Construction of Regular Rate-Compatible LDPC Convolutional Codes

In this paper, we propose a new method to derive a family of regular rate-compatible low-density parity-check（RC-LDPC） convolutional codes from RC-LDPC block codes. In the RC-LDPC convolutional family, each extended sub-matrix of each extended code is obtained by choosing specified elements from two fixed matrices HE1K and HE1K, which are derived by modifying the extended matrices HE1 and HE2 of a systematic RC-LDPC block code. The proposed method which is based on graph extension simplifies the design, and prevent the defects caused by the puncturing method. It can be used to generate both regular and irregular RC-LDPC convolutional codes. All resulted codes in the family are systematic which simplify the encoder structure and have maximum encoding memories which ensure the property. Simulation results show the family collectively offer a steady improvement in performance with code compatibility over binary-input additive white Gaussian noise channel（BI-AWGNC）.

NEW METHOD TO RECOVER INTERNET PACKET LOSSES USING(2,1,m)SYSTEMATIC CONVOLUTIONAL CODES

A new method to recover packet losses using (2,1,m) convolutional codes is proposed. The erasure correcting decoding algorithm and the decoding determinant theorem is presented. It is also proved that the codes with optimal distance profile have also optimal delay characteristic. Simulation results show that the proposed method can recover the packet losses more elliciently than RS codes over different decoding delay conditions and thus suits for different packet network delav conditions.

Construction of Rate-Compatible(RC) Low-Density Parity-Check(LDPC) Convolutional Codes Based on RC-LDPC Block Codes

In this paper,a family of rate-compatible(RC) low-density parity-check(LDPC) convolutional codes can be obtained from RC-LDPC block codes by graph extension method.The resulted RC-LDPC convolutional codes,which are derived by permuting the matrices of the corresponding RC-LDPC block codes,are systematic and have maximum encoding memory.Simulation results show that the proposed RC-LDPC convolutional codes with belief propagation(BP) decoding collectively offer a steady improvement on performance compared with the block counterparts over the binary-input additive white Gaussian noise channels(BI-AWGNCs).

Non-Intrusive Design of Self-Checking FSM Based on Convolutional Codes

A non-intrusive design of self-checking finite state machines (FSMs) in VLSI circuits was investigated using convolutional codes. We propose a novel scheme which cannot only detect but also correct errors occurred in FSM states. The error state will be corrected and sent back to the FSM, so that the concurrent error in the current state is detected and corrected immediately. Moreover, we realize the IP core of the self-checking module by SMIC 0.25-μm CMOS technology and also simulate its function in FPGA.

Semi-LDPC Convolutional Codes:Construction and Low-Latency Windowed List Decoding

This paper presents a new coding scheme called semi-low-density parity-check convolutional code(semi-LDPC-CC),whose parity-check matrix consists of both sparse and dense sub-matrices,a feature distinguished from the conventional LDPC-CCs.We propose sliding-window list(SWL)decoding algorithms with a fixed window size of two,resulting in a low decoding latency but a competitive error-correcting performance.The performance can be predicted by upper bounds derived from the first event error probability and by genie-aided(GA)lower bounds estimated from the underlying LDPC block codes(LDPC-BCs),while the complexity can be reduced by truncating the list with a threshold on the difference between the soft metrics in the serial decoding implementation.Numerical results are presented to validate our analysis and demonstrate the performance advantage of the semi-LDPC-CCs over the conventional LDPC-CCs.

Blind recognition of punctured convolutional codes

This paper presents an algorithm for blind recognition of punctured convo-lutional codes which is an important problem in adaptive modulation and coding. For a given finite sequence of convolutional code, the parity check matrix of the convolutional code is first computed by solving a linear system with adequate error tolerance. Then a minimal basic encoding matrix of the original convolutional code and its puncturing pattern are determined according to the known parity check matrix of the punctured convolutional code.

