Abstract： The layered decoding algorithm has been widely used in the implementation of Low Density Parity Check （LDPC） decoders, due to its high convergence speed. However, the pipeline operation of the layered dec...Abstract： The layered decoding algorithm has been widely used in the implementation of Low Density Parity Check （LDPC） decoders, due to its high convergence speed. However, the pipeline operation of the layered decoder may introduce memory access conflicts, which heavily deteriorates the decoder throughput. To essentially deal with the issue of memory access conflicts,展开更多
For quantum sparse graph codes with stabilizer formalism, the unavoidable girth-four cycles in their Tanner graphs greatly degrade the iterative decoding performance with standard belief-propagation （BP） algorithm. ...For quantum sparse graph codes with stabilizer formalism, the unavoidable girth-four cycles in their Tanner graphs greatly degrade the iterative decoding performance with standard belief-propagation （BP） algorithm. In this paper, we present a jointly-check iterative algorithm suitable for decoding quantum sparse graph codes efficiently. Numerical simulations show that this modified method outperforms standard BP algorithm with an obvious performance improvement.展开更多
It is known that Block Turbo Codes （BTC） can be nearly optimally decoded by Chase-II algorithm, in which the Least Reliable Bits （LRBs） are chosen empirically to keep the size of the test patterns （sequences） re...It is known that Block Turbo Codes （BTC） can be nearly optimally decoded by Chase-II algorithm, in which the Least Reliable Bits （LRBs） are chosen empirically to keep the size of the test patterns （sequences） relatively small and to reduce the decoding complexity. While there are also other adaptive techniques, where the decoder＇s LRBs adapt to the external parameter of the decoder like SNR （Signal Noise Ratio） level, a novel adaptive algorithm for BTC based on the statistics of an internal variable of the decoder itself is proposed in this paper. Different from the previous reported results, it collects the statistics of the multiplicity of the candidate sequences, i.e., the number of the same candidate sequences with the same minimum squared Euclidean distance resulted from the decoding of test sequences. It is shown by Monte Carlo simulations that the proposed adaptive algorithm has only about 0.02dB coding loss but the average complexity of the proposed algorithm is about 42% less compared with Pyndiah＇s iterative decoding algorithm using the fixed LRBs parameter.展开更多
Since real world communication channels are not error free, the coded data transmitted on them may be corrupted, and block based image coding systems are vulnerable to transmission impairment. So the best neighborh...Since real world communication channels are not error free, the coded data transmitted on them may be corrupted, and block based image coding systems are vulnerable to transmission impairment. So the best neighborhood match method using genetic algorithm is used to conceal the error blocks. Experimental results show that the searching space can be greatly reduced by using genetic algorithm compared with exhaustive searching method, and good image quality is achieved. The peak signal noise ratios(PSNRs) of the restored images are increased greatly.展开更多
A new method for the construction of the high performance systematic irregular low-density paritycheck （LDPC） codes based on the sparse generator matrix （G-LDPC） is introduced. The code can greatly reduce the enco...A new method for the construction of the high performance systematic irregular low-density paritycheck （LDPC） codes based on the sparse generator matrix （G-LDPC） is introduced. The code can greatly reduce the encoding complexity while maintaining the same decoding complexity as traditional regular LDPC （H-LDPC） codes defined by the sparse parity check matrix. Simulation results show that the performance of the proposed irregular LDPC codes can offer significant gains over traditional LDPC codes in low SNRs with a few decoding iterations over an additive white Gaussian noise （AWGN） channel.展开更多
Soft-cancellation(SCAN) is a soft output iterative algorithm widely used in polar decoding. This algorithm has better decoding performance than reduced latency soft-cancellation(RLSC) algorithm, which can effectively ...Soft-cancellation(SCAN) is a soft output iterative algorithm widely used in polar decoding. This algorithm has better decoding performance than reduced latency soft-cancellation(RLSC) algorithm, which can effectively reduce the decoding delay of SCAN algorithm by 50% but has obvious performance loss. A modified reduced latency soft-cancellation(MRLSC) algorithm is presented in the paper. Compared with RLSC algorithm, LLR information storage required in MRLSC algorithm can be reduced by about 50%, and better decoding performance can be achieved with only a small increase in decoding delay. The simulation results show that MRLSC algorithm can achieve a maximum block error rate(BLER) performance gain of about 0.4 dB compared with RLSC algorithm when code length is 2048. At the same time, compared with the performance of several other algorithms under(1024, 512) polar codes, the results show that the throughput of proposed MRLSC algorithm has the advantage at the low and medium signal-to-noise ratio(SNR) and better BLER performance at the high SNR.展开更多
