. To further reduce the computational complexity and training cost of the TurboNet, we can prune it into TurboNet+. Compared with the existing black-box DL approaches, the TurboNet+ has considerable advantage in computational complexity and is conducive to significantly reducing the decoding overhead. Furthermore, we also present a simple training strategy to address the overfitting issue, which enable efficient training of the proposed TurboNet+. Simulation results demonstrate TurboNet+'s superiority in error-correction ability, signal-to-noise ratio generalization, and computational overhead. In addition, an experimental system is established for an over-the-air (OTA) test with the help of a 5G rapid prototyping system and demonstrates TurboNet's strong learning ability and great robustness to various scenarios.

关键词： Decoding Iterative decoding Training Computer architecture Turbo codes Computational modeling Computational complexity DL turbo decoding max-log-map algorithm network pruning OTA

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Design for a turbo-code decoder using a block-wise algorithm

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IEICE TRANSACTIONS ON COMMUNICATIONS 2002年第2期E85B卷 559-564页

作者： Park, GH Yoon, SH Hong, D Kang, CE Yonsei Univ Dept Elect & Comp Engn Informat & Telecommun Lab Seodaemoon Gu Seoul 120749 South Korea LG Elect Inc LG R&D Complex 533 Mobile Comm Res Lab Dept Mobile Comm TechDongan Gu Kyeongku Do 431749 South Korea

Several implementation methods for a map decoder are proposed in this paper, Using a novel pipeline structured time-shared process, the authors are able to efficiently overcome the restrictions imposed by the recursion process on state metrics. and the complexity of the map decoder can be reduced to a level on the order of a SOVA (Soft Output Viterbi algorithm) decoder. In addition. the authors propose an efficient controller structure that can be used for variable frame-size systems such as cdma-2000. The map decoder using a block-wise algorithm designed here was implemented in only one 20,000 gate circuit. It was validated by VHDL, which was compared with the results of the initial simulation (C programs). The decoder demonstrated a 300 kbps decoding processing ability with 8 iterations on a FPGA circuit, with a deviation only about 0.1-0.2 dB greater than that for an ideal map decoder, even when all hardware environments are considered.

关键词： turbo-codes decoder map algorithm max-log-map algorithm block-wise algorithm

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The Acceleration of Turbo Decoder On The Newest GPGPU of Kepler Architecture 14

The Acceleration of Turbo Decoder On The Newest GPGPU of Kep...

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International Symposium on Communications and Information Technologies

作者： Zhang, Yang Xing, Zuocheng Yuan, Luechao Liu, Cang Wang, Qinglin Natl Univ Def Technol Sci & Technol Parallel & Distributed Proc Lab Changsha Hunan Peoples R China

ISBN: (纸本)9781479944163

In the paper, a new implementation of a 3GPP LTE standards compliant turbo decoder based on GPGPU is proposed. It uses the newest GPU-Tesla K20c, which is based on the Kepler GK110 architecture. The new architecture has more powerful parallel computing capability and we use it to fully exploit the parallelism in the turbo decoding algorithm in novel ways. Meanwhile, we use various memory hierarchies to meet various kinds of data demands on speed and capacity. Simulation shows that our implementation is practical and it gets 76% improvement on throughput over the latest GPU implementation. The result demonstrates that the newest Kepler architecture is suitable for turbo decoding and it can be a promising reconfigurable platform for the communication system.

关键词： Turbo Decoder GPGPU Kepler Parallel max-log-map algorithm

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Energy efficient turbo decoder with reduced state metric quantization

Energy efficient turbo decoder with reduced state metric qua...

