Lossy Joint Source-Channel Coding in the Finite Blocklength Regime

Kostina, Victoria; Verdú, S.

doi:10.1109/tit.2013.2238657

Cited by 142 publications

(109 citation statements)

References 21 publications

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“…This is different from the recent works on finite blocklength (or dispersion) analysis on (point-to-point) lossy joint sourcechannel coding [16], [17] where the second-order dispersion term is in fact a sum of two standard deviations-that of the Dtilted information of the source [14], [17] and the information density of the channel. Intuitively, this results from the fact that the source is independent of the channel noise and hence the variance of the sum is equal to the sum of the variances.…”

Section: A (N )-Transmissibility For An Auxiliary Systemcontrasting

confidence: 60%

“…In the latter, the authors introduced new channel coding rate bounds and used these bounds to strengthen the results in Strassen's seminal work [13]. In addition, finite blocklength analysis has also been applied to lossy source coding [14], [15] and point-to-point JSCC [16], [17] just to name a few. The general version of the point-topoint-JSCC problem was studied by Han [18,Chapter 5] and extended by Campo et al [19].…”

Section: B Related Workmentioning

confidence: 99%

“…There are at least two directions for further research: Firstly, we would like to understand whether a second-order coding result analogous to [16], [17] can be derived using different coding schemes. Secondly, we would like to derive a converse result for the problem perhaps based on the result in [8].…”

Section: Conclusion and Further Workmentioning

confidence: 99%

See 2 more Smart Citations

Transmission of correlated sources over a MAC: A Gaussian approximation-based analysis

Tan

2012

2012 50th Annual Allerton Conference on Communication, Control, and Computing (Allerton)

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The problem of separately encoding and subsequently transmitting correlated sources over a discrete memoryless multiple-access channel is revisited. In particular, we examine the sufficient conditions on the source and the channel under which there exists a n-length block code satisfying the condition that the error probability of reconstructing the discrete memoryless multiple source is no larger than some fixed constant > 0, or in short, -lossless transmission. We modify the decoding rule of Cover-El Gamal-Salehi and analyze the error probability using Gaussian approximations to derive a secondorder generalization their sufficient condition for the -lossless transmission of the correlated sources.

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Section: A (N )-Transmissibility For An Auxiliary Systemcontrasting

confidence: 60%

Section: B Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Transmission of correlated sources over a MAC: A Gaussian approximation-based analysis

Tan

2012

2012 50th Annual Allerton Conference on Communication, Control, and Computing (Allerton)

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“…It is shown in [4], [5] that the relationship between k, n, and ✏ for optimal JSCC admits the following asymptotic expansion…”

Section: A Second-order Rate For Source-channel Codesmentioning

confidence: 99%

“…The separation asymptotic expansion (2), which can be viewed as a direct corollary of [7]- [10], is also stated in [4], [5]. Second-order coding rate results for the problem of UMP were derived in [5] as a step towards the JSCC dispersion.…”

Section: B Prior Workmentioning

confidence: 99%

Second-order coding rate for m-class source-channel codes

Shkel

Tan

Draper

2015

2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)

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The second-order coding rate for source-channel codes with m levels of unequal message protection (UMP) is derived. The second-order coding rate takes the form of an optimization problem which reduces to separate source-channel coding rate for m = 2. A procedure for solving the given optimization problem is proposed. The proposed procedure exploits the structure of the problem to reduce the optimization search space to one dimension. Numerical results for the BSC are obtained and it is shown, empirically, that the second-order coding rate of source-channel codes with m levels of UMP approaches the optimal joint source-channel coding rate as m grows.

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Analog Coding in Emerging Memory Systems

Zarcone

Engel

Eryilmaz

et al. 2020

Sci Rep

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Exponential growth in data generation and large-scale data science has created an unprecedented need for inexpensive, low-power, low-latency, high-density information storage. This need has motivated significant research into multi-level memory devices that are capable of storing multiple bits of information per device. The memory state of these devices is intrinsically analog. Furthermore, much of the data they will store, along with the subsequent operations on the majority of this data, are all intrinsically analog-valued. Ironically though, in the current storage paradigm, both the devices and data are quantized for use with digital systems and digital error-correcting codes. Here, we recast the storage problem as a communication problem. This then allows us to use ideas from analog coding and show, using phase change memory as a prototypical multi-level storage technology, that analog-valued emerging memory devices can achieve higher capacities when paired with analog codes. Further, we show that storing analog signals directly through joint coding can achieve low distortion with reduced coding complexity. Specifically, by jointly optimizing for signal statistics, device statistics, and a distortion metric, we demonstrate that single-symbol analog codings can perform comparably to digital codings with asymptotically large code lengths. These results show that end-to-end analog memory systems have the potential to not only reach higher storage capacities than discrete systems but also to significantly lower coding complexity, leading to faster and more energy efficient data storage. A paradigm shift in the type and quantity of storable information is currently underway. Internet-connected devices are projected to reach 50 billion, more than 6 devices per person, by the year 2020 1. Much of the data produced by these devices, such as pixel intensities from cameras, sound recordings from microphones, and time-series from sensors, comes from signals that are intrinsically analog-valued or many-valued (>100 values) and ordinal. These signals are also highly redundant and compressible, with a large degree of their joint activity explained by a smaller number of factors than the intrinsic dimensionality of the signal. Furthermore, an increasing portion of the operations performed on the data are analog, with much of it being used for statistical inference or human perception (e.g. object-detection for images). A concurrent paradigm shift is underway in the media we use to store data. Early storage media such as phonograph records and VCR tapes relied on perturbing an analog-valued state (wax height and magnetic polarization, respectively). Digital computation led to the popularity of binary storage representations that inhibit noise propagation and utilize the concurrently developed theories of binary error-correcting codes 2. However, many emerging memory technologies have shifted back to analog-valued media to create multi-level devices that fill the need for inexpensive, high-density storage. MLC-Flash, Phase Ch...

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Lossy Joint Source-Channel Coding in the Finite Blocklength Regime

Cited by 142 publications

References 21 publications

Transmission of correlated sources over a MAC: A Gaussian approximation-based analysis

Transmission of correlated sources over a MAC: A Gaussian approximation-based analysis

Second-order coding rate for m-class source-channel codes

Analog Coding in Emerging Memory Systems

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