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Chao Tian - One of the best experts on this subject based on the ideXlab platform.
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Matched Multiuser Gaussian Source Channel Communications via Uncoded Schemes
IEEE Transactions on Information Theory, 2017Co-Authors: Chao Tian, Suhas N. Diggavi, Jun Chen, Shlomo Shamai ShitzAbstract:We investigate whether uncoded schemes are optimal for Gaussian Sources on multiuser Gaussian channels. Particularly, we consider two problems: the first is to send correlated Gaussian Sources on a Gaussian broadcast channel where each receiver is interested in reconstructing only one Source component (or one specific linear function of the Sources) under the mean squared error distortion measure; the second is to send correlated Gaussian Sources on a Gaussian multiple-access channel, where each transmitter observes a noisy combination of the Sources, and the receiver wishes to reconstruct the individual Source components (or individual linear functions) under the mean squared error distortion measure. It is shown that when the channel parameters satisfy certain general conditions, the induced distortion tuples are on the boundary of the achievable distortion region, and thus optimal. Instead of following the conventional approach of attempting to characterize the achievable distortion region, we ask the question whether and how a match can be effectively determined. This decision problem formulation helps to circumvent the difficult optimization problem often embedded in region characterization problems, and it also leads us to focus on the critical conditions in the outer bounds that make the inequalities become equalities, which effectively decouple the overall problem into several simpler sub-problems. Optimality results previously unknown in the literature are obtained using this novel approach. Explicit and novel outer bounds are derived for the two problems as the byproducts of our investigation.
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matched multiuser Gaussian Source channel communications via uncoded schemes
International Symposium on Information Theory, 2015Co-Authors: Chao Tian, Jun Chen, Suhas Diggavi, Shlomo ShamaiAbstract:We investigate whether uncoded schemes are optimal for Gaussian Sources on multiuser Gaussian channels. Particularly, we consider two problems: the first is to send correlated Gaussian Sources on a Gaussian broadcast channel where each receiver is interested in reconstructing only one Source component (or one specific linear function of the Sources) under the mean squared error distortion measure; the second is to send correlated Gaussian Sources on a Gaussian multiple-access channel, where each transmitter observes a noisy combination of the Source, and the receiver wishes to reconstruct the individual Source components (or individual linear functions) under the mean squared error distortion measure. It is shown that when the channel parameters match certain general conditions, the induced distortion tuples are on the boundary of the achievable distortion region, and thus optimal. Instead of following the conventional approach of attempting to characterize the achievable distortion region, we ask the question whether and how a match can be effectively determined. This decision problem formulation helps to circumvent the difficult optimization problem often embedded in region characterization problems, and it also leads us to focus on the critical conditions in the outer bounds that make the inequalities become equalities, which effectively decouples the overall problem into several simpler sub-problems.
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the achievable distortion region of sending a bivariate Gaussian Source on the Gaussian broadcast channel
IEEE Transactions on Information Theory, 2011Co-Authors: Chao Tian, Suhas Diggavi, Shlomo ShamaiAbstract:We provide a complete characterization of the achievable distortion region for the problem of sending a bivariate Gaussian Source over bandwidth-matched Gaussian broadcast channels, where each receiver is interested in only one component of the Source. This setting naturally generalizes the simple single Gaussian Source bandwidth-matched broadcast problem for which the uncoded scheme is known to be optimal. We show that a hybrid scheme can achieve the optimum for the bivariate case, but neither an uncoded scheme alone nor a separation-based scheme alone is sufficient. We further show that in this joint Source channel coding setting, the Gaussian scenario is the worst scenario among the Sources and channel noises with the same covariances.