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IEEE Workshop on Signal Processing Systems

作者： Liu, Haisheng Diguet, Jean-Philippe Jego, Christophe Jezequel, Michel Boutillon, Emmanuel ENST Bretagne GET CNRS TAMCICUMR 2872 Brest France Univ Bretagne Sud CNRS FRE 2734 LESTER Lorient France

ISBN: (纸本)9781424412211

In the field of mobile communications, the energy issue of a turbo decoder becomes an equivalent constraint as throughput and performance. This paper describes a technique to reduce the internal bitwidth of the state metrics, and hence, to decrease the entire energy dissipation of a turbo decoder. This approach is based on the saturation of the state metrics. Two cases are investigated: saturation outside the ACS recursion loop and saturation inside the ACS recursion loop. The targeted system is the Universal Mobile Telecommunications System (UTMTS) with an 8-state turbo decoder using the max-log-map algorithm. When received symbols and extrinsic informations are respectively 4-bit and 6-bit quantized, the internal bitwidth of the state metrics can be reduced from 7 bits downto 4 bits. This reduction is paid by a loss of 0.1 dB at a Bit Error Rate (BER) of 10(-6). In addition, when 4 SISO decoders perform in parallel, the proposed optimization yields to a reduction of memory area by 10% and leads to an energy reduction of 24% for a 70 mn technology.

关键词： turbo codes max-log-map algorithm state metric quantization energy efficient architecture

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Low-complexity BCJR decoder for turbo decoders and its VLSI implementation in 0.18-μm CMOS 62

Low-complexity BCJR decoder for turbo decoders and its VLSI ...

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62nd IEEE Vehicular Technology Conference

作者： Sabeti, L Ahmadi, M Tepe, KE Univ Windsor Dept Elect Engn Windsor ON N9B 3P4 Canada

ISBN: (纸本)0780391527

This paper proposes a low-complexity design for BCJR or maximum a posteriori (map) decoders. max-log-map algorithm, which offers a good compromise between performance and complexity, is selected for implementation. The decoder architecture is parallel and pipeline. New quantization and new branch metric calculation unit are proposed in this paper. Overall decoder design is flexible to the transmission block lengths, which makes it appropriate for variable length transmission systems. Performance results are tested on turbo decoders and show that the proposed BUR decoder is quite suitable for turbo decoders. The chip is implemented in a 0.18-mu m six-layer metal CMOS technology and has the core size of 1mm(2) (including two memories). The throughput of the turbo decoder is 6.5Mb/s after 10 iterations.

关键词： turbo coding max-log-map algorithm implementation

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A Simplified Soft-demapping Scheme for Probabilistic Constellation Shaping 59

A Simplified Soft-demapping Scheme for Probabilistic Constel...

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59th Annual IEEE International Conference on Communications (IEEE ICC)

作者： Jia, Yinhua Wu, Liangming Xu, Changlong Liu, Wei Xu, Hao Richardson, Tom Qualcomm Technol Inc San Diego CA 92121 USA

ISBN: (纸本)9798350304060;9798350304053

Probabilistic constellation shaping (PCS) improves the spectral efficiency by adjusting the probability distribution of the transmitted symbols to match the channel characteristics. The conventional log-maximum A Posteriori (log-map) algorithm can work for demodulation of PCS system by taking into account the probability of each constellation point. However, the conventional max-log-map algorithm cannot be applied directly. In this paper, a simplified soft-demapping scheme is proposed based on the max-log-map algorithm for the PCS system. The proposed scheme has a lower complexity than the logmap algorithm with acceptable performance loss. In addition, the distribution mismatch between transmitter and receiver is evaluated. The results show that four distributions are adequate for PCS-64 and PCS-256 to cover a wide range of signal-to-noise ratios.

关键词： Probabilistic constellation shaping demodulation max-log-map algorithm

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Minimal Trellis for Systematic Recursive Convolutional Encoders

Minimal Trellis for Systematic Recursive Convolutional Encod...

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IEEE International Symposium on Information Theory (ISIT)

作者： Pimentel, Cecilio Souza, Richard Demo Uchoa-Filho, Bartolomeu F. Benchimol, Isaac Univ Fed Pernambuco DES CODEC Recife PE Brazil UTFPR CPGEI Curitiba Parana Brazil Univ Fed Santa Catarina GPqCom EEL CTC Florianopolis SC Brazil IFAM CMDI Manaus Amazonas Brazil

