Efficient unequal error protection for online fountain codes

In this paper,an efficient unequal error protection(UEP)scheme for online fountain codes is proposed.In the buildup phase,the traversing-selection strategy is proposed to select the most important symbols(MIS).Then,in the completion phase,the weighted-selection strategy is applied to provide low overhead.The performance of the proposed scheme is analyzed and compared with the existing UEP online fountain scheme.Simulation results show that in terms of MIS and the least important symbols(LIS),when the bit error ratio is 10-4,the proposed scheme can achieve 85%and 31.58%overhead reduction,respectively.

CodeScore-R:用于评估代码合成功能准确性的自动化鲁棒指标

评估指标在代码合成领域中至关重要.常用的代码评估指标可以分为3种类型:基于匹配、基于语义和基于执行.其中,基于执行的Pass@k指标通过执行测试用例,能够准确判断预测代码的功能准确性.然而,该指标的计算需要大量开销,因此亟需设计一种自动化评估指标,在无需测试用例时仍可评估预测代码的功能准确性.此外,好的评估指标应当具有鲁棒性,即预测代码发生微小改变时,评估指标仍能保持其准确性.为此,提出了一种基于UniXcoder和对比学习的自动化鲁棒指标CodeScore-R,用于评估代码合成的功能准确性. CodeScore-R采用草图化处理、语法等价转换和变异测试等技术手段,有效减轻了标识符、语法结构和运算符对评估结果的干扰.实验结果表明,在Java和Python语言上的代码生成和迁移任务中,CodeScore-R的表现优于其他无需测试用例的评估指标,且更接近Pass@k指标,并具有更强的鲁棒性.

Improved Belief Propagation Decoder for LDPC-CRC-Polar Codes with Bit-Freezing

Though belief propagation bit-flip(BPBF)decoding improves the error correction performance of polar codes,it uses the exhaustive flips method to achieve the error correction performance of CA-SCL decoding,thus resulting in high decoding complexity and latency.To alleviate this issue,we incorporate the LDPC-CRC-Polar coding scheme with BPBF and propose an improved belief propagation decoder for LDPC-CRC-Polar codes with bit-freezing(LDPCCRC-Polar codes BPBFz).The proposed LDPCCRC-Polar codes BPBFz employs the LDPC code to ensure the reliability of the flipping set,i.e.,critical set(CS),and dynamically update it.The modified CS is further utilized for the identification of error-prone bits.The proposed LDPC-CRC-Polar codes BPBFz obtains remarkable error correction performance and is comparable to that of the CA-SCL(L=16)decoder under medium-to-high signal-to-noise ratio(SNR)regions.It gains up to 1.2dB and 0.9dB at a fixed BLER=10-4compared with BP and BPBF(CS-1),respectively.In addition,the proposed LDPC-CRC-Polar codes BPBFz has lower decoding latency compared with CA-SCL and BPBF,i.e.,it is 15 times faster than CA-SCL(L=16)at high SNR regions.

Doped low-density parity-check codes

In this paper,we propose a doping approach to lower the error floor of Low-Density Parity-Check(LDPC)codes.The doping component is a short block code in which the information bits are selected from the coded bits of the dominant trapping sets of the LDPC code.Accordingly,an algorithm for selecting the information bits of the short code is proposed,and a specific two-stage decoding algorithm is presented.Simulation results demonstrate that the proposed doped LDPC code achieves up to 2.0 dB gain compared with the original LDPC code at a frame error rate of 10^(-6)Furthermore,the proposed design can lower the error floor of original LDPC Codes.

Blind Recognition of Non-Binary LDPC Codes Based on Ant Colony Optimization

This paper introduces a novel blind recognition of non-binary low-density parity-check(LDPC)codes without a candidate set,using ant colony optimization(ACO)algorithm over additive white Gaussian noise(AWGN)channels.Specifically,the scheme that effectively combines the ACO algorithm and the non-binary elements over finite fields is proposed.Furthermore,an improved,simplified elitist ACO algorithm based on soft decision reliability is introduced to recognize the parity-check matrix over noisy channels.Simulation results show that the recognition rate continuously increases with an increased signalto-noise ratio(SNR)over the AWGN channel.