To address the issue of field size in random network coding, we propose an Improved Adaptive Random Convolutional Network Coding (IARCNC) algorithm to considerably reduce the amount of occupied memory. The operation o...To address the issue of field size in random network coding, we propose an Improved Adaptive Random Convolutional Network Coding (IARCNC) algorithm to considerably reduce the amount of occupied memory. The operation of IARCNC is similar to that of Adaptive Random Convolutional Network Coding (ARCNC), with the coefficients of local encoding kernels chosen uniformly at random over a small finite field. The difference is that the length of the local encoding kernels at the nodes used by IARCNC is constrained by the depth; meanwhile, increases until all the related sink nodes can be decoded. This restriction can make the code length distribution more reasonable. Therefore, IARCNC retains the advantages of ARCNC, such as a small decoding delay and partial adaptation to an unknown topology without an early estimation of the field size. In addition, it has its own advantage, that is, a higher reduction in memory use. The simulation and the example show the effectiveness of the proposed algorithm.展开更多
The existing methods for identifying recursive systematic convolutional encoders with high robustness require to test all the candidate generator matrixes in the search space exhaustively.With the increase of the code...The existing methods for identifying recursive systematic convolutional encoders with high robustness require to test all the candidate generator matrixes in the search space exhaustively.With the increase of the codeword length and constraint length,the search space expands exponentially,and thus it limits the application of these methods in practice.To overcome the limitation,a novel identification method,which gets rid of exhaustive test,is proposed based on the cuckoo search algorithm by using soft-decision data.Firstly,by using soft-decision data,the probability that a parity check equation holds is derived.Thus,solving the parity check equations is converted to maximize the joint probability that parity check equations hold.Secondly,based on the standard cuckoo search algorithm,the established cost function is optimized.According to the final solution of the optimization problem,the generator matrix of recursive systematic convolutional code is estimated.Compared with the existing methods,our proposed method does not need to search for the generator matrix exhaustively and has high robustness.Additionally,it does not require the prior knowledge of the constraint length and is applicable in any modulation type.展开更多
With the development of manufacture technology, the multi-level cell(MLC)technique dramatically increases the storage density of NAND flash memory. As the result,cell-to-cell interference(CCI) becomes more serious and...With the development of manufacture technology, the multi-level cell(MLC)technique dramatically increases the storage density of NAND flash memory. As the result,cell-to-cell interference(CCI) becomes more serious and hence causes an increase in the raw bit error rate of data stored in the cells.Recently, low-density parity-check(LDPC)codes have appeared to be a promising solution to combat the interference of MLC NAND flash memory. However, the decoding complexity of the sum-product algorithm(SPA) is extremely high. In this paper, to improve the accuracy of the log likelihood ratio(LLR) information of each bit in each NAND flash memory cell, we adopt a non-uniform detection(N-UD) which uses the average maximum mutual information to determine the value of the soft-decision reference voltages.Furthermore, with an aim to reduce the decoding complexity and improve the decoding performance, we propose a modified soft reliabilitybased iterative majority-logic decoding(MSRBI-MLGD) algorithm, which uses a non-uniform quantizer based on power function to decode LDPC codes. Simulation results show that our design can offer a desirable trade-off between the performance and complexity for high-column-weight LDPC-coded MLC NAND flash memory.展开更多
A pseudo-random coding side-lobe suppression method based on CLEAN algorithm is introduced.The CLEAN algorithm mainly processes pulse compression results of a pseudo-random coding,and estimates a target＇s distance by...A pseudo-random coding side-lobe suppression method based on CLEAN algorithm is introduced.The CLEAN algorithm mainly processes pulse compression results of a pseudo-random coding,and estimates a target＇s distance by a method named interpolation method,so that we can get an ideal pulse compression result of the target,and then use the adjusted ideal pulse compression side-lobe to cut the actual pulse compression result,so as to achieve the remarkable performance of side-lobe suppression for large targets,and let the adjacent small targets appear.The computer simulations by MATLAB with this method analyze the effect of side-lobe suppression in an ideal or noisy environment.It is proved that this method can effectively solve the problem due to the side-lobe of pseudo-random coding being too high,and can enhance the radar＇s multi-target detection ability.展开更多
