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Finite Blocklength Analysis of Gaussian random coding in AWGN Channels Under Covert Constraint

IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY 2021年 16卷 1261-1274页

作者： Yu, Xinchun Wei, Shuangqing Luo, Yuan Shanghai Jiao Tong Univ Sch Elect Informat & Elect Engn Shanghai 200240 Peoples R China Louisiana State Univ Sch Elect Engn & Comp Sci Div Elect & Comp Engn Baton Rouge LA 70803 USA

It is well known that finite blocklength analysis plays an important role in evaluating performances of communication systems in practical settings. This paper considers the achievability and converse bounds on the maximal channel coding rate (throughput) at a given blocklength and error probability in covert communication over AWGN channels. The covert constraint is given in terms of an upper bound on total variation distance (TVD) between the distributions of eavesdropped signals at an adversary with and without presence of active and legitimate communication, respectively. For the achievability, Gaussian random coding scheme is adopted for convenience in the analysis of TVD. The classical results of finite blocklength regime are not applicable in this case. By exploiting and extending canonical approaches, we first present new and more general achievability bounds for random coding schemes under maximal or average probability of error requirements. The general bounds are then applied to covert communication in AWGN channels where codewords are generated from Gaussian distribution while meeting the maximal power constraint. We further show an interesting connection between attaining tight achievability and converse bounds and solving two total variation distance based minimax and maxmin problems. The TVD constraint is analyzed under the given random coding scheme, which induces bounds on the transmission power through divergence inequalities. Further comparison is made between the new achievability bounds and existing ones derived under deterministic codebooks. Our thorough analysis thus leads us to a comprehensive characterization of the attainable throughput in covert communication over AWGN channels.

关键词： AWGN channels Encoding Gaussian distribution Throughput Measurement Channel models Transmitters Finite blocklengh achievability and converse bounds random coding Gaussian codebooks maximum power constraint

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Massive Gaussian Multiple-Access by random coding With Soft Interference Cancellation

Massive Gaussian Multiple-Access by Random Coding With Soft ...

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IEEE International Conference on Communications (ICC)

作者： Muller, Ralf R. Friedrich Alexander Univ Erlangen Nurnberg Inst Digital Commun Erlangen Germany

ISBN: (纸本)9781728171227

We utilize recent results on the exact block error probability of Gaussian random codes in additive white Gaussian noise to analyze Gaussian random coding for massive multiple-access at finite message length. Soft iterative interference cancellation is found to closely approach the performance bounds recently found in [1]. The existence of two fundamentally different regimes in the trade-off between power and bandwidth efficiency reported in [2] is related to much older results in [3] on power optimization by linear programming. Furthermore, we tighten the achievability bounds of [1] in the low power regime and show that orthogonal constellations are very close to the theoretical limits for message lengths around 100 and above.

关键词： multiple-access successive cancellation iterative decoding finite blocklength block error probability random coding low-latency communications spectral efficiency

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High Capacity Neural Block Classifiers with Logistic Neurons and random coding

High Capacity Neural Block Classifiers with Logistic Neurons...

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International Joint Conference on Neural Networks (IJCNN) held as part of the IEEE World Congress on Computational Intelligence (IEEE WCCI)

作者： Adigun, Olaoluwa Kosko, Bart Univ Southern Calif Dept Elect & Comp Engn Signal & Image Proc Inst Los Angeles CA 90089 USA

ISBN: (纸本)9781728169262

We show that neural networks with logistic output neurons and random codewords can store and classify far more patterns than those that use softmax neurons and 1-in-K encoding. Logistic neurons can choose binary codewords from an exponentially large set of codewords. random coding picks the binary or bipolar codewords for training such deep classifier models. This method searched for the bipolar codewords that minimized the mean of an inter-codeword similarity measure. The method used blocks of networks with logistic input and output layers and with few hidden layers. Adding such blocks gave deeper networks and reduced the problem of vanishing gradients. It also improved learning because the input and output neurons of an interior block must equal the input pattern's code word. Deep-sweep training of the neural blocks further improved the classification accuracy. The networks trained on the CIFAR-100 and the Caltech-256 image datasets. Networks with 40 output logistic neurons and random coding achieved much of the accuracy of 100 softmax neurons on the CIFAR-100 patterns. Sufficiently deep random-coded networks with just 80 or more logistic output neurons had better accuracy on the Caltech-256 dataset than did deep networks with 256 softmax output neurons.

