The Design of Vertical RS-CRC and LDPC Code for Ship-Based Satellite Communications On-the-Move

Wang, Bingrui; Chen, Pingping; Fang, Yi; Lau, Francis C. M.

doi:10.1109/access.2019.2895746

Cited by 9 publications

(7 citation statements)

References 33 publications

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“…Widespread possibilities for error detection and correction can be realized by encoding and decoding the transmitted data. Some types of errorcorrection codes such as convolution codes, RS codes, Turbo codes, BCH codes, and LDPC codes are used [37].…”

Section: B Multi Coding Processmentioning

confidence: 99%

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Performance Analysis of 3D Video Transmission Over Deep-Learning-Based Multi-Coded N-ary Orbital Angular Momentum FSO System

et al. 2021

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Orbital angular momentum-shift keying (OAM-SK), which is the rapid switching of OAM modes, is vital but seriously impeded by the deficiency of OAM demodulation techniques, particularly when videos are transferred over the system. Thus, in this paper, 3D chaotic interleaved multi-coded video frames (VFs) are conveyed via an N-OAM-SK free space optic (FSO) communication system to enhance the reliability and efficiency of the model. To tackle the defects of the OAM-SK-FSO mechanism, two efficient deep learning (DL) techniques, namely convolution recurrent neural network (CRNN) and 3D convolution neural network (3DCNN) are used to decode OAM modes with a lower BER. Moreover, a graphics processing unit (GPU) is used to accelerate the training process with slight power consumption. The utilized datasets for OAM states are generated by applying different scenarios using trial and error method. The simulation results imply that LDPC coded VFs achieve the greatest peak signal-to-noise ratios (PSNRs) and the lowest BERs using the 16-OAM-SK model. Both 3DCNN and CRNN techniques have nearly the same performance, but this performance deteriorates in the case of larger dataset classes. Moreover, the GPU accelerates the performance by almost 67.6% and 36.9% using CRNN and 3DCNN techniques, respectively. These two DL techniques are more effective in evaluating the classification accuracy than the other traditional techniques by almost 10 − 20%.

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Section: B Multi Coding Processmentioning

confidence: 99%

“…Finally, we calculate the image quality matrices between the reconstructed image and the original image using the following measures [37], [44]:…”

Section: ;mentioning

confidence: 99%

Performance Analysis of 3D Video Transmission Over Deep-Learning-Based Multi-Coded N-ary Orbital Angular Momentum FSO System

et al. 2021

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“…Consequently, they have long been in the focus of coding theorists as well as coding practitioners [3]. There is vigorous research concerning these codes and their decoding algorithms even 60 years after their discovery, which could be documented by the following selected references [6][7][8][9][10][11][12]. Therefore, there are numerous known algorithms for their encoding as well as for decoding.…”

Section: Some Notes On Rs Code Decodingmentioning

confidence: 99%

Erasure decoding of five times extended Reed-Solomon codes

Rakús

Farkas

Palenik

2019

Journal of Electrical Engineering

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“…W ITH the fast development of communication technologies, the requirements on forward-errorcorrection (FEC) codes are becoming more and more rigorous. Among the good FEC codes, turbo codes [1][2][3], lowdensity parity-check (LDPC) codes [4][5][6][7] and polar codes [8][9][10][11] have been intensively studied because they can perform close to the capacity limits. In addition, turbo Hadamard codes (THCs) [12], LDPC Hadamard codes [13] and concatenated zigzag Hadamard codes [14] have been shown to perform well even near the ultimate Shannon limit (i.e., −1.59 dB).…”

Section: Introductionmentioning

confidence: 99%

Hardware Design of Concatenated Zigzag Hadamard Encoder/Decoder System With High Throughput

2020

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Both turbo Hadamard codes and concatenated zigzag Hadamard codes are ultimate-Shannonlimit-approaching channel codes. The former one requires the use of Bahl-Cocke-Jelinek-Raviv (BCJR) in the iterative decoding process, making the decoder structure more complex and limiting its throughput. The latter one, however, does not involve BCJR decoding. Hence its decoder structure can be much simpler and can potentially operate at a much higher throughput. In this paper, we investigate the hardware design of a concatenated zigzag Hadamard encoder/decoder system and implement it onto an FPGA board. We design a decoder capable of decoding multiple codewords at the same time, and the proposed system can operate with a throughput of 1.44 Gbps-an increase of 50% compared with the turbo Hadamard encoder/decoder system. As for the error performance, the encoder/decoder system with a 6-bit quantization achieves a bit error rate of 2 × 10 −5 at E b /N 0 = −0.2 dB. INDEX TERMS concatenated zigzag Hadamard code, hardware design, high throughput, turbo Hadamard code, zigzag Hadamard code.

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The Design of Vertical RS-CRC and LDPC Code for Ship-Based Satellite Communications On-the-Move

Cited by 9 publications

References 33 publications

Performance Analysis of 3D Video Transmission Over Deep-Learning-Based Multi-Coded N-ary Orbital Angular Momentum FSO System

Performance Analysis of 3D Video Transmission Over Deep-Learning-Based Multi-Coded N-ary Orbital Angular Momentum FSO System

Erasure decoding of five times extended Reed-Solomon codes

Hardware Design of Concatenated Zigzag Hadamard Encoder/Decoder System With High Throughput

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