An effective Luby transform （LT） encoding algorithm based on short cycle elimination is proposed to improve decoding probabilities of short length LT codes. By searching the generator ma- trix, some special encoded ...An effective Luby transform （LT） encoding algorithm based on short cycle elimination is proposed to improve decoding probabilities of short length LT codes. By searching the generator ma- trix, some special encoded symbols are generated by the encoder to effectively break the short cycles that have negative effect on the performance of LT codes. Analysis and numerical results show that by employing the proposed algorithm, the encoding complexity decreases and the decoding probabili- ties improve both in binary erasure channels （BECs） and additive white gauss noise （AWGN） chan- nels.展开更多
The matrix inversion operation is needed in the MMSE decoding algorithm of orthogonal space-time block coding （OSTBC） proposed by Papadias and Foschini. In this paper, an minimum mean square error （MMSE） decoding ...The matrix inversion operation is needed in the MMSE decoding algorithm of orthogonal space-time block coding （OSTBC） proposed by Papadias and Foschini. In this paper, an minimum mean square error （MMSE） decoding algorithm without matrix inversion is proposed, by which the computational complexity can be reduced directly but the decoding performance is not affected.展开更多
With the rapid development of digital information technology,images are increasingly used in various fields.To ensure the security of image data,prevent unauthorized tampering and leakage,maintain personal privacy,and...With the rapid development of digital information technology,images are increasingly used in various fields.To ensure the security of image data,prevent unauthorized tampering and leakage,maintain personal privacy,and protect intellectual property rights,this study proposes an innovative color image encryption algorithm.Initially,the Mersenne Twister algorithm is utilized to generate high-quality pseudo-random numbers,establishing a robust basis for subsequent operations.Subsequently,two distinct chaotic systems,the autonomous non-Hamiltonian chaotic system and the tentlogistic-cosine chaotic mapping,are employed to produce chaotic random sequences.These chaotic sequences are used to control the encoding and decoding process of the DNA,effectively scrambling the image pixels.Furthermore,the complexity of the encryption process is enhanced through improved Joseph block scrambling.Thorough experimental verification,research,and analysis,the average value of the information entropy test data reaches as high as 7.999.Additionally,the average value of the number of pixels change rate(NPCR)test data is 99.6101%,which closely approaches the ideal value of 99.6094%.This algorithm not only guarantees image quality but also substantially raises the difficulty of decryption.展开更多
针对射频识别(RFID:Radio Frequency Identification)系统的信道资源有限,当多个标签竞争同一个频率或时间槽时,会导致发生碰撞和冲突的问题,为优化广播信道的通信效率,对基于帧时隙ALOHA的物联网RFID广播信道防碰撞算法进行了研究。该...针对射频识别(RFID:Radio Frequency Identification)系统的信道资源有限,当多个标签竞争同一个频率或时间槽时,会导致发生碰撞和冲突的问题,为优化广播信道的通信效率,对基于帧时隙ALOHA的物联网RFID广播信道防碰撞算法进行了研究。该方法引入帧时隙概念,对通信时间进行时间段划分;通过时隙内空闲、成功识别以及碰撞3种状态的发生概率分析,得到广播信道内的碰撞原因。结合贝叶斯算法与泊松分布规则,通过标签数目概率分布计算,实现读写器作用范围内标签数量的估计,并根据标签数量计算结果调整下一帧帧长。若调整后的帧时隙范围内仍存在标签碰撞问题,则通过FastICA(Indcpendent Component Analysis)独立主成分分析法,将帧时隙内的标签识别问题,转化为EPC(Electronic Product Code)编码生成问题,进而实现统一时隙内多标签的并行识别,避免发生碰撞。实验表明,所提方的标签数量的估算准确,能在保证通信信道稳定性的前提下,提高时隙内标签识别率,有效提高广播信道的传播效率。展开更多
基金the National Natural Science Foundation of China，the National Key Basic Research Program of China，The authors would like to thank all project partners for their valuable contributions and feedbacks
文摘Abstract： The layered decoding algorithm has been widely used in the implementation of Low Density Parity Check （LDPC） decoders, due to its high convergence speed. However, the pipeline operation of the layered decoder may introduce memory access conflicts, which heavily deteriorates the decoder throughput. To essentially deal with the issue of memory access conflicts,
基金Project supported by the National Natural Science Foundation of China(Grant No.60972046)Grant from the National Defense Pre-Research Foundation of China
文摘For quantum sparse graph codes with stabilizer formalism, the unavoidable girth-four cycles in their Tanner graphs greatly degrade the iterative decoding performance with standard belief-propagation （BP） algorithm. In this paper, we present a jointly-check iterative algorithm suitable for decoding quantum sparse graph codes efficiently. Numerical simulations show that this modified method outperforms standard BP algorithm with an obvious performance improvement.