关键词： logistic network blocking random coding deep sweep training backpropagation invariance

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A Hardware Realization of Superresolution Combining random coding and Blurring

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IEEE TRANSACTIONS ON COMPUTATIONAL IMAGING 2019年第3期5卷 366-380页

作者： Beale, Kevin Chen, Jianbo Giljum, Anthony Kelly, Kevin F. Romberg, Justin Georgia Inst Technol Dept Elect & Comp Engn Atlanta GA 30332 USA Rice Univ Dept Elect & Comp Engn POB 1892 Houston TX 77251 USA

Resolution enhancements are often desired in imaging applicationswhere high-resolution sensor arrays are difficult to obtain. Many computational imaging methods have been proposed to encode high-resolution scene information on low-resolution sensors by cleverly modulating light from the scene before it hits the sensor. These methods often employ movement of some portion of the imaging apparatus, only to acquire images up to the resolution of a modulating element, or require extensive postprocessing to recover the high-resolution image. In this paper, a technique is presented for resolving beyond the resolutions of both a pointwise-modulating mask element and a sensor array through the introduction of a controlled blur into the optical pathway. This proposed "hardware" superresolution method can be applied without machine learning and is shown to outperform standard software-only methods. The analysis contains an intuitive and exact expression for the overall superresolvability of the system, and arguments are presented to explain how the combination of random coding and blurring makes the superresolution problem well-posed. Experimental results demonstrate that resolution enhancements of approximately 4xand higher are possible in practice using standard optical components, withoutmechanical motion of the imaging apparatus, and without any a priori assumptions on scene structure.

关键词： Superresolution random coding digital micromirror device

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Total Variation Distance and Improved random coding Union Bounds

Total Variation Distance and Improved Random Coding Union Bo...

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IEEE Global Communications Conference (GLOBECOM)

作者： Letzepis, Nick Def Sci & Technol Grp Cyber & Elect Warfare Div West Ave Edinburgh SA 5111 Australia Def Sci & Technol Grp Cyber & Elect Warfare Div West Ave Adelaide SA Australia

ISBN: (纸本)9781728109626

This paper presents two new upper bounds on the probability of error for maximum likelihood decoding in the finite blocklength regime. The first bound applies to fixed channel codes and uses the well-known union bound to express the probability of decoding error in terms of the total variation distance between the conditional transition probabilities. It is shown that this bound is tighter than the Bhattacharyya union bound and its variants. The second bound is an improvement on the random coding Union bound. In fact, the only decoding events that render it an upper bound, rather than an equality, are the ties a maximum likelihood decoder resolves in favour of the correct codeword. These bounds are then used to give new results for random spherical codes on the Gaussian channel.

关键词： Total variation distance random coding sphere-packing bound Bhattacharyya union bound

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A Unified random coding Bound

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IEEE TRANSACTIONS ON INFORMATION THEORY 2018年第10期64卷 6779-6802页

作者： Lee, Si-Hyeon Chung, Sae-Young Pohang Univ Sci & Technol Dept Elect Engn Pohang 37673 South Korea Korea Adv Inst Sci & Technol Dept Elect Engn Daejeon 34141 South Korea

In this paper, we prove a unified achievability bound that generalizes and improves random coding bounds for any combination of source coding, channel coding, joint source-channel coding, and coding for computing problems assuming blockwise node operation. As a general network setup, we consider an acyclic discrete memoryless network, where the network demands and constraints are specified by a joint-typicality constraint on the whole channel input and output sequences. For achievability, a basic building block for node operation consists of simultaneous nonunique decoding, simultaneous compression, and symbol-by-symbol mapping. Our hound can be useful for deriving random coding bounds without error analysis, especially for large and complex networks. In particular, our hound can be used for unifying and generalizing many known relaying strategies. For example, a generalized decode-compressamplify-and-forward bound is obtained as a simple corollary of our main theorem, and it is shown to strictly outperform the previously known relaying schemes. Furthermore, by exploiting the symmetry in our bound, we formally define and characterize three types of network duality based on channel input-output reversal and network flow reversal combined with packing-covering duality.

关键词： Unified approach achievability random coding decode-compress-amplify-and-forward duality

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Exact Asymptotics of random coding Error Probability for General Memoryless Channels

Exact Asymptotics of Random Coding Error Probability for Gen...