Quantized Decoders that Maximize Mutual Information for Polar Codes

In this paper,we innovatively associate the mutual information with the frame error rate(FER)performance and propose novel quantized decoders for polar codes.Based on the optimal quantizer of binary-input discrete memoryless channels(BDMCs),the proposed decoders quantize the virtual subchannels of polar codes to maximize mutual information(MMI)between source bits and quantized symbols.The nested structure of polar codes ensures that the MMI quantization can be implemented stage by stage.Simulation results show that the proposed MMI decoders with 4 quantization bits outperform the existing nonuniform quantized decoders that minimize mean-squared error(MMSE)with 4 quantization bits,and yield even better performance than uniform MMI quantized decoders with 5 quantization bits.Furthermore,the proposed 5-bit quantized MMI decoders approach the floating-point decoders with negligible performance loss.

Application of maximum rank distance codes in designing of STBC-OFDM system for next-generation wireless communications

Space-Time Block Coded(STBC)Orthogonal Frequency Division Multiplexing(OFDM)satisfies higher data-rate requirements while maintaining signal quality in a multipath fading channel.However,conventional STBCs,including Orthogonal STBCs(OSTBCs),Non-Orthogonal(NOSTBCs),and Quasi-Orthogonal STBCs(QOSTBCs),do not provide both maximal diversity order and unity code rate simultaneously for more than two transmit antennas.This paper targets this problem and applies Maximum Rank Distance(MRD)codes in designing STBCOFDM systems.By following the direct-matrix construction method,we can construct binary extended finite field MRD-STBCs for any number of transmitting antennas.Work uses MRD-STBCs built over Phase-Shift Keying(PSK)modulation to develop an MRD-based STBC-OFDM system.The MRD-based STBC-OFDM system sacrifices minor error performance compared to traditional OSTBC-OFDM but shows improved results against NOSTBC and QOSTBC-OFDM.It also provides 25%higher data-rates than OSTBC-OFDM in configurations that use more than two transmit antennas.The tradeoffs are minor increases in computational complexity and processing delays.

Decoding topological XYZ^(2) codes with reinforcement learning based on attention mechanisms

Quantum error correction, a technique that relies on the principle of redundancy to encode logical information into additional qubits to better protect the system from noise, is necessary to design a viable quantum computer. For this new topological stabilizer code-XYZ^(2) code defined on the cellular lattice, it is implemented on a hexagonal lattice of qubits and it encodes the logical qubits with the help of stabilizer measurements of weight six and weight two. However topological stabilizer codes in cellular lattice quantum systems suffer from the detrimental effects of noise due to interaction with the environment. Several decoding approaches have been proposed to address this problem. Here, we propose the use of a state-attention based reinforcement learning decoder to decode XYZ^(2) codes, which enables the decoder to more accurately focus on the information related to the current decoding position, and the error correction accuracy of our reinforcement learning decoder model under the optimisation conditions can reach 83.27% under the depolarizing noise model, and we have measured thresholds of 0.18856 and 0.19043 for XYZ^(2) codes at code spacing of 3–7 and 7–11, respectively. our study provides directions and ideas for applications of decoding schemes combining reinforcement learning attention mechanisms to other topological quantum error-correcting codes.

Recurrent neural network decoding of rotated surface codes based on distributed strategy

Quantum error correction is a crucial technology for realizing quantum computers.These computers achieve faulttolerant quantum computing by detecting and correcting errors using decoding algorithms.Quantum error correction using neural network-based machine learning methods is a promising approach that is adapted to physical systems without the need to build noise models.In this paper,we use a distributed decoding strategy,which effectively alleviates the problem of exponential growth of the training set required for neural networks as the code distance of quantum error-correcting codes increases.Our decoding algorithm is based on renormalization group decoding and recurrent neural network decoder.The recurrent neural network is trained through the ResNet architecture to improve its decoding accuracy.Then we test the decoding performance of our distributed strategy decoder,recurrent neural network decoder,and the classic minimum weight perfect matching(MWPM)decoder for rotated surface codes with different code distances under the circuit noise model,the thresholds of these three decoders are about 0.0052,0.0051,and 0.0049,respectively.Our results demonstrate that the distributed strategy decoder outperforms the other two decoders,achieving approximately a 5%improvement in decoding efficiency compared to the MWPM decoder and approximately a 2%improvement compared to the recurrent neural network decoder.