基金the National Natural Science Foundation of China under grants，NUAA research funding
文摘It is known that Block Turbo Codes （BTC） can be nearly optimally decoded by Chase-II algorithm, in which the Least Reliable Bits （LRBs） are chosen empirically to keep the size of the test patterns （sequences） relatively small and to reduce the decoding complexity. While there are also other adaptive techniques, where the decoder＇s LRBs adapt to the external parameter of the decoder like SNR （Signal Noise Ratio） level, a novel adaptive algorithm for BTC based on the statistics of an internal variable of the decoder itself is proposed in this paper. Different from the previous reported results, it collects the statistics of the multiplicity of the candidate sequences, i.e., the number of the same candidate sequences with the same minimum squared Euclidean distance resulted from the decoding of test sequences. It is shown by Monte Carlo simulations that the proposed adaptive algorithm has only about 0.02dB coding loss but the average complexity of the proposed algorithm is about 42% less compared with Pyndiah＇s iterative decoding algorithm using the fixed LRBs parameter.
文摘Since real world communication channels are not error free, the coded data transmitted on them may be corrupted, and block based image coding systems are vulnerable to transmission impairment. So the best neighborhood match method using genetic algorithm is used to conceal the error blocks. Experimental results show that the searching space can be greatly reduced by using genetic algorithm compared with exhaustive searching method, and good image quality is achieved. The peak signal noise ratios(PSNRs) of the restored images are increased greatly.
文摘A new method for the construction of the high performance systematic irregular low-density paritycheck （LDPC） codes based on the sparse generator matrix （G-LDPC） is introduced. The code can greatly reduce the encoding complexity while maintaining the same decoding complexity as traditional regular LDPC （H-LDPC） codes defined by the sparse parity check matrix. Simulation results show that the performance of the proposed irregular LDPC codes can offer significant gains over traditional LDPC codes in low SNRs with a few decoding iterations over an additive white Gaussian noise （AWGN） channel.
基金the Zhejiang Provincial Natural Science Foundation of China under Grant No. Y20F010069supported in part by the National Natural Science Foundation of China (NSFC) under Grant No. 51874264, 61571108Key Laboratory of Electromagnetic Wave Information Technology and Metrology of Zhejiang Province, College of Information Engineering, China Jiliang University, Hangzhou 310018, China
文摘Soft-cancellation(SCAN) is a soft output iterative algorithm widely used in polar decoding. This algorithm has better decoding performance than reduced latency soft-cancellation(RLSC) algorithm, which can effectively reduce the decoding delay of SCAN algorithm by 50% but has obvious performance loss. A modified reduced latency soft-cancellation(MRLSC) algorithm is presented in the paper. Compared with RLSC algorithm, LLR information storage required in MRLSC algorithm can be reduced by about 50%, and better decoding performance can be achieved with only a small increase in decoding delay. The simulation results show that MRLSC algorithm can achieve a maximum block error rate(BLER) performance gain of about 0.4 dB compared with RLSC algorithm when code length is 2048. At the same time, compared with the performance of several other algorithms under(1024, 512) polar codes, the results show that the throughput of proposed MRLSC algorithm has the advantage at the low and medium signal-to-noise ratio(SNR) and better BLER performance at the high SNR.
基金supported by the National Science Foundation （NSF） under Grants No.60832001,No.61271174 the National State Key Lab oratory of Integrated Service Network （ISN） under Grant No.ISN01080202
文摘To address the issue of field size in random network coding, we propose an Improved Adaptive Random Convolutional Network Coding (IARCNC) algorithm to considerably reduce the amount of occupied memory. The operation of IARCNC is similar to that of Adaptive Random Convolutional Network Coding (ARCNC), with the coefficients of local encoding kernels chosen uniformly at random over a small finite field. The difference is that the length of the local encoding kernels at the nodes used by IARCNC is constrained by the depth; meanwhile, increases until all the related sink nodes can be decoded. This restriction can make the code length distribution more reasonable. Therefore, IARCNC retains the advantages of ARCNC, such as a small decoding delay and partial adaptation to an unknown topology without an early estimation of the field size. In addition, it has its own advantage, that is, a higher reduction in memory use. The simulation and the example show the effectiveness of the proposed algorithm.
文摘The existing methods for identifying recursive systematic convolutional encoders with high robustness require to test all the candidate generator matrixes in the search space exhaustively.With the increase of the codeword length and constraint length,the search space expands exponentially,and thus it limits the application of these methods in practice.To overcome the limitation,a novel identification method,which gets rid of exhaustive test,is proposed based on the cuckoo search algorithm by using soft-decision data.Firstly,by using soft-decision data,the probability that a parity check equation holds is derived.Thus,solving the parity check equations is converted to maximize the joint probability that parity check equations hold.Secondly,based on the standard cuckoo search algorithm,the established cost function is optimized.According to the final solution of the optimization problem,the generator matrix of recursive systematic convolutional code is estimated.Compared with the existing methods,our proposed method does not need to search for the generator matrix exhaustively and has high robustness.Additionally,it does not require the prior knowledge of the constraint length and is applicable in any modulation type.
