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convolutional coding FOR BPSK SYSTEM WITH ORTHOGONAL SOUNDING TONE ON FAST RAYLEIGH FADING CHANNEL

ELECTRONICS LETTERS 1986年第24期22卷 1277-1278页

作者： CHEN, YL WEI, CH Institute of Electronics National Chiao Tung University Hsin-Chu Republic of China

For combating the fast Rayleigh fading usually encountered in mobile communication channels, convolutional coding and Viterbi decoding together with interleaving and the BPSK system using an orthogonal sounding tone are considered. The bit error probability performance of the system is analysed, and numerical results for the systems with rate-½ optimum codes of constraint lengths K = 3 to 7 are also provided.

关键词： Mobile radio systems orthogonal sounding tone interleaving Viterbi decoding digital communication digital communication systems BPSK system numerical results Codes mobile communication channels error statistics mobile communication systems fading bit error probability performance codes phase shift keying convolutional coding fast Rayleigh fading channel

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Signal design and convolutional coding for noncoherent space-time communication on the block-Rayleigh-fading channel

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IEEE TRANSACTIONS ON INFORMATION THEORY 2002年第5期48卷 1186-1194页

作者： McCloud, ML Brehler, M Varanasi, MK Univ Colorado Dept Elect & Comp Engn Boulder CO 80309 USA

We consider the problem of designing signal constellations for the multiple transmit-multiple receive antenna Rayleigh-fading communication channel, when neither the transmitter nor the receiver know the fading. In particular, by employing the asymptotic union bound (AUB) on the probability of error, we give a new formulation of the problem of signal design for the noncoherent fading channel. Since unitary signals are optimal for this channel (in the limit of large signal-to-noise ratios SNRs), the problem can be posed in terms of packings on the Grassmanian manifold. A key difference in our approach from that of other authors is that we use a notion of distance on this manifold that is suggested by the union bound. As a consequence of our use of this distance measure, we obtain signal designs that are guaranteed to achieve the full diversity order of the channel, a result that does not hold when the chordal distance is used. We introduce a new method of recursively designing signals, termed successive updates, to approximately optimize this performance measure. We then examine the use of our signals with several convolutional codes over the fading channel. An upper bound on the bit error probability of the maximum-likelihood decoder is presented together with an asymptotic analysis of that bound.

关键词： convolutional coding fading channels noncoherent communication signal design space-time modulation

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IMPROVED HF MODEM USING convolutional coding

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ELECTRONICS & COMMUNICATION ENGINEERING JOURNAL 1992年第2期4卷 73-82页

作者： HONARY, B ZOLGHADR, F DARNELL, M MAUNDRELL, M UNIV HULL DEPT ELECTR ENGNHULL HU6 7RXN HUMBERSIDEENGLAND ROYAL AIRCRAFT ESTAB CTR DEF RES AGCYFARNBOROUGH GU14 6TDHANTSENGLAND

The paper describes the design of a digitally implemented modem for use over HF (2-30 MHz) radio channels. As a completely digital approach offers the prospect of a number of significant improvements, a new digital multifrequency-shift-keying (MFSK) modem has been developed that employs a novel digital processing procedure termed code-assisted bit synchronisation (CABS). Signal detection is achieved via a set of noncoherent correlators, whilst symbol synchronisation and error correction are performed using a soft-decision Viterbi decoder. Practical tests of the modem show that it operates effectively under both additive white Gaussian noise and real HF channel conditions.

关键词： error correction frequency shift keying digital radio modem Codes 2 to 30 MHz additive white Gaussian noise convolutional coding digital multifrequency-shift-keying real HF channel conditions digital radio systems encoding signal detection Other telecommunication terminals and equipment Radio links and equipment soft-decision Viterbi decoder modems noncoherent correlators synchronisation code-assisted bit synchronisation symbol synchronisation

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MRCON-Net: Multiscale reweighted convolutional coding neural network for low-dose CT imaging

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COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2022年 221卷 106851-106851页

作者： Liu, Jin Kang, Yanqin Xia, Zhenyu Qiang, Jun Zhang, JunFeng Zhang, Yikun Chen, Yang Anhui Polytech Univ Coll Comp & Informat Wuhu Peoples R China Henan Univ Econ & Law Sch Comp & Informat Engn Zhengzhou Peoples R China Southeast Univ Key Lab Comp Network & Informat Integrat Minist Educ Nanjing Peoples R China Southeast Univ Sch Cyber Sci & Engn Nanjing Peoples R China Southeast Univ Sch Comp Sci & Engn Nanjing Peoples R China