Improved Segmented Belief Propagation List Decoding for Polar Codes with Bit-Flipping

Belief propagation list(BPL) decoding for polar codes has attracted more attention due to its inherent parallel nature. However, a large gap still exists with CRC-aided SCL(CA-SCL) decoding.In this work, an improved segmented belief propagation list decoding based on bit flipping(SBPL-BF) is proposed. On the one hand, the proposed algorithm makes use of the cooperative characteristic in BPL decoding such that the codeword is decoded in different BP decoders. Based on this characteristic, the unreliable bits for flipping could be split into multiple subblocks and could be flipped in different decoders simultaneously. On the other hand, a more flexible and effective processing strategy for the priori information of the unfrozen bits that do not need to be flipped is designed to improve the decoding convergence. In addition, this is the first proposal in BPL decoding which jointly optimizes the bit flipping of the information bits and the code bits. In particular, for bit flipping of the code bits, a H-matrix aided bit-flipping algorithm is designed to enhance the accuracy in identifying erroneous code bits. The simulation results show that the proposed algorithm significantly improves the errorcorrection performance of BPL decoding for medium and long codes. It is more than 0.25 d B better than the state-of-the-art BPL decoding at a block error rate(BLER) of 10^(-5), and outperforms CA-SCL decoding in the low signal-to-noise(SNR) region for(1024, 0.5)polar codes.

Polar codes based OFDM-PLC systems in the presence of impulsive noise

Power line communication(PLC)has the potential to become the preferred technique for providing broadband communication to homes and offices with advantage of eliminating the need for new wiring infrastructure and reducing the cost.But it suffers from the impulsive noise because it introduces significant time variance into the power line channel.In this paper,a polar codes based orthogonal frequency division multiplexing(OFDM)PLC system is proposed to deal with the impulsive noise and thereby improve the transmission performance.Firstly,the impulsive noise is modelled with a multi-damped sine function by analyzing the time behavior of impulse events.Then the polar codes are used to combat the impulsive noise of PLC channel,and a low complexity bit-flipping decoding method based on CRC-aided successive cancellation list(CA-SCL)decoding algorithm is proposed.Simulations evaluate the proposed decoding algorithm and the results validate the suggested polar codes based OFDM-PLC scheme which can improve the BER performance of PLC with impulsive interference.

一种规则变量节点度LT Codes编码方案

LT Codes差错平台(Erasure Floor)由变量节点的最小度决定,规则变量节点度LT Codes能够最大化变量节点的最小度,从而降低LT Codes的差错平台.该文提出一种新的规则变量节点度LT Codes编码方法,该编码方法省去了现有方法中对变量节点度值查找表的排序操作,降低了现有方案的编码复杂度;通过对度分布的修正增加低度校验节点,使得规则变量节点度LT Codes解码瀑布区域(雪崩区域)提前.仿真结果表明该文方法与现有方法相比有效减少了编码时间,降低了成功解码所需的平均传输开销,加快了误符号率收敛速度.

基于SPIHT图象压缩编码的Turbo codes编码

针对信源与信道编码的特点 ,提出了结合SPIHT(setpartitioninginhierarchicaltrees)算法和改进的TurboCodes的信源与信道联合编码方案 .这一方案充分考虑了SPIHT算法和TurboCodes的特性 ,根据信源编码后数据在重建时的重要程度 ,进行不同等纠错保护的信道编码 .实验表明 ,论文的方法能够使误码率与码长达到一个较好的平衡 。

一种改进的Turbo codes译码方法

Turbo码是一种目前研究比较多的纠错码,译码端采用了基于软判决信息输入/输出的反馈迭代结构,译码的迭代是其具有优越纠错性能的关键,也是造成其时延的问题所在,该文提出一种自适应选择迭代次数的方法,实验表明该方法能够在译码结果收敛时自动停止迭代,避免大量无谓的计算,同时保证译码的准确性。