基金supported in part by the NSF of China (61471131, 61771149, 61501126)NSF of Guangdong Province 2016A030310337+1 种基金the open research fund of National Mobile Communications Research Laboratory, Southeast University (No. 2018D02)the Guangdong Province Universities and Colleges Pearl River Scholar Funded Scheme (2017-ZJ022)
文摘With the development of manufacture technology, the multi-level cell(MLC)technique dramatically increases the storage density of NAND flash memory. As the result,cell-to-cell interference(CCI) becomes more serious and hence causes an increase in the raw bit error rate of data stored in the cells.Recently, low-density parity-check(LDPC)codes have appeared to be a promising solution to combat the interference of MLC NAND flash memory. However, the decoding complexity of the sum-product algorithm(SPA) is extremely high. In this paper, to improve the accuracy of the log likelihood ratio(LLR) information of each bit in each NAND flash memory cell, we adopt a non-uniform detection(N-UD) which uses the average maximum mutual information to determine the value of the soft-decision reference voltages.Furthermore, with an aim to reduce the decoding complexity and improve the decoding performance, we propose a modified soft reliabilitybased iterative majority-logic decoding(MSRBI-MLGD) algorithm, which uses a non-uniform quantizer based on power function to decode LDPC codes. Simulation results show that our design can offer a desirable trade-off between the performance and complexity for high-column-weight LDPC-coded MLC NAND flash memory.
文摘A pseudo-random coding side-lobe suppression method based on CLEAN algorithm is introduced.The CLEAN algorithm mainly processes pulse compression results of a pseudo-random coding,and estimates a target＇s distance by a method named interpolation method,so that we can get an ideal pulse compression result of the target,and then use the adjusted ideal pulse compression side-lobe to cut the actual pulse compression result,so as to achieve the remarkable performance of side-lobe suppression for large targets,and let the adjacent small targets appear.The computer simulations by MATLAB with this method analyze the effect of side-lobe suppression in an ideal or noisy environment.It is proved that this method can effectively solve the problem due to the side-lobe of pseudo-random coding being too high,and can enhance the radar＇s multi-target detection ability.
基金Supported by China Mobile Research Institute and China National S&T Major Project(2010ZX03003-003)
文摘An effective Luby transform （LT） encoding algorithm based on short cycle elimination is proposed to improve decoding probabilities of short length LT codes. By searching the generator ma- trix, some special encoded symbols are generated by the encoder to effectively break the short cycles that have negative effect on the performance of LT codes. Analysis and numerical results show that by employing the proposed algorithm, the encoding complexity decreases and the decoding probabili- ties improve both in binary erasure channels （BECs） and additive white gauss noise （AWGN） chan- nels.
文摘The matrix inversion operation is needed in the MMSE decoding algorithm of orthogonal space-time block coding （OSTBC） proposed by Papadias and Foschini. In this paper, an minimum mean square error （MMSE） decoding algorithm without matrix inversion is proposed, by which the computational complexity can be reduced directly but the decoding performance is not affected.
基金supported by the Open Fund of Advanced Cryptography and System Security Key Laboratory of Sichuan Province(Grant No.SKLACSS-202208)the Natural Science Foundation of Chongqing(Grant No.CSTB2023NSCQLZX0139)the National Natural Science Foundation of China(Grant No.61772295).
文摘With the rapid development of digital information technology,images are increasingly used in various fields.To ensure the security of image data,prevent unauthorized tampering and leakage,maintain personal privacy,and protect intellectual property rights,this study proposes an innovative color image encryption algorithm.Initially,the Mersenne Twister algorithm is utilized to generate high-quality pseudo-random numbers,establishing a robust basis for subsequent operations.Subsequently,two distinct chaotic systems,the autonomous non-Hamiltonian chaotic system and the tentlogistic-cosine chaotic mapping,are employed to produce chaotic random sequences.These chaotic sequences are used to control the encoding and decoding process of the DNA,effectively scrambling the image pixels.Furthermore,the complexity of the encryption process is enhanced through improved Joseph block scrambling.Thorough experimental verification,research,and analysis,the average value of the information entropy test data reaches as high as 7.999.Additionally,the average value of the number of pixels change rate(NPCR)test data is 99.6101%,which closely approaches the ideal value of 99.6094%.This algorithm not only guarantees image quality but also substantially raises the difficulty of decryption.
