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bidirectional decoding OF CONVOLUTIONAL-CODES FOR INDOOR CELLULAR RADIO

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 1994年第2期43卷 264-269页

作者： DESPINS, CL BELZILE, J HACCOUN, D UNIV QUEBEC ECOLE TECHNOL SURER DEPT ELECT ENGN MONTREAL H2T 2C8 PQ CANADA ECOLE POLYTECH DEPT ELECT & COMP ENGN MONTREAL H3C 3A7 QUEBEC CANADA

bidirectional suboptimal breadth-first decoding of convolutional codes is an attractive technique for slowly varying and quasi-static fading channels as it restricts the extent of decoding errors due to correct path loss to very heavy noise or interference regions. This paper compares the performance of such a decoding scheme to the Viterbi algorithm over wide-band TDMA indoor radio links where equalization and space diversity are also used to combat dispersive fading and cochannel interference. On the basis of equal computational complexity and equal decoding delay, suboptimal, breadth-first, bidirectional decoding of a long constraint length convolutional code is shown to be superior to Viterbi decoding of a shorter constraint length code. Furthermore, this advantage increases as the outage criterion (in terms of bit error rate) becomes more stringent which makes bidirectional decoding particularly attractive for data applications and makes channel coding a more attractive alternative to increasing the space diversity order at the receiver.

关键词： convolutional codes decoding diversity reception fading mobile radio systems radio links telecommunication channels time division multiple access Viterbi algorithm bidirectional decoding bit error rate channel coding cochannel interference computational

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Exploiting reverse target-side contexts for neural machine translation via asynchronous bidirectional decoding

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ARTIFICIAL INTELLIGENCE 2019年 277卷 103168-000页

作者： Su, Jinsong Zhang, Xiangwen Lin, Qian Qin, Yue Yao, Junfeng Liu, Yang Xiamen Univ Xiamen 361005 Fujian Peoples R China Tsinghua Univ Beijing 100084 Peoples R China

Based on a unified encoder-decoder framework with attentional mechanism, neural machine translation (NMT) models have attracted much attention and become the mainstream in the community of machine translation. Generally, the NMT decoders produce translation in a left-to-right way. As a result, only left-to-right target-side contexts from the generated translations are exploited, while the right-to-left target-side contexts are completely unexploited for translation. In this paper, we extend the conventional attentional encoder-decoder NMT framework by introducing a backward decoder, in order to explore asynchronous bidirectional decoding for NMT. In the first step after encoding, our backward decoder learns to generate the target-side hidden states in a right-to-left manner. Next, in each timestep of translation prediction, our forward decoder concurrently considers both the source-side and the reverse target-side hidden states via two attention models. Compared with previous models, the innovation in this architecture enables our model to fully exploit contexts from both source side and target side, which improve translation quality altogether. We conducted experiments on NIST Chinese-English, WMT English-German and Finnish-English translation tasks to investigate the effectiveness of our model. Experimental results show that (1) our improved RNN-based NMT model achieves significant improvements over the conventional RNNSearch by 1.44/-3.02, 1.11/-1.01, and 1.23/-1.27 average BLEU and TER points, respectively;and (2) our enhanced Transformer outperforms the standard Transformer by 1.56/-1.49, 1.76/-2.49, and 1.29/-1.33 average BLEU and TER points, respectively. (C). 2019 Elsevier B.V. All rights reserved.

关键词： Neural machine translation bidirectional decoding Attention mechanism

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BDCore: bidirectional decoding with Co-graph Representation for Joint Entity and Relation Extraction

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KNOWLEDGE-BASED SYSTEMS 2024年 294卷

作者： Zeng, Daojian Zhao, Chao Li, Dongye Dai, Jianhua Hunan Normal Univ Hunan Prov Key Lab Intelligent Comp & Language Inf Changsha Peoples R China Changsha Univ Sci & Technol Sch Comp & Commun Engn Changsha Peoples R China

Relation extraction has become a crucial step for the automatic construction of Knowledge Graph (KG). Recently, researchers leverage Sequence-to-Sequence (Seq2Seq) models for Joint Entity and Relation Extraction (JERE). Nevertheless, traditional decoding methods entail the generation of the target sequence incrementally from left to right by the decoder, without the ability to revise earlier predictions when errors occur. This limitation becomes evident when decoding errors manifest prior to the current decoding step. Furthermore, the interrelations among triplets originating from the same sentence exhibit a robust correlation, which has been overlooked. In this paper, we propose B idirectional D ecoding with Co -graph re presentation (BDCore) to address the issues mentioned above. Specifically, we first introduce a backward decoder to decode the target sequence in a reverse order. Then, the forward decoder introduces two attention mechanisms to simultaneously considering the hidden states of the encoder and the backward decoder. Thus, the backward decoding information helps to alleviate the negative impact of the forward decoding errors. Besides, we construct a relation co-occurrence graph (Co-graph) and exploit Graph Convolutional Network (GCN) to capture the relation correlation. The extensive experiments demonstrate the benefits of the proposed bidirectional decoding and co-graph representation for relation extraction. Compared to the previous methods, our approach significantly outperforms the baselines on the NYT benchmark.

