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JET: Joint source and channel coding for error resilient virtual reality video wireless transmission

SIGNAL PROCESSING 2018年 147卷 154-162页

作者： Liu, Zhi Ishihara, Susumu Cui, Ying Ji, Yusheng Tanaka, Yoshiaki Shizuoka Univ 3-5-1 Johoku Hamamatsu Shizuoka 4328561 Japan Shanghai Jiao Tong Univ 800 Dongchuan Rd Minhang Qu 200240 Peoples R China Natl Inst Informat Chiyoda Ku 2-1-2 Hitotsubashi Tokyo 1018430 Japan Waseda Univ Shinjuku Ku 3-4-1 Okubo Tokyo 1698555 Japan

Virtual reality (VR) provides users extraordinary viewing experience and draws more and more attentions from both industry and academia. In this paper, we propose JET: Joint source and channel coding for Error resilient virtual reality video wireless Transmission, where we jointly investigate how to conquer the problem of source video's huge size, how to efficiently satisfy a user's view switch request and how to handle packet loss. Specifically, we first divide a VR video into smaller video tiles. Upon a user's view switch request, the tiles corresponding to the part that the user is requesting, referred to as the field of view (FoV), and the part that the user may switch to before new video can be received, are delivered over a wireless network. We consider unequal error protection (UEP) for FoV and the rest part and formulate the inherent error resilient VR video transmission problem into a joint source and channel coding problem. In particular, we optimize the tile partition, quantization parameter and Forward Error Correction (FEC) packet allocation to maximize a user's received video quality. We also propose a low-complexity heuristic algorithm to solve this optimization problem. Extensive simulations are conducted and simulation results verify the superior performance. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Virtual reality VR 360 video source and channel coding Video streaming Error resilient

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Delay-Limited source and channel coding of Quasi-Stationary sources over Block Fading channels: Design and Scaling Laws

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IEEE TRANSACTIONS ON COMMUNICATIONS 2013年第4期61卷 1562-1572页

作者： Joda, Roghayeh Lahouti, Farshad Univ Tehran Coll Engn Ctr Wireless Multimedia Commun Ctr Excellence Appl Elect SystSch Elect & Comp E Tehran 14395515 Iran

In this paper, delay-limited transmission of quasi-stationary sources over block fading channels is considered. Considering distortion outage probability as the performance measure, two source and channel coding schemes with power adaptive transmission are presented. The first one is optimized for fixed rate transmission, and hence enjoys simplicity of implementation. The second one is a high performance scheme, which also benefits from optimized rate adaptation with respect to source and channel states. In high SNR regime, the performance scaling laws in terms of outage distortion exponent and asymptotic outage distortion gain are derived, where two schemes with fixed transmission power and adaptive or optimized fixed rates are considered as benchmarks for comparisons. Various analytical and numerical results are provided which demonstrate a superior performance for source and channel optimized rate and power adaptive scheme. It is also observed that from a distortion outage perspective, the fixed rate adaptive power scheme substantially outperforms an adaptive rate fixed power scheme for delay-limited transmission of quasi-stationary sources over wireless block fading channels. The effect of the characteristics of the quasi-stationary source on performance, and the implication of the results for transmission of stationary sources are also investigated.

关键词： Outage capacity quasi-stationary source outage distortion source and channel coding rate and power adaptation

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Sparse approximation based on a random overcomplete basis

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JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT 2016年第6期2016卷 063302-063302页

作者： Nakanishi-Ohno, Yoshinori Obuchi, Tomoyuki Okada, Masato Kabashima, Yoshiyuki Univ Tokyo Grad Sch Frontier Sci Kashiwa Chiba 2778561 Japan Japan Soc Promot Sci Chiyoda Ku Tokyo 1020083 Japan Tokyo Inst Technol Interdisciplinary Grad Sch Sci & Engn Yokohama Kanagawa 2268502 Japan

