A Denoiser for Correlated Noise Channel Decoding: Gated-Neural Network

This letter proposes a sliced-gated-convolutional neural network with belief propagation(SGCNN-BP) architecture for decoding long codes under correlated noise. The basic idea of SGCNNBP is using Neural Networks(NN) to transform the correlated noise into white noise, setting up the optimal condition for a standard BP decoder that takes the output from the NN. A gate-controlled neuron is used to regulate information flow and an optional operation—slicing is adopted to reduce parameters and lower training complexity. Simulation results show that SGCNN-BP has much better performance(with the largest gap being 5dB improvement) than a single BP decoder and achieves a nearly 1dB improvement compared to Fully Convolutional Networks(FCN).

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.

A highly reliable encoding and decoding communication framework based on semantic information

Increasing research has focused on semantic communication,the goal of which is to convey accurately the meaning instead of transmitting symbols from the sender to the receiver.In this paper,we design a novel encoding and decoding semantic communication framework,which adopts the semantic information and the contextual correlations between items to optimize the performance of a communication system over various channels.On the sender side,the average semantic loss caused by the wrong detection is defined,and a semantic source encoding strategy is developed to minimize the average semantic loss.To further improve communication reliability,a decoding strategy that utilizes the semantic and the context information to recover messages is proposed in the receiver.Extensive simulation results validate the superior performance of our strategies over state-of-the-art semantic coding and decoding policies on different communication channels.

The"Decoding Zhonghua"International Conference on Dialogue among Civilisations Held in Beijing

The"Decoding Zhonghua"International Conference on Dialogue among Civilisations,hosted by China International Public Relations Association,China Ethnic News and Academy of Contemporary China and World Studies was held in Beijing on January 17th.With the theme"Pursing Harmonious Coexistence of Civilisations through Dialogue".

Achievability of Chong-Motani-Garg relay channel capacity bounds using forward decoding

To reduce decoding delay of a communication scheme which is backward-decoding-based and achievable Chong Motani-Garg capacity bounds, a novel forward-sliding-window decoding-based communication scheme is proposed. In this scheme, if w = （w1, w2） is the message to be sent in block b, the relay will decode message w1 and generate a new message z at the end of block b, and the receiver will decode message w1 at the end of block b ＋ 1 and decode message z and w2 at the end of block b ＋ 2. Analysis results show that this new communication scheme can achieve the same Chong-Motani-Garg bounds and the decoding delay is only two blocks which is much shorter than that of backward decoding. Therefore, Chong-Motani-Garg bounds can be achieved by a forward decoding-based communication scheme with short decoding delay.

Iterative Decoding of Parallel Concatenated Block Codes and Coset Based MAP Decoding Algorithm for F24 Code

A multi dimensional concatenation scheme for block codes is introduced, in which information symbols are interleaved and re encoded for more than once. It provides a convenient platform to design high performance codes with flexible interleaver size. Coset based MAP soft in/soft out decoding algorithms are presented for the F24 code. Simulation results show that the proposed coding scheme can achieve high coding gain with flexible interleaver length and very low decoding complexity.

Low complexity iterative differential decoding algorithm for multiband UWB communication systems

Due to not requiring channel state information （CSI） at both the transmitter and the receiver, noncoherent ultra-wideband （UWB） incurs a performance penalty of approximately 3 dB in the required signal to noise ratio （SNR） compared to the coherent case. To overcome the gap, an effective differential encoding and decoding scheme for multiband UWB systems is proposed. The proposed scheme employs the parallel concatenation of two recursive differential unitary space-frequency encoders at the transmitter. At the receiver, two component decoders iteratively decode information bits by interchanging soft metric values between each other. To reduce the computation complexity, a decoding algorithm which only uses transition probability to calculate the log likelihood ratios （LLRs） for the decoded bits is given. Simulation results show that the proposed scheme can dramatically outperform the conventional differential and even coherent detection at high SNR with a few iterations.

Low complexity joint source-channel decoding for transmission of wavelet compressed images

To utilize residual redundancy to reduce the error induced by fading channels and decrease the complexity of the field model to describe the probability structure for residual redundancy, a simplified statistical model for residual redundancy and a low complexity joint source-channel decoding（JSCD） algorithm are proposed. The complicated residual redundancy in wavelet compressed images is decomposed into several independent 1-D probability check equations composed of Markov chains and it is regarded as a natural channel code with a structure similar to the low density parity check （LDPC） code. A parallel sum-product （SP） and iterative JSCD algorithm is proposed. Simulation results show that the proposed JSCD algorithm can make full use of residual redundancy in different directions to correct errors and improve the peak signal noise ratio （PSNR） of the reconstructed image and reduce the complexity and delay of JSCD. The performance of JSCD is more robust than the traditional separated encoding system with arithmetic coding in the same data rate.