关键词： Joint relation extraction bidirectional decoding Seq2Seq Graph Convolutional Network Backward decoder

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bidirectional sequential decoding

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IEEE TRANSACTIONS ON INFORMATION THEORY 1997年第4期43卷 1319-1326页

作者： Kallel, S Li, KP Department of Electrical Engineering University of British Columbia Vancouver BC Canada

The main drawback of sequential decoding is the variability of its decoding effort which could cause decoding erasures. We propose and analyze in this correspondence an efficient bidirectional sequential decoding (BSD) technique to alleviate this drawback. In the proposed BSD, two decoders are used;one is called a forward decoder (FD), and is used to search the tree from forward direction;while the other is called a backward decoder (ED), and is used for the backward search of the tree. Forward decoding and backward decoding are performed simultaneously, and stop whenever FD and ED merge at a common encoder state somewhere in the tree. The relationships between backward coding and forward coding are examined in detail. Good rate 1/2 convolutional codes, with memory m ranging from 2 to 25, suitable for bidirectional decoding found through extensive computer search, are provided. These codes possess the same distance properties from both forward and backward directions. It is found by means of extensive computer simulations as well as a heuristic argument that the advantage of BSD appears as a substantial decrease of the computational variability of sequential decoding. Our findings suggest that the Pareto exponent of unidirectional sequential decoding (USD) can be practically doubled by using BSD.

关键词： bidirectional decoding computational variability convolutional coding sequential decoding symmetric code

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bidirectional syndrome decoding for binary rate (n-1)/n convolutional codes

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 1998年第3期E81A卷 510-513页

作者： Tajima, M Takida, K Kawasaki, Z Toyama Univ Fac Engn Dept Intellectual Informat Syst Engn Toyama 9308555 Japan

The structure of bidirectional syndrome decoding for binary rate (n-1)/n convolutional codes is investigated. It is shown that for backward decoding based on the trellis of a syndrome former H-T, the syndrome sequence must be generated in time-reversed order using an extra syndrome former H*(T), where H* is a generator matrix of the reciprocal dual code of the original code. It is also shown that if the syndrome bits are generated once and only once using H-T and H*(T): then the corresponding two error sequences have the intersection of v(1) x n error symbols, where v(1) is the memory length of H-T.

关键词： bidirectional decoding syndrome decoding syndrome former convolutional code reciprocal dual code

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Adaptive graph transformer with future interaction modeling for multi-agent trajectory prediction

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KNOWLEDGE-BASED SYSTEMS 2025年 316卷

作者： Chen, Xiaobo Wang, Junyu Deng, Fuwen Li, Zuoyong Shandong Technol & Business Univ Sch Comp Sci & Technol Yantai 264005 Peoples R China Minjiang Univ Sch Comp & Big Data Fuzhou 350121 Peoples R China

Forecasting the trajectories of traffic agents is essential for autonomous systems such as self-driving cars and social robots to guarantee safety in crowded scenarios. Capturing social interactions between agents and generating informative future features bring great challenges to accurate trajectory prediction. To this end, this paper proposes a novel multi-agent trajectory prediction model called AGTFI based on the adaptive graph transformer and future interaction modeling. First, an adaptive graph transformer (AGT) proficient at extracting node and edge features is introduced to capture the complex social interactions between traffic agents. Moreover, a two-stage prediction approach is devised where the first stage is devoted to generating pre-estimated future motion features by bidirectional corrected GRU (BCGRU) and the second stage further incorporates future social interactions into BCGRU to reduce prediction errors. Quantitative and qualitative evaluations of AGTFI on benchmark datasets, including ETH-UCY, SDD, and INTERACTION demonstrate the effectiveness of our model. Ablation studies are conducted to verify the rationale behind the model components.

关键词： Trajectory prediction Graph transformer Attention mechanism bidirectional decoding

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bidirectional Fano Algorithm for High Throughput Sequential decoding

Bidirectional Fano Algorithm for High Throughput Sequential ...

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20th IEEE Symposium on Personal, Indoor and Mobile Radio Communications

作者： Xu, Ran Kocak, Taskin Woodward, Graeme Morris, Kevin Dolwin, Craig Univ Bristol Ctr Commun Res Merchant Venturers Bldg Bristol Avon England Toshiba Res Europe Ltd Telecomm Res Lab Queens Square Bristol Avon England

ISBN: (纸本)9781424451234

Various techniques, such as bidirectional search, have been employed in sequential decoding to reduce the decoding delay. In this paper, a bidirectional Fano algorithm (BFA) is proposed, in which a forward decoder (FD) and a backward decoder (BD) search in the opposite direction simultaneously. It is shown that the proposed BFA can reduce the average decoding delay by at least 50% compared to the unidirectional Fano algorithm (UFA). Due to the reduction in the variability of the computational effort by using bidirectional search, there is even higher decoding throughput improvement at low signal-to-noise-ratio (SNR). For example at Eb/No=3dB, there is 300% throughput improvement by using the BFA decoding compared to the conventional UFA decoding. The proposed BFA decoding technique can be employed in very high throughput wireless communication systems with low hardware complexity and power consumption.