We discuss a strategy of sparse approximation that is based on the use of an overcomplete basis, and evaluate its performance when a random matrix is used as this basis. A small combination of basis vectors is chosen from a given overcomplete basis, according to a given compression rate, such that they compactly represent the target data with as small a distortion as possible. As a selection method, we study the l(0)- and l(1)-based methods, which employ the exhaustive search and l(1)-norm regularization techniques, respectively. The performance is assessed in terms of the trade-off relation between the distortion and the compression rate. First, we evaluate the performance analytically in the case that the methods are carried out ideally, using methods of statistical mechanics. The analytical result is then confirmed by performing numerical experiments on finite size systems, and extrapolating the results to the infinite-size limit. Our result clarifies the fact that the l(0)-based method greatly outperforms the l(1)-based one. An interesting outcome of our analysis is that any small value of distortion is achievable for any fixed compression rate r in the large-size limit of the overcomplete basis, for both the l(0)- and l(1)-based methods. The difference between these two methods is manifested in the size of the overcomplete basis that is required in order to achieve the desired value for the distortion. As the desired distortion decreases, the required size grows in a polynomial and an exponential manners for the l(0)- and l(1)-based methods, respectively. Second, we examine the practical performances of two well-known algorithms, orthogonal matching pursuit and approximate message passing, when they are used to execute the l(0)- and l(1)-based methods, respectively. Our examination shows that orthogonal matching pursuit achieves a much better performance than the exact execution of the l(1)-based method, as well as approximate message passing. However, regardin

关键词： analysis of algorithms heuristics source and channel coding statistical inference

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Analogy between gambling and measurement-based work extraction

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JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT 2016年第4期2016卷 043403-043403页

作者： Vinkler, Dror A. Permuter, Haim H. Merhav, Neri Ben Gurion Univ Negev Dept Elect & Comp Engn POB 653 IL-84105 Beer Sheva Israel Technion Dept Elect Engn IL-32000 Haifa Israel

In information theory, one area of interest is gambling, where mutual information characterizes the maximal gain in wealth growth rate due to knowledge of side information;the betting strategy that achieves this maximum is named the Kelly strategy. In the field of physics, it was recently shown that mutual information can characterize the maximal amount of work that can be extracted from a single heat bath using measurement-based control protocols, i. e. using 'information engines'. However, to the best of our knowledge, no relation between gambling and information engines has been presented before. In this paper, we briefly review the two concepts and then demonstrate an analogy between gambling, where bits are converted into wealth, and information engines, where bits representing measurements are converted into energy. From this analogy follows an extension of gambling to the continuous-valued case, which is shown to be useful for investments in currency exchange rates or in the stock market using options. Moreover, the analogy enables us to use well-known methods and results from one field to solve problems in the other. We present three such cases: maximum work extraction when the probability distributions governing the system and measurements are unknown, work extraction when some energy is lost in each cycle, e. g. due to friction, and an analysis of systems with memory. In all three cases, the analogy enables us to use known results in order to obtain new ones.

关键词： exact results source and channel coding statistical inference communication supply and information networks

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Typical reconstruction performance for distributed compressed sensing based on l_2,1-norm regularized least square and Bayesian optimal reconstruction: influences of noise

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JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT 2016年第6期2016卷 063304-063304页

作者： Shiraki, Yoshifumi Kabashima, Yoshiyuki NTT Corp NTT Commun Sci Labs Atsugi Kanagawa 2430198 Japan Tokyo Inst Technol Dept Math & Comp Sci Yokohama Kanagawa 2268502 Japan

A signal model called joint sparse model 2 (JSM-2) or the multiple measurement vector problem, in which all sparse signals share their support, is important for dealing with practical signal processing problems. In this paper, we investigate the typical reconstruction performance of noisy measurement JSM-2 problems for l(2,1)-norm regularized least square reconstruction and the Bayesian optimal reconstruction scheme in terms of mean square error. Employing the replica method, we show that these schemes, which exploit the knowledge of the sharing of the signal support, can recover the signals more precisely as the number of channels increases. In addition, we compare the reconstruction performance of two different ensembles of observation matrices: one is composed of independent and identically distributed random Gaussian entries and the other is designed so that row vectors are orthogonal to one another. As reported for the single-channel case in earlier studies, our analysis indicates that the latter ensemble offers better performance than the former ones for the noisy JSM-2 problem. The results of numerical experiments with a computationally feasible approximation algorithm we developed for this study agree with the theoretical estimation.