Soft Decoding Scheme of Convolution Code Combined with Huffman Coding

This paper proposes a modification of the soft output Viterbi decoding algorithm (SOVA) which combines convolution code with Huffman coding. The idea is to extract the bit probability information from the Huffman coding and use it to compute the a priori source information which can be used when the channel environment is bad. The suggested scheme does not require changes on the transmitter side. Compared with separate decoding systems, the gain in signal to noise ratio is about 0 5-1.0 dB with a limi...

NOVEL DECODING OF SQUARE QAM MODULATED MIMO SYSTEMS BASED ON TURBO MULTIUSER DETECTION

By introducing the bit-level multi-stream coded Layered Space-Time （LST） transmitter along with a novel iterative MultiStage Decoding （MSD） at the receiver, the paper shows how to achieve the near-capacity performance of the Multiple-Input Multiple-Output （MIMO） systems with square Quadrature Amplitude Modulation （QAM）. In the proposed iterative MSD scheme, the detection at each stage is equivalent to multiuser detection of synchronous Code Division Multiple Access （CDMA） multiuser systems with the aid of the binary representation of the transmitted symbols. Therefore, the optimal Soft-Input Soft-Output （SISO） multiuser detection and low-complexity SISO multiuser detection can be utilized herein. And the proposed scheme with low-complexity SISO multiuser detection has polynomial complexity in the number of transmit antennas M, the number of receive antennas N, and the number of bits per constellation point Me. Simulation results demonstrate that the proposed scheme has similar Bit Error Rate （BER） performance to that of the known Iterative Tree Search （ITS） detection.

Design and Implementation of a Novel Algorithm for Iterative Decoding of Product Codes

A novel product code iterative decoding algorithm and its high speed implementation scheme are proposed in this paper. Based on partial combination of selected columns of check matrix, the reduced-complexity syndrome decoding method is proposed to decode sub-codes of product code and deliver soft output information. So iterative decoding of product codes is possible. The fast sorting algorithm and a look-up method are proposed for high speed implementation of this algorithm. Compared to the conventional weighing iterative algorithm, the proposed algorithm has lower complexity while offering better performance, which is demonstrated by simulations and implementation analysis. The implementation scheme and verilog HDL simulation show that it is feasible to achieve high speed decoding with the proposed algorithm.

Improved Polar Decoder Utilizing Neural Network in Fast Simplified Successive-Cancellation Decoding

Polar codes using successive-cancellation decoding always suffer from high latency for its serial nature. Fast simplified successive-cancellation decoding algorithm improves the situation in theoretically but not performs well as expected in practical for the workload of nodes identification and the existence of many short blocks. Meanwhile, Neural network (NN) based decoders have appeared as potential candidates to replace conventional decoders for polar codes. But the exponentially increasing training complexity with information bits is unacceptable which means it is only suitable for short codes. In this paper, we present an improvement that increases decoding efficiency without degrading the error-correction performance. The long polar codes are divided into several sub-blocks, some of which can be decoded adopting fast maximum likelihood decoding method and the remained parts are replaced by several short codes NN decoders. The result shows that time steps the proposed algorithm need only equal to 79.8% of fast simplified successive-cancellation decoders require. Moreover, it has up to 21.2 times faster than successive-cancellation decoding algorithm. More importantly, the proposed algorithm decreases the hardness when applying in some degree.

On the Manipulation of the Selectivity of Encoding and Decoding overthe Translator's Subjectivity

The translation activity is a process of the interlinguistic transmission of information realized by the information encoding and decoding.Encoding and decoding,cognitive practices operated in objective contexts,are inevitably of selectivity ascribing to the restriction of contextual reasons.The translator as the intermediary agent connects the original author(encoder)and the target readers(decoder),shouldering the dual duties of the decoder and the encoder,for which his subjectivity is irrevocably manipulated by the selectivity of encoding and decoding.

RETRACTED: <i>Improved Polar Decoder Utilizing Neural Network in Fast Simplified Successive-Cancellation Decoding</i>

This article has been retracted to straighten the academic record. In making this decision the Editorial Board follows COPE's Retraction Guidelines. The aim is to promote the circulation of scientific research by offering an ideal research publication platform with due consideration of internationally accepted standards on publication ethics. The Editorial Board would like to extend its sincere apologies for any inconvenience this retraction may have caused. Please see the article page for more details. The full retraction notice in PDF is preceding the original paper which is marked "RETRACTED".