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IEEE International Symposium on Information Theory (ISIT)

作者： Honda, Junya Univ Tokyo Tokyo Japan RIKEN Wako Saitama Japan

ISBN: (纸本)9781538647813

This paper considers the error probability of random coding for memoryless channels in the fixed-rate regime. random coding is a fundamental tool to construct a capacity-achieving channel code and many studies have been conducted for the asymptotics of the decoding error probability. Gallager derived the exact asymptotics (that is, an evaluation with asymptotically vanishing relative error) of the error probability below the critical rate. On the other hand, the asymptotics for the rate above the critical rate has been unknown except for symmetric channels (in the strong sense) and strongly nonlattice channels. This paper derives the exact asymptotics for general memoryless channels covering all previously unsolved cases. The analysis reveals that strongly symmetric channels and strongly nonlattice channels correspond to two extreme cases and the expression of the asymptotics is much complicated for general channels.

关键词： channel coding random coding error exponent finite-length analysis local limit theorem

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random coding Error Exponents for the Two-User Interference Channel

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IEEE TRANSACTIONS ON INFORMATION THEORY 2017年第2期63卷 1019-1042页

作者： Huleihel, Wasim Merhav, Neri Technion Israel Inst Technol Andrew & Erna Viterbi Fac Elect Engn IL-3200003 Haifa Israel

This paper is about deriving lower bounds on the error exponents for the two-user interference channel under the random coding regime for several ensembles. Specifically, we first analyze the standard random coding ensemble, where the codebooks are comprised of independently and identically distributed (i.i.d.) codewords. For this ensemble, we focus on optimum decoding, which is in contrast to other, suboptimal decoding rules that have been used in the literature (e.g., joint typicality decoding, treating interference as noise, and so on). The fact that the interfering signal is a codeword, rather than an i.i.d. noise process, complicates the application of conventional techniques of performance analysis of the optimum decoder. In addition, unfortunately, these conventional techniques result in loose bounds. Using analytical tools rooted in statistical physics, as well as advanced union bounds, we derive single-letter formulas for the random coding error exponents. We compare our results with the best known lower bound on the error exponent, and show that our exponents can be strictly better. Then, in the second part of this paper, we consider more complicated coding ensembles and find a lower bound on the error exponent associated with the celebrated Han-Kobayashi random coding ensemble, which is based on superposition coding.

关键词： random coding error exponent interference channels superposition coding Han-Kobayashi scheme statistical physics optimal decoding multiuser communication

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A Note on random coding Bounds for Classical-Quantum Channels

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PROBLEMS OF INFORMATION TRANSMISSION 2017年第3期53卷 222-228页

作者： Dalai, M. Univ Brescia Dept Informat Engn Brescia Italy

A modified derivation of achievability results in classical-quantum channel coding theory is proposed, which has, in our opinion, two main benefits over previously used methods: it allows to (i) follow in a simple and clear way how binary hypothesis testing relates to channel coding achievability results, and (ii) derive in a unified way all previously known random coding achievability bounds on error exponents for classical and classical-quantum channels.

关键词： Hypothesis testing random coding binary hypothesis testing Bound Channel coding

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Inkjet-printed random coding metal particles for modulation enhancement of an optical-controlled terahertz wave modulator

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OPTICAL AND QUANTUM ELECTRONICS 2016年第1期48卷 1-8页

作者： Chen, Kejian Bu, Ting Bai, Yang Zhuang, Songlin Univ Shanghai Sci & Technol Engn Res Ctr Opt Instrument & Syst Shanghai Key Lab Modern Opt Syst Minist Educ Shanghai 200093 Peoples R China

The modulation enhancement performance of inkjet-printed random coding metal particles lattice is studied in this paper. By optimizing duty ratio of metal particles lattice, the modulation depth of optical-controlled terahertz wave modulators can reach to 62 and 83 % with periodic configuration and random coding structure, respectively. Their optimized modulation depths are nearly 1.3 times and 1.7 times of reference device, respectively. The random coding device has better performance mainly because the random distribution lattice leads more incident pumping light to be absorbed by substrate material due to the multiple scattering. Besides, the influence of different solvent heating treatments on modulation depth is also studied in this paper. The heating treatment with hotplate has more opportunity to form high quality metal particles and greatly improves the performance of modulator. Our study not only provides an alternative route to develop high performance optical-controlled terahertz wave modulators, but also brings an alternative way to other research area such as terahertz antenna, solar cell, etc.

关键词： Terahertz Modulators random coding Inkjet printing

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