关键词： analysis of algorithms message-passing algorithms source and channel coding

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source and channel coding for Correlated sources Over Multiuser channels

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IEEE TRANSACTIONS ON INFORMATION THEORY 2009年第9期55卷 3927-3944页

作者： Gunduz, Deniz Erkip, Elza Goldsmith, Andrea Poor, H. Vincent Princeton Univ Dept Elect Engn Princeton NJ 08544 USA Stanford Univ Dept Elect Engn Stanford CA 94305 USA NYU Polytech Inst Dept Elect & Comp Engn Brooklyn NY 11201 USA

source and channel coding over multiuser channels in which receivers have access to correlated source side information are considered. For several multiuser channel models necessary and sufficient conditions for optimal separation of the source and channel codes are obtained. In particular, the multiple-access channel, the compound multiple-access channel, the interference channel, and the two-way channel with correlated sources and correlated receiver side information are considered, and the optimality of separation is shown to hold for certain source and side information structures. Interestingly, the optimal separate source and channel codes identified for these models are not necessarily the optimal codes for the underlying source coding or the channel coding problems. In other words, while separation of the source and channel codes is optimal, the nature of these optimal codes is impacted by the joint design criterion.

关键词： Network information theory separation theorem source and channel coding

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Sequence complexity and work extraction

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JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT 2015年第6期000卷 P06037-P06037页

作者： Merhav, Neri Technion Israel Inst Technol Dept Elect Engn IL-32000 Haifa Israel

We consider a simplified version of a solvable model by Mandal and Jarzynski, which constructively demonstrates the interplay between work extraction and the increase of the Shannon entropy of an information reservoir which is in contact with a physical system. We extend Mandal and Jarzynski's main findings in several directions: first, we allow sequences of correlated bits rather than just independent bits. Secondly, at least for the case of binary information, we show that, in fact, the Shannon entropy is only one measure of complexity of the information that must increase in order for work to be extracted. The extracted work can also be upper bounded in terms of the increase in other quantities that measure complexity, like the predictability of future bits from past ones. Third, we provide an extension to the case of non-binary information (i.e. a larger alphabet), and finally, we extend the scope to the case where the incoming bits (before the interaction) form an individual sequence, rather than a random one. In this case, the entropy before the interaction can be replaced by the Lempel-Ziv (LZ) complexity of the incoming sequence, a fact that gives rise to an entropic meaning of the LZ complexity, not only in information theory, but also in physics.

关键词： rigorous results in statistical mechanics exact results exact results source and channel coding

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Typical reconstruction limits for distributed compressed sensing based on l_2,1-norm minimization and Bayesian optimal reconstruction

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JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT 2015年第5期000卷 P05029-P05029页

作者： Shiraki, Yoshifumi Kabashima, Yoshiyuki NTT Corp NTT Commun Sci Lab Atsugi Kanagawa 2430198 Japan Tokyo Inst Technol Dept Computat Intelligence & Syst Sci Yokohama Kanagawa 2268502 Japan

The distributed compressed sensing framework provides an efficient compression scheme of multichannel signals that are sparse in some domains and highly correlated with one another. In particular, a signal model called the joint sparse model 2 (JSM-2) or multiple measurement vector problem, in which all sparse signals share their support, is important for dealing with practical problems such as magnetic resonance imaging and magnetoencephalography. In this paper, we investigate the typical reconstruction performance of JSM-2 problems for two schemes. One is l(2,1)-norm minimization reconstruction and the other is Bayesian optimal reconstruction. Employing the replica method, we show that the reconstruction performance of both schemes which exploit the knowledge of the sharing of the signal support overcomes that of their corresponding approaches for the single-channel compressed sensing problem. We also develop a computationally feasible approximate algorithm for performing the Bayes optimal scheme to validate our theoretical estimation. Our replica-based analysis numerically indicates that the spinodal point of the Bayesian reconstruction disappears, which implies that a fundamental reconstruction limit can be achieved by the BP-based approximate algorithm in a practical amount of time when the number of channels is sufficiently large. The results of the numerical experiments of both reconstruction schemes agree excellently with the theoretical evaluation.