Response compaction for system-on-a-chip based on advanced convolutional codes

This paper addresses the problem of test response compaction. In order to maximize compaction ratio, a single-output compactor based on a （n, n-1, m, 3） convolutional code is presented. When the proposed theorems are satisfied, the compactor can avoid two and any odd erroneous bits cancellations, and handle one unknown bit （X bit）. When the X bits in response are clustered, multiple-weight check matrix design algorithm can be used to reduce the effect of massive X bits. Some extended experimental results show that the proposed encoder has an acceptable-level X tolerant capacity and low error cancellations probability.

Ensemble of High Performance Structured Binary Convolutional LDPC Codes with Moderate Rates

An algebraic construction methodology is proposed to design binary time-invariant convolutional low-density parity-check(LDPC)codes.Assisted by a proposed partial search algorithm,the polynomialform parity-check matrix of the time-invariant convolutional LDPC code is derived by combining some special codewords of an(n,2,n−1)code.The achieved convolutional LDPC codes possess the characteristics of comparatively large girth and given syndrome former memory.The objective of our design is to enable the time-invariant convolutional LDPC codes the advantages of excellent error performance and fast encoding.In particular,the error performance of the proposed convolutional LDPC code with small constraint length is superior to most existing convolutional LDPC codes.

Blind recognition of k/n rate convolutional encoders from noisy observation

Blind recognition of convolutional codes is not only essential for cognitive radio, but also for non-cooperative context. This paper is dedicated to the blind identification of rate k/n convolutional encoders in a noisy context based on Walsh-Hadamard transformation and block matrix (WHT-BM). The proposed algorithm constructs a system of noisy linear equations and utilizes all its coefficients to recover parity check matrix. It is able to make use of fault-tolerant feature of WHT, thus providing more accurate results and achieving better error performance in high raw bit error rate (BER) regions. Moreover, it is more computationally efficient with the use of the block matrix (BM) method. © 2017 Beijing Institute of Aerospace Information.

Improved Design and SOVA Algorithm for Serial Concatenated Convolutional Code

To improve the performance of the short interleaved serial concatenated convolutional code(SCCC) with low decoding iterative times, the structure of Log MAP algorithm is introduced into the conventional SOVA decoder to improve its performance at short interleaving delay. The combination of Log MAP and SOVA avoids updating the matrices of the maximum path, and also makes a contribution to the requirement of short delay. The simulation results of several SCCCs show that the improved decoder can obtain satisfied performance with short frame interleaver and it is suitable to the high bit rate low delay communication systems.

Blind reconstruction of convolutional code based on segmented Walsh-Hadamard transform

Walsh-Hadamard transform （WriT） can solve linear error equations on Field F2, and the method can be used to recover the parameters of convolutional code. However, solving the equations with many unknowns needs enormous computer memory which limits the application of WriT. In order to solve this problem, a method based on segmented WriT is proposed in this paper. The coefficient vector of high dimension is reshaped and two vectors of lower dimension are obtained. Then the WriT is operated and the requirement for computer memory is much reduced. The code rate and the constraint length of convolutional code are detected from the Walsh spectrum. And the check vector is recovered from the peak position. The validity of the method is verified by the simulation result, and the performance is proved to be optimal.

Improved Adaptive Random Convolutional Network Coding Algorithm

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.

Integrated Joint Source-Channel Symbol-by-Symbol Decoding of Variable-Length Codes Using 3-D MAP Sequence Estimation

Most of multimedia schemes employ variable-length codes （VLCs） like Huffman code as core components in obtaining high compression rates. However VLC methods are very sensitive to channel noise. The goal of this paper is to salvage as many data from the damaged packets as possible for higher audiovisual quality. This paper proposes an integrated joint source-channel decoder （I-JSCD） at a symbol-level using three-dimensional （3-D） trellis representation for first-order Markov sources encoded with VLC source code and convolutional channel code. This method combines source code and channel code state-spaces and bit-lengths to construct a two-dimensional （2-D） state-space, and then develops a 3-D trellis and a maximum a-posterior （MAP） algorithm to estimate the source sequence symbol by symbol. Experiment results demonstrate that our method results in significant improvement in decoding performance, it can salvage at least half of （50%） data in any channel error rate, and can provide additional error resilience to VLC stream like image, audio, video stream over high error rate links.