Improved MPEG-4 High-Efficiency AAC With Variable-Length Soft-Decision Decoding of the Quantized Spectral Coefficients

MPEG-4 High-Efficiency Advanced Audio Coding (HE-AAC) is designed for low bit rate applications, such as audio streaming in mobile communications. The HE-AAC audio codec offers a better coding efficiency since variable-length codes (VLCs) are adopted. However, HE-AAC has originally been designed for storage and error-free transmission conditions. For the transmission over bit error-prone channels, error propagation is a serious problem for the VLCs. Therefore, a robust HE-AAC decoder is desired, especially for mobile communications. In contrast to traditional hard-decision decoding, utilizing bit-wise channel reliability information, softdecision (SD) decoding has been known to offer better audio quality. In HE-AAC, the global gain parameter is coded with fixedlength codes (FLCs), while the scale factors and quantized spectral coefficients are coded with VLCs. In this work, we apply FL/SD decoding to the global gain parameter, VL/SD decoding to the parameters scale factors and quantized spectral coefficients. Especially, in order to apply VL/SD decoding to the quantized spectral coefficients, a new modified trellis representation in VL/SD decoding is proposed. An improved HE-AAC performance is clearly observed, with the support of both instrumental measurements and a subjective listening test.

Erasure-Correction-Enhanced Iterative Decoding for LDPC-RS Product Codes

Low-density parity-check(LDPC)codes are widely used due to their significant errorcorrection capability and linear decoding complexity.However,it is not sufficient for LDPC codes to satisfy the ultra low bit error rate(BER)requirement of next-generation ultra-high-speed communications due to the error floor phenomenon.According to the residual error characteristics of LDPC codes,we consider using the high rate Reed-Solomon(RS)codes as the outer codes to construct LDPC-RS product codes to eliminate the error floor and propose the hybrid error-erasure-correction decoding algorithm for the outer code to exploit erasure-correction capability effectively.Furthermore,the overall performance of product codes is improved using iteration between outer and inner codes.Simulation results validate that BER of the product code with the proposed hybrid algorithm is lower than that of the product code with no erasure correction.Compared with other product codes using LDPC codes,the proposed LDPC-RS product code with the same code rate has much better performance and smaller rate loss attributed to the maximum distance separable(MDS)property and significant erasure-correction capability of RS codes.

A simplified decoding algorithm for multi-CRC polar codes

Polar codes represent one of the major breakthroughs in 5G standard,and have been proven to be able to achieve the symmetric capacity of binary-input discrete memoryless channels using the successive cancellation list(SCL)decoding algorithm.However,the SCL algorithm suffers from a large amount of memory overhead.This paper proposes an adaptive simplified decoding algorithm for multiple cyclic redundancy check(CRC)polar codes.Simulation results show that the proposed method can reduce the decoding complexity and memory space.It can also acquire the performance gain in the low signal to noise ratio region.

An Iterative Decoding Scheme for Davey-MacKay Construction

In the Davey-MacKay(DM) construction,the inner decoder treats unknown transmitted bits as random independent substitution errors. It limits the synchronization capability of the inner decoder, and thus weakens the error-correcting capability of the DM construction.In order to improve the performance of the DM construction, an iterative decoding scheme is proposed, which iteratively utilizes the more accurate estimates of transmitted codewords. In the proposed scheme, the estimated average bit error rates and the estimated low-density parity-check(LDPC) codewords from the outer decoder are fed back into the inner decoder to update the synchronization process. Simulation results show that the proposed iterative decoding scheme significantly outperforms the traditional DM construction.

Construction of LDPC Codes for the Layered Decoding Algorithm

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,

AN IMPROVED SOVA-BASED DECODING SCHEME FOR TURBO-STCM

Parallel concatenated spa ce time trellis code modulation, called Turbo STCM, can efficiently increase the coding gains of the space time codes. However, the complexity of the iterat iv e decoding restricts its application. This paper introduces a lower complex deco ding algorithm based on soft output Viterbi algorithm (SOVA) for Turbo STCM. S imulational results show that the new SOVA algorithm for the Turbo STCM outperf orms the original space time trellis code (STTC) by 4~6 dB. At the same time, compared with the Max Log MAP (maximum a posteriori) algorithm, the new scheme requires a lower complexity and approaches the performance of Turbo STCM decod ing w ith Max Log MAP.