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,

Novel joint encoding/decoding algorithms of fountain codes for underwater acoustic communication

Fountain codes are considered to be a promising coding technique in underwater acoustic communication（UAC） which is challenged with the unique propagation features of the underwater acoustic channel and the harsh marine environment. And Luby transform（LT） codes are the first codes fully realizing the digital fountain concept. However, in conventional LT encoding/decoding algorithms, due to the imperfect coverage（IC） of input symbols and short cycles in the generator matrix, stopping sets would occur and terminate the decoding. Thus, the recovery probability is reduced,high coding overhead is required and decoding delay is increased.These issues would be disadvantages while applying LT codes in underwater acoustic communication. Aimed at solving those issues, novel encoding/decoding algorithms are proposed. First,a doping and non-uniform selecting（DNS） encoding algorithm is proposed to solve the IC and the generation of short cycles problems. And this can reduce the probability of stopping sets occur during decoding. Second, a hybrid on the fly Gaussian elimination and belief propagation（OFG-BP） decoding algorithm is designed to reduce the decoding delay and efficiently utilize the information of stopping sets. Comparisons via Monte Carlo simulation confirm that the proposed schemes could achieve better overall decoding performances in comparison with conventional schemes.

Noncoherent Unitary Space-Time Codes： Constellation Design and Decoding Algorithm

Two novel schemes of unitary space-time constellations generation based on zero vectors adding are proposed for the multiple-antenna communication system. In the first scheme, T2 zero row vectors are added into conventional unitary matrices directly, and the number of new unitary matrices obtained by different positions of the added zero vectors in T symbol duration is [T / T2 ] times larger than that of conventional unitary matrices. In the second scheme, one part of the required constellations is created by the first scheme and the other part is obtained by the conventional design. This means that more information bits can be transmitted by the new constellations. According to their special construction, two corresponding decoding algorithms are proposed with low complexity in flat fading channel, respectively. At the same time, the probability of miss detection is deduced for the decoding algorithms. Performance analysis and simulation results show that the proposed constellations outperform the conventional constellations and the proposed decoding algorithms are efficient and simple.

An MMSE Decoding Algorithm without Matrix Inversion in QSTBC

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.

An FPGA-based LDPC decoder with optimized scale factor of NMS decoding algorithm

Considering that the hardware implementation of the normalized minimum sum(NMS)decoding algorithm for low-density parity-check(LDPC)code is difficult due to the uncertainty of scale factor,an NMS decoding algorithm with variable scale factor is proposed for the near-earth space LDPC codes(8177,7154)in the consultative committee for space data systems(CCSDS)standard.The shift characteristics of field programmable gate array(FPGA)is used to optimize the quantization data of check nodes,and finally the function of LDPC decoder is realized.The simulation and experimental results show that the designed FPGA-based LDPC decoder adopts the scaling factor in the NMS decoding algorithm to improve the decoding performance,simplify the hardware structure,accelerate the convergence speed and improve the error correction ability.

Decoding algorithm with multiple features based on optical camera communication system

The performance of decoding algorithm is one of the important influential factors to determine the communication quality of optical camera communication(OCC) system. In this paper, we first propose a decoding algorithm with adaptive thresholding based on the captured pixel values under an ideal environment, and then we further propose a decoding algorithm with multiple features, which is more suitable under the existence of the interference of light sources. The algorithm firstly determines the light-emitting diode(LED) array profile information by removing the interfering light sources through geometric features, and then identifies the LED state by calculating two grayscale features, the average gray ratio(AGR) and the gradient radial inwardness(GRI) of the LEDs, and finally obtains the LED state matrix. The experimental results show that the bit error ratio(BER) of the decoding algorithm with multiple features decreases from 1×10^(-2) to 5×10^(-4) at 80 m.

Decoding algorithms of single photon counting imager based on two-dimensional Vernier anodes

The decoding algorithms of two-dimensional Vernier anodes are deduced theoretically.The precision of decoding and uniqueness of encoding are proved.The influencing factors of detection sensitivity and spatial resolution are discussed.The single photon imaging system is constructed,and the two-dimensional Vernier collector is fabricated.The image of the ultra-weak emission source is reconstructed.The spatial resolution of the system is about 100μm.

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.

Low-Complexity Detection and Decoding Scheme for LDPC-Coded MLC NAND Flash Memory

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.