关键词： bidirectional decoding Fano algorithm high throughput decoding sequential decoding

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Two decoding algorithms for tailbiting codes

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IEEE TRANSACTIONS ON COMMUNICATIONS 2003年第10期51卷 1658-1665页

作者： Shao, RY Lin, S Fossorier, MPC Maxtor Corp Shrewsbury MA 01545 USA Univ Calif Davis Dept Elect & Comp Engn Davis CA 95616 USA Univ Hawaii Manoa Dept Elect Engn Honolulu HI 96822 USA

This paper presents two efficient Viterbi decoding-based suboptimal algorithms for tailbiting codes. The first algorithm, called the wrap-around Viterbi algorithm. (WAVA), falls into the circular decoding category. It processes the tailbiting trellis iteratively, explores the initial state of the transmitted sequence through continuous Viterbi decoding, and improves the decoding decision with iterations. A sufficient condition for the decision to be optimal is derived. For long tailbiting codes, the WAVA gives essentially optimal performance with about one round of Viterbi trial. For short- and medium-length tailbiting codes, simulations show that the WAVA achieves closer-to-optimum performance with fewer decoding stages compared with the other suboptimal circular decoding algorithms. The second algorithm, called the bidirectional Viterbi algorithm (BVA), employs two Wrap-around Viterbi decoders to process the tailbiting trellis from both ends in opposite directions. The surviving paths from the two decoders are combined to form composite paths once the decoders meet in the middle of the trellis. The composite paths at each stage thereafter serve as candidates for decision update. The bidirectional process improves the error performance and shortens the decoding latency of the unidirectional decoding with additional storage and computation requirements. Simulation results show that both proposed algorithms effectively achieve practically optimum performance for tailbiting codes of any length.

关键词： bidirectional decoding circular decoding tailbiting codes tailbiting trellises Viterbi algorithm

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Weakly Symmetric Fix-Free Codes

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IEEE TRANSACTIONS ON INFORMATION THEORY 2014年第9期60卷 5500-5515页

作者： Aghajan, Adel Khosravifard, Mohammadali Isfahan Univ Technol Dept Elect & Comp Engn Esfahan *** Iran

bidirectional decoding improves the error resilience of the fix-free codes, which is important in some applications like video coding. However, in general, two separate decoders must be designed for forward and backward decoding and hence, the cost of decoding is almost doubled. For the symmetric fix-free codes, although the forward and backward decoders are the same, the redundancy could be much greater than the case of asymmetric fix-free codes. In this paper, a class of fix-free codes, called weakly symmetric, is studied. A code is weakly symmetric if the reverse of each codeword itself is a codeword. This imposes a much weaker constraint on the codewords than what is necessitated by the symmetric codes, i.e., each codeword must be equal to its reverse. We show that the forward and backward decoders of a weakly symmetric fix-free code are essentially the same. In addition, it is shown that two significant sufficient conditions for the existence of asymmetric fix-free codes are also applicable to the case of weakly symmetric fix-free codes. As a result, we conclude that for any memoryless source, the redundancy of the optimal weakly symmetric fix-free code is at most 1.0817 bits. Moreover, it can be only 0.8 bit greater than the redundancy of the Huffman code in the worst case. In summary, weakly symmetric fix-free codes can be regarded as an option by which one can to some extent achieve the low redundancy of asymmetric fix-free codes and the low-cost bidirectional decoding of symmetric fix-free codes, simultaneously.

关键词： Symmetric fix-free codes asymmetric fix-free codes bidirectional decoding redundancy Kraft sum

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Convolutional Codes with Optimum bidirectional Distance Profile

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PROBLEMS OF INFORMATION TRANSMISSION 2023年第3期59卷 181-203页

作者： Stanojevic, I. Senk, V. Univ Novi Sad Fac Tech Sci Novi Sad Serbia

We define the bidirectional distance profile (BDP) of a convolutional code as the minimum of the distance profiles of the code and its corresponding "reverse" code. We present tables of codes with the optimum BDP (OBDP), which minimize the average complexity of bidirectional sequential decoding algorithms. The computer search is accelerated by the facts that optimum distance profile (ODP) codes of larger memory must have ODP codes of smaller memory as their "prefixes", and that OBDP codes can be obtained by "concatenating" ODP and reverse ODP codes of smaller memory. We compare the performance of OBDP codes and other codes by simulation.

关键词： convolutional codes distance profile bidirectional decoding

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