Algebraic Approach to Random Convolutional Network Coding over Wireless Packet Networks

To characterize the algebraic structure of wireless network coding, a hypergragh is utilized to model wireless packet networks from network layer. The algebraic description of random convolutional network coding is deduced, and the coding condition is also presented. Analyses and simulations show that random convolutional coding is capacity-achieving with probability approaching 1.

Performance of Convolutionally Coded Multicarrier DS-CDMA System

A new convolutionally coded direct sequence (DS) CDMA system is proposed. The outputs of a convolutional encoder modulate multiple band-limited DS-CDMA waveforms. The receiver detects and combines signals for the desired user and feeds a soft-decision Viterbi decoder. The performance of this system is compared to that of a convolutionally coded single carrier DS CDMA system with a Rake receiver. At roughly equivalent receiver complexity, results will demonstrate superior performance of the coded multicarrier system.

Joint Source-Channel Decoding of EVRC Speech Encoder Using Residual Redundancy

The enhanced variable rate codec (EVRC) is a standard for the 'Speech ServiceOption 3 for Wideband Spread Spectrum Digital System,' which has been employed in both IS-95cellular systems and ANSI J-STC-008 PCS (personal communications systems). This paper concentrateson channel decoders that exploit the residual redundancy inherent in the enhanced variable ratecodec bitstream. This residual redundancy is quantified by modeling the parameters as first orderMarkov chains and computing the entropy rate based on the relative frequencies of transitions.Moreover, this residual redundancy can be exploited by an appropriately 'tuned' channel decoder toprovide substantial coding gain when compared with the decoders that do not exploit it. Channelcoding schemes include convolutional codes, and iteratively decoded parallel concatenatedconvolutional 'turbo' codes.

Performance evaluation of multicast relay network using LDPC and convolutional channel codes along-with XOR network coding

In this paper, we have compared the performance of joint network channel coding （JNCC） for multicast relay network using low density parity check （LDPC） codes and Convolutional codes as channel codes while exclusive or （XOR） network coding used at the intermediate relay nodes. Multicast relay transmission is a type of transmission scheme in which two fixed relay nodes contribute in the second hop of end-to-end transmission between base transceiver station （BTS） and a pair of mobile stations. We have considered one way and two way multicast scenarios to evaluate the bit error rate （BER） and throughput performance. It has been shown that when using XOR network coding at the intermediate relay nodes, the same transmission becomes possible in less time slots hence throughput performance can be improved. Moreover we have also discussed two possible scenarios in the proposed system model, in which both diversity and multiplexing gain has been considered. It is worth notifying that BER and throughput achieved for LDPC codes is better than Convolutional codes for all the schemes discussed.

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...

Joint Source-Channel Bit Allocation Based on Expected End-to-End Distortion Model

An adaptive joint source channel bit allocation method for video communications over error-prone channel is proposed.To protect the bit-streams from the channel bit errors,the rate compatible punctured convolution(RCPC)code is used to produce coding rates varying from 4/5 to 1/2 using the same encoder and the Viterbi decoder.An expected end-to-end distortion model was presented to estimate the distortion introduced in compressed source coding due to quantization and channel bit errors jointly.Based on the proposed end-to-end distortion model,an adaptive joint source-channel bit allocation method was proposed under time-varying error-prone channel conditions.Simulated results show that the proposed methods could utilize the available channel capacity more efficiently and achieve better video quality than the other fixed coding-based bit allocation methods when transmitting over error-prone channels.

Channel Coding Techniques for VHF-Mobile Radio System and Its DSP Implementation

Two variable channel-coding schemes with unequal error protection （UEP） are proposed in terms of speech transmission over VHF-mobile radio system. These channel coding are separately based on rate-compatible punctured convolution （RCPC） code scheme and rate-compatible punctured turbo （RCPT） code scheme. With optimum puncturing designation and suitable scheme of rate matching, these two UEP schemes can achieve intra-class unequal error protection, which makes the protection for source bits with different importance more accurate. Its real time implementation based on a TMS320C6416 digital signal processor is also presented. The experimental results suggest that this method have reasonable system complexity and short processing delay.