Background and objective: Low-dose computed tomography (LDCT) has become increasingly important for alleviating X-ray radiation damage. However, reducing the administered radiation dose may lead to degraded CT images with amplified mottle noise and nonstationary streak artifacts. Previous studies have confirmed that deep learning (DL) is promising for improving LDCT imaging. However, most DL-based frameworks are built intuitively, lack interpretability, and suffer from image detail information loss, which has become a general challenging issue. Methods: A multiscale reweighted convolutional coding neural network (MRCON-Net) is developed to address the above problems. MRCON-Net is compact and more explainable than other networks. First, inspired by the learning-based reweighted iterative soft thresholding algorithm (ISTA), we extend traditional convolutional sparse coding (CSC) to its reweighted convolutional learning form. Second, we use dilated convolution to extract multiscale image features, allowing our single model to capture the correlations between features of different scales. Finally, to automatically adjust the elements in the feature code to correct the obtained solution, a channel attention (CA) mechanism is utilized to learn appropriate weights. Results: The visual results obtained based on the American Association of Physicians in Medicine (AAPM) Challenge and United Image Healthcare (UIH) clinical datasets confirm that the proposed model significantly reduces serious artifact noise while retaining the desired structures. Quantitative results show that the average structural similarity index measurement (SSIM) and peak signal-to-noise ratio (PSNR) achieved on the AAPM Challenge dataset are 0.9491 and 40.66, respectively, and the SSIM and PSNR achieved on the UIH clinical dataset are 0.915 and 42.44, respectively;these are promising quantitative results. Conclusion: Compared with recent state-of-the-art methods, the proposed model achieves subtle struct

关键词： Low-dose CT convolutional coding Multiscale Reweighted learning

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D³C²-Net: Dual-Domain Deep convolutional coding Network for Compressive Sensing

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2024年第10期34卷 9341-9355页

作者： Li, Weiqi Chen, Bin Liu, Shuai Zhao, Shijie Du, Bowen Zhang, Yongbing Zhang, Jian Peking Univ Sch Elect & Comp Engn Shenzhen 518055 Peoples R China Tsinghua Univ Grad Sch Shenzhen Shenzhen 518055 Peoples R China ByteDance Inc Shenzhen 518055 Peoples R China Tongji Univ Sch Software Engn Shanghai 200092 Peoples R China Harbin Inst Technol Shenzhen Sch Comp Sci & Technol Shenzhen 518055 Peoples R China

By mapping iterative optimization algorithms into neural networks (NNs), deep unfolding networks (DUNs) exhibit well-defined and interpretable structures and achieve remarkable success in the field of compressive sensing (CS). However, most existing DUNs solely rely on the image-domain unfolding, which restricts the information transmission capacity and reconstruction flexibility, leading to their loss of image details and unsatisfactory performance. To overcome these limitations, this paper develops a dual-domain optimization framework that combines the priors of (1) image- and (2) convolutional-coding-domains and offers generality to CS and other inverse imaging tasks. By converting this optimization framework into deep NN structures, we present a Dual-Domain Deep convolutional coding Network ((DC2)-C-3-Net), which enjoys the ability to efficiently transmit high-capacity self-adaptive convolutional features across all its unfolded stages. Our theoretical analyses and experiments on simulated and real captured data, covering 2D and 3D natural, medical, and scientific signals, demonstrate the effectiveness, practicality, superior performance, and generalization ability of our method over other competing approaches and its significant potential in achieving a balance among accuracy, complexity, and interpretability. Code is available at https://***/lwq20020127/D3C2-Net.

关键词： convolutional codes Convolution Optimization Encoding Artificial neural networks Image reconstruction Image coding Compressive sensing inverse imaging problem image restoration convolutional coding deep unfolding network

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Efficient and Robust Distributed Matrix Computations via convolutional coding

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IEEE TRANSACTIONS ON INFORMATION THEORY 2021年第9期67卷 6266-6282页

作者： Das, Anindya Bijoy Ramamoorthy, Aditya Vaswani, Namrata Iowa State Univ Dept Elect & Comp Engn Ames IA 50011 USA

Distributed matrix computations - matrix-matrix or matrix-vector multiplications - are well-recognized to suffer from the problem of stragglers (slow or failed worker nodes). Much of prior work in this area is (i) either sub-optimal in terms of its straggler resilience, or (ii) suffers from numerical problems, i.e., there is a blow-up of round-off errors in the decoded result owing to the high condition numbers of the corresponding decoding matrices. Our work presents a convolutional coding approach to this problem that removes these limitations. It is optimal in terms of its straggler resilience, and has excellent numerical robustness as long as the workers' storage capacity is slightly higher than the fundamental lower bound. Moreover, it can be decoded using a fast peeling decoder that only involves add/subtract operations. Our second approach has marginally higher decoding complexity than the first one, but allows us to operate arbitrarily close to the storage capacity lower bound. Its numerical robustness can be theoretically quantified by deriving a computable upper bound on the worst case condition number over all possible decoding matrices by drawing connections with the properties of large block Toeplitz matrices. All above claims are backed up by extensive experiments done on the AWS cloud platform.