PERFORMANCE OF SIMPLE-ENCODING IRREGULAR LDPC CODES BASED ON SPARSE GENERATOR MATRIX

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.

Generalized Block Markov Superposition Transmission over Free-Space Optical Links

In free-space optical(FSO) communications, the performance of the communication systems is severely degraded by atmospheric turbulence. Channel coding and diversity techniques are commonly used to combat channel fading induced by atmospheric turbulence. In this paper, we present the generalized block Markov superposition transmission(GBMST) of repetition codes to improve time diversity. In the GBMST scheme, information sub-blocks are transmitted in the block Markov superposition manner, with possibly different transmission memories. Based on analyzing an equivalent system, a lower bound on the bit-error-rate(BER) of the proposed scheme is presented. Simulation results demonstrate that, under a wide range of turbulence conditions, the proposed scheme improves diversity gain with only a slight reduction of transmission rate. In particular, with encoding memory sequence(0, 0, 8) and transmission rate 1/3, a diversity order of eleven is achieved under moderate turbulence conditions. Numerical results also show that, the GBMST systems with appropriate settings can approach the derived lower bound, implying that full diversity is achievable.

Real-Time Implementation for Reduced-Complexity LDPC Decoder in Satellite Communication

In this paper,it has proposed a realtime implementation of low-density paritycheck(LDPC) decoder with less complexity used for satellite communication on FPGA platform.By adopting a(2048.4096)irregular quasi-cyclic(QC) LDPC code,the proposed partly parallel decoding structure balances the complexity between the check node unit(CNU) and the variable node unit(VNU) based on min-sum(MS) algorithm,thereby achieving less Slice resources and superior clock performance.Moreover,as a lookup table(LUT) is utilized in this paper to search the node message stored in timeshare memory unit,it is simple to reuse and save large amount of storage resources.The implementation results on Xilinx FPGA chip illustrate that,compared with conventional structure,the proposed scheme can achieve at last 28.6%and 8%cost reduction in RAM and Slice respectively.The clock frequency is also increased to 280 MHz without decoding performance deterioration and convergence speed reduction.

New concatenated soft decoding of Reed-Solomon codes with lower complexities

To improve error-correcting performance, an iterative concatenated soft decoding algorithm for Reed-Solomon （RS） codes is presented in this article. This algorithm brings both complexity as well as advantages in performance over presently popular sot~ decoding algorithms. The proposed algorithm consists of two powerful soft decoding techniques, adaptive belief propagation （ABP） and box and match algorithm （BMA）, which are serially concatenated by the accumulated log-likelihood ratio （ALLR）. Simulation results show that, compared with ABP and ABP-BMA algorithms, the proposed algorithm can bring more decoding gains and a better tradeoff between the decoding performance and complexity.

Review of brain-computer interface based on steady-state visual evoked potential

The brain-computer interface(BCI)technology has received lots of attention in the field of scientific research because it can help disabled people improve their quality of life.Steady-state visual evoked potential(SSVEP)is the most researched BCI experimental paradigm,which offers the advantages of high signal-to-noise ratio and short training-time requirement by users.In a complete BCI system,the two most critical components are the experimental paradigm and decoding algorithm.However,a systematic combination of the SSVEP experimental paradigm and decoding algorithms is missing in existing studies.In the present study,the transient visual evoked potential,SSVEP,and various improved SSVEP paradigms are compared and analyzed,and the problems and development bottlenecks in the experimental paradigm are finally pointed out.Subsequently,the canonical correlation analysis and various improved decoding algorithms are introduced,and the opportunities and challenges of the SSVEP decoding algorithm are discussed.

Block Markov superposition transmission with pulse position modulation over free-space optical links

In FSO(Free-Space Optical)communications,performance of the communication systems is severely degraded by atmospheric turbulence.PPM(Pulse Position Modulation)is widely used in FSO communication systems owing to its high power efficiency.In this paper,we present a combination of the BMST(Block Markov Superposition Transmission)technique and the PPM scheme to improve the reliability of the transmission over FSO links.Based on analyzing an equivalent system,a lower bound on the bit-error-rate of the proposed scheme is presented.Extensive simulations are performed which show that the BMST-PPM system performs well under a wide range of turbulence conditions and improves the performance of the basic code.Simulation results also show that,the performance of the system with the sliding-window detection/decoding algorithm matches well with the lower bound in the low-error-rate region.