关键词： message-passing algorithms source and channel coding communication supply and information networks

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Statistical mechanics approach to 1-bit compressed sensing

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JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT 2013年第02期2013卷 P02041-P02041页

作者： Xu, Yingying Kabashima, Yoshiyuki Tokyo Inst Technol Dept Computat Intelligence & Syst Sci Yokohama Kanagawa 2268502 Japan

Compressed sensing is a framework that makes it possible to recover an N-dimensional sparse vector x is an element of R-N from its linear transformation y is an element of R-M of lower dimensionality M < N. A scheme further reducing the data size of the compressed expression by using only the sign of each entry of y to recover x was recently proposed. This is often termed 1-bit compressed sensing. Here, we analyze the typical performance of an l(1)-norm-based signal recovery scheme for 1-bit compressed sensing using statistical mechanics methods. We show that the signal recovery performance predicted by the replica method under the replica symmetric ansatz, which turns out to be locally unstable for modes breaking the replica symmetry, is in good consistency with experimental results of an approximate recovery algorithm developed earlier. This suggests that the l(1)-based recovery problem typically has many local optima of a similar recovery accuracy, which can be achieved by the approximate algorithm. We also develop another approximate recovery algorithm inspired by the cavity method. Numerical experiments show that when the density of nonzero entries in the original signal is relatively large the new algorithm offers better performance than the abovementioned scheme and does so with a lower computational cost.

关键词： analysis of algorithms source and channel coding error correcting codes

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Passage-time coding with a timing kernel inferred from irregular cortical spike sequences

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JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT 2013年第03期2013卷 P03004-P03004页

作者： Tsubo, Yasuhiro Isomura, Yoshikazu Fukai, Tomoki RIKEN Brain Sci Inst Lab Neural Circuit Theory Wako Saitama 3510198 Japan Tamagawa Univ Brain Sci Inst Machida Tokyo 1948610 Japan JST CREST Kawaguchi Saitama 3320012 Japan

In vivo cortical neurons exhibit highly irregular spike sequences. However, the computational implications of this irregular firing with respect to neural codings are not yet fully understood. Recently, we formulated neuronal firing as a stochastic process to translate the firing rate determined by synaptic input into an irregular sequence of inter-spike intervals (ISIs). We previously determined that steady-state distributions of ISIs obey a power-law in the majority of neurons recorded from the sensorimotor cortex of a rat performing a forelimb-movement task. This observation led us to a hypothesis for a neural code with irregular spiking, which we termed as 'constrained maximization of firing-rate entropy' (CMFE). This hypothesis asserts that noisy neuronal activity maximizes steady-state firing-rate entropy under the joint constraints of energy consumption and uncertainty over output spike trains. CMFE previously assumed that the values of the rate parameters in two successive ISIs are random and uncorrelated with each other. However, this is an oversimplification and is unrealistic. In addition, the CMFE hypothesis seems to contradict our perception that the firing-rate distribution is dependent on external stimuli. Therefore, it is necessary to explore a rate-coding scheme that can resolve these issues. In this study, we review the concept of CMFE and extend it to incorporate the correlated nature of a firing rate sequence in a biological nervous system. We introduced passage-time coding of stimulus with the timing kernel inferred from irregular cortical spike sequences in our previous study. We showed how the timing kernel determines the amount of information in spike sequences.

关键词： stochastic processes (theory) source and channel coding neural code computational neuroscience

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