ISBN: (纸本)9781457705953

We consider high-rate systematic recursive convolutional encoders to be adopted as constituent encoders in turbo schemes. It has been shown by Douillard and Berrou that the construction of high-rate turbo codes by means of high-rate constituent encoders offers several advantages over the typical construction based on the puncturing of rate-1/2 constituent encoders. To reduce the decoding complexity associated with high-rate codes, we adopt the "minimal" trellis representation of convolutional codes introduced by McEliece and Lin. While in the literature this trellis has been obtained for nonrecursive nonsystematic generator matrices, we herein introduce the construction of the "minimal" trellis for a systematic recursive convolutional encoding matrix. We also derive expressions for the arithmetic decoding complexity when the max-log-map algorithm is applied over the conventional and the "minimal" trellises. Examples are provided, which show that significant savings in decoding complexity are obtained, while keeping the same error performance of conventional schemes, when the minimal trellis is used. Finally, a code search is conducted and examples are provided which indicate that a refinement in terms of decoding complexity-error performance trade-off is obtained.

关键词： Complexity theory Convolutional codes Decoding Matrix decomposition Systematics Turbo codes arithmetic decoding complexity communication complexity complexity-error performance convolutional codes decoding decoding complexity high-rate turbo code matrix algebra max-log-map algorithm maximum likelihood estimation minimal trellis nonrecursive nonsystematic generator matrix recursive estimation systematic recursive convolutional encoder trellis codes turbo codes

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An Efficient FPGA-based Turbo Decoder and Its Application in FH-SS System

An Efficient FPGA-based Turbo Decoder and Its Application in...

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4th International Conference on Wireless Communications, Networking and Mobile Computing

作者： Bu, Xiang-yuan Yang, Guo-ying Liu, Ce-lun Zhou, Rong-hua Beijing Inst Technol Dept Elect Engn Beijing 100081 Peoples R China

ISBN: (纸本)9781424421077

This paper focuses on implementing an efficient and simplified turbo decoder with FPGA. The max-log-map algorithm is employed and a simplified and improved max-log-map algorithm is present. By carefully manipulating hardware, we implement the whole turbo decoder with a single-RSC structure. Comparing with the conventional decoder, our turbo decoder reduces about 60% hardware cost and operates up to 2Mbit/s. Finally, we investigate the performance of our FPGA-based turbo decoder in a FH-SS system with partial band jamming. The results drawn from this code are compared with a RS code. Results show that the turbo code significantly outperforms the RS code.

关键词： max-log-map algorithm FPGA Turbo Decoder FH-SS

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Performance Evaluation of Turbo Coded OFDM with Channel Estimation Over SUI Channel Models 9

Performance Evaluation of Turbo Coded OFDM with Channel Esti...

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9th International Symposium on Communication Systems, Networks & Digital Signal Processing (CSNDSP)

作者： Khan, Latif Ullah Mahmud, Sahibzada Ali Khan, Gul M. Zafar, M. Haseeb Univ Engn & Technol Dept Elect Engn Peshawar Pakistan

ISBN: (纸本)9781479925810

In this paper, the performance of the Least Squares (LS) estimator along with turbo codes in OFDM is evaluated for the SUI channel models in the presence of AWGN. Turbo codes are used in this paper because of its BER performance close to Shannon limit. The iterative turbo decoder exchanges soft information between the component decoders. maximum A Posteriori (map) and its simplified version max-log-map algorithms are used for the component decoders. The performance and complexity comparison is also made between the decoding algorithms. Moreover the effect of memory order on the performance of the decoding algorithms is also studied.

关键词： OFDM LS estimator map algorithm max-log-map algorithm SUI Channel Models

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A Low Complex Parallel Decoding Structure for Turbo-codes

A Low Complex Parallel Decoding Structure for Turbo-codes

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2000 International Conference on Communication Technology(WCC2000·ICCT2000)

作者： Zhang Zhongpei Zhou Liang 12th Dept.of UESTC National Commun.Lab UESTC

ISBN: (纸本)0780363949

The max-log-map(MLM) algorithm is simple for Turbo-codes' decoding, based on the algorithm a structure of parallel array for Turbo-codes decoding is suggested,which is easy to implement by *** this structure,flow direction of dates and computation process of the algorithm are obtained,the relation of nodes and date frames are analyzed,and the simple time sequencing of dates operation is *** structure is proved by simulation.

关键词： max-log-map algorithm Soft output decoding Parallel structure Array

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