关键词： Decoding Encoding convolutional codes Numerical stability Complexity theory Resilience Matrix decomposition Distributed computing straggler convolutional coding Toeplitz matrix Vandermonde matrix

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A Wireless OFDM Control System of SCIG for Applications in Smart Grids Jointly Employing convolutional coding and FWMA Filtering

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JOURNAL OF CONTROL AUTOMATION AND ELECTRICAL SYSTEMS 2019年第3期30卷 360-370页

作者： Sguarezi, A. J. Solis-Chaves, J. S. de Almeida, L. A. L. Costa, Fabiano F. Casella, I. R. S. Capovilla, C. E. Fed Univ ABC UFABC Engn Modeling & Appl Social Sci Ctr CECS Santo Andre SP Brazil Univ Fed Bahia Salvador BA Brazil

In this paper, a new power control system for wind turbines based on a squirrel cage induction generator linked to the mains by means of a back-to-back converter for smart grid applications is proposed. The wireless system employs orthogonal frequency division multiplexing, convolutional coding, and functionally weighted moving average filtering to improve the system performance against the errors due to the propagation channel in the transmitted power references. Hence, the system avoids damages in turbines and converters and also increases the power quality of the power injected into the grid. Hence, the reactive power injection can be helpful in ancillary services. The system was analyzed regarding the total harmonic distortion for SCIGs' currents and the system response to verifying the delivered power quality by the generator to the mains. The simulated results validate the proposed wireless-coded control system.

关键词： Squirrel cage induction generator Wind energy Smart grids Wireless communications convolutional coding Functionally weighted moving average filter

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A Noise-Robust Online convolutional coding model and its applications to poisson denoising and image fusion

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APPLIED MATHEMATICAL MODELLING 2021年 95卷 644-666页

作者： Wang, Wei Xia, Xiang-Gen He, Chuanjiang Ren, Zemin Wang, Tianfu Lei, Baiying Shenzhen Univ Natl Reg Key Technol Engn Lab Med Ultrasound Guangdong Key Lab Biomed Measurements & Ultrasoun Sch Biomed EngnHlth Sci Ctr Shenzhen Peoples R China Univ Delaware Dept Elect & Comp Engn Newark DE 19716 USA Chongqing Univ Coll Math & Stat Chongqing 401331 Peoples R China Chongqing Univ Sci & Technol Coll Math & Phys Chongqing 401331 Peoples R China

In this paper, we propose a noise-robust online convolutional coding model for image representation, which can use the noisy images as training data. Then an alternating algorithm is utilized to convert the model into two sub-problems, the image pursuit problem and the dictionary learning problem. For the image pursuit problem, the Gauss elimination method is used to solve the equation set which is derived by the Euler equation and discrete Fourier transform. For the dictionary learning problem, a gradient-descent flow is derived to solve it. Experimental results show that our method can output more meaningful feature representations compared to the related models while the training data was corrupted by Poisson noise. (c) 2021 Elsevier Inc. All rights reserved.

关键词： convolutional coding convolutional dictionary learning Online dictionary learning Gradient descent flow

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PERFORMANCE OF convolutional coding WITH SYMBOL ERASURE FOR QPSK FREQUENCY-SELECTIVE FADING CHANNELS

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IEICE TRANSACTIONS ON COMMUNICATIONS 1993年第2期E76B卷 139-147页

作者： ZHOU, H DENG, RH NATL UNIV SINGAPORE DEPT ELECT ENGN SINGAPORE 0511 SINGAPORE NATL UNIV SINGAPORE DEPT ELECT & COMP ENGN SINGAPORE 0511 SINGAPORE

In this paper, we study the performance of convolutional coding using an error-and-erasure correction Viterbi decoder for pi/4-shift QDPSK mobile radio transmission. The receiver uses received signal envelope as channel state information to erase unreliable symbols instead of making explicit decision before decoding. The performance study is carried out over frequency-selective fading channel with additive white Gaussian noise, co-channel interference and propagation delay spread. The results show that decoding with symbol erasure can significantly improve the system transmission performance compared to decoding without symbol erasure.

关键词： FREQUENCY-SELECTIVE FADING convolutional coding ERROR-AND-ERASURE CORRECTION VITERBI DEcoding

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Improving the capacity of CDMA systems using convolutional coding and interference cancellation

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IEE PROCEEDINGS-COMMUNICATIONS 1998年第3期145卷 186-190页

作者： Band, IW Cruickshank, DGM Univ Edinburgh Dept Elect & Elect Engn Signals & Syst Grp Edinburgh EH9 3JL Midlothian Scotland

The authors compare methods of reducing the co-channel interference on a DS-CDMA downlink signal by employing convolutional coding at the base station and a Viterbi decoder as the initial estimator for a parallel cancellation scheme. The combination of a matched filter and the Viterbi algorithm is shows to afford increased performance compared to equivalent bandwidth systems which do not use forward error correction. The use of a Wiener filter to collapse the spectrum of the spread signal leads to even greater capacity improvements. The systems discussed may be implemented with an affordable increase in receiver complexity and processing delay.

关键词： convolutional coding interference cancellation CDMA systems co-channel interference

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