.NET下基于PowerDesigner和CodeSmith的软件自动化开发技术

针对当前软件开发效率低下、难以快速适应需求变化等问题,提出一种新的软件自动化开发技术。在一定的约束条件下通过PowerDesigner完成数据库概念模型的设计和物理模型转换,在CodeSmith代码引擎的支持下,通过自定义的模板来实现软件代码的自动生成。有效解决了基于数据库的MIS系统的开发效率和软件质量问题。通过在实际项目中的应用表明,该技术能有效提升软件开发效率,降低开发成本。

Design of rate compatible punctured IRA codes for IR-HARQ schemes

An incremental redundancy hybrid automatic repeat- request （IR-HARQ）scheme based on irregular repeat-accumulate （IRA）codes is proposed. The design of rate compatible punctured IRA codes suitable for an IR-HARQ scheme is well formulated and efficiently solved by a linear-programming method, along with a one-dimensional approach for density evolution. Compared to IR-HARQ schemes based on turbo codes, simulation shows that the proposed IR-HARQ schemes based on IRA codes may achieve almost the same performance at a block size of 1 024, but better throughput at a block size of 4 096. The advantages of the proposed scheme in implementation, including decoding complexity and parallelism, make it more attractive in practice than the IR-HARQ schemes based on both turbo and LDPC codes.

An Efficient Test Data Compression Technique Based on Codes

This paper presents a new test data compression/decompression method for SoC testing,called hybrid run length codes. The method makes a full analysis of the factors which influence test parameters：compression ratio,test application time, and area overhead. To improve the compression ratio, the new method is based on variable-to-variable run length codes,and a novel algorithm is proposed to reorder the test vectors and fill the unspecified bits in the pre-processing step. With a novel on-chip decoder, low test application time and low area overhead are obtained by hybrid run length codes. Finally, an experimental comparison on ISCAS 89 benchmark circuits validates the proposed method

Make Full Use of Nonverbal Codes in Teaching ESP Students

Based on Larry A. Samovar’s theory and combined with my own teaching practice, this essay mainly analyzes four nonverbal codes: body behavior, silence, seating and personal space in teaching ESP students. Meanwhile, it also provides suggestions on how to make full use of them so as to direct, stimulate and encourage students in classroom activities.

Performance analysis of coded OFDM systems using a novel class of LDPC codes

A new method of constructing regular low-density parity-check (LDPC) codes was proposed. And the novel class of LDPC codes was applied in a coded orthogonal frequency division multiplexing (OFDM) system. This method extended the class of LDPC codes which could be constructed from shifted identity matrices. The method could avoid short cycles in Tanner graphs with simple inequation in the construction of shifting identity matrices, which made the girth of Tanner graphs 8. Because of the quasicyclic structure and the inherent block configuration of parity-check matrices, the encoders and the decoders were practically feasible. They were linear-time encodable and decodable. The LDPC codes proposed had various code rates, ranging from low to high. They performed excellently with iterative decoding and demonstrate better performance than other regular LDPC codes in OFDM systems.

Low complexity suboptimal decode algorithms for quasi- orthogonal space time block codes

Due to the high complexity of the pairwise decoding algorithm and the poor performance of zero forcing（ ZF） /minimum mean square error（ MMSE） decoding algorithm, two low-complexity suboptimal decoding algorithms, called pairwisequasi-ZF and pairwise-quasi-MMSE decoders, are proposed. First,two transmit signals are detected by the quasi-ZF or the quasiMMSE algorithm at the receiver. Then, the two detected signals as the decoding results are substituted into the two pairwise decoding algorithm expressions to detect the other two transmit signals. The bit error rate（ BER） performance of the proposed algorithms is compared with that of the current known decoding algorithms.Also, the number of calculations of ZF, MMSE, quasi-ZF and quasi-MMSE algorithms is compared with each other. Simulation results showthat the BER performance of the proposed algorithms is substantially improved in comparison to the quasi-ZF and quasiMMSE algorithms. The BER performance of the pairwise-quasiZF（ pairwise-quasi-MMSE） decoder is equivalent to the pairwiseZF（ pairwise-MMSE） decoder, while the computational complexity is significantly reduced.