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the achievable distortion region of bivariate Gaussian Source on Gaussian broadcast channel
International Symposium on Information Theory, 2010Co-Authors: Chao Tian, Suhas Diggavi, Shlomo ShamaiAbstract:We provide a complete characterization of the achievable distortion region for the problem of sending a bivariate Gaussian Source over a bandwidth-matched Gaussian broadcast channel, where each receiver is interested in only one component of the Source. This setting naturally generalizes the simple single Gaussian Source bandwidth-matched broadcast problem for which the uncoded scheme is known to be optimal. We show that a hybrid scheme can achieve the optimum for the bivariate case, but neither an uncoded scheme alone nor a separation-based scheme alone is sufficient.
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the achievable distortion region of bivariate Gaussian Source on Gaussian broadcast channel
arXiv: Information Theory, 2010Co-Authors: Chao Tian, Suhas Diggavi, Shlomo ShamaiAbstract:We provide a complete characterization of the achievable distortion region for the problem of sending a bivariate Gaussian Source over bandwidth-matched Gaussian broadcast channels, where each receiver is interested in only one component of the Source. This setting naturally generalizes the simple single Gaussian Source bandwidth-matched broadcast problem for which the uncoded scheme is known to be optimal. We show that a hybrid scheme can achieve the optimum for the bivariate case, but neither an uncoded scheme alone nor a separation-based scheme alone is sufficient. We further show that in this joint Source channel coding setting, the Gaussian setting is the worst scenario among the Sources and channel noises with the same covariances.
Shlomo Shamai - One of the best experts on this subject based on the ideXlab platform.
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matched multiuser Gaussian Source channel communications via uncoded schemes
International Symposium on Information Theory, 2015Co-Authors: Chao Tian, Jun Chen, Suhas Diggavi, Shlomo ShamaiAbstract:We investigate whether uncoded schemes are optimal for Gaussian Sources on multiuser Gaussian channels. Particularly, we consider two problems: the first is to send correlated Gaussian Sources on a Gaussian broadcast channel where each receiver is interested in reconstructing only one Source component (or one specific linear function of the Sources) under the mean squared error distortion measure; the second is to send correlated Gaussian Sources on a Gaussian multiple-access channel, where each transmitter observes a noisy combination of the Source, and the receiver wishes to reconstruct the individual Source components (or individual linear functions) under the mean squared error distortion measure. It is shown that when the channel parameters match certain general conditions, the induced distortion tuples are on the boundary of the achievable distortion region, and thus optimal. Instead of following the conventional approach of attempting to characterize the achievable distortion region, we ask the question whether and how a match can be effectively determined. This decision problem formulation helps to circumvent the difficult optimization problem often embedded in region characterization problems, and it also leads us to focus on the critical conditions in the outer bounds that make the inequalities become equalities, which effectively decouples the overall problem into several simpler sub-problems.
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the achievable distortion region of sending a bivariate Gaussian Source on the Gaussian broadcast channel
IEEE Transactions on Information Theory, 2011Co-Authors: Chao Tian, Suhas Diggavi, Shlomo ShamaiAbstract:We provide a complete characterization of the achievable distortion region for the problem of sending a bivariate Gaussian Source over bandwidth-matched Gaussian broadcast channels, where each receiver is interested in only one component of the Source. This setting naturally generalizes the simple single Gaussian Source bandwidth-matched broadcast problem for which the uncoded scheme is known to be optimal. We show that a hybrid scheme can achieve the optimum for the bivariate case, but neither an uncoded scheme alone nor a separation-based scheme alone is sufficient. We further show that in this joint Source channel coding setting, the Gaussian scenario is the worst scenario among the Sources and channel noises with the same covariances.
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the achievable distortion region of bivariate Gaussian Source on Gaussian broadcast channel
International Symposium on Information Theory, 2010Co-Authors: Chao Tian, Suhas Diggavi, Shlomo ShamaiAbstract:We provide a complete characterization of the achievable distortion region for the problem of sending a bivariate Gaussian Source over a bandwidth-matched Gaussian broadcast channel, where each receiver is interested in only one component of the Source. This setting naturally generalizes the simple single Gaussian Source bandwidth-matched broadcast problem for which the uncoded scheme is known to be optimal. We show that a hybrid scheme can achieve the optimum for the bivariate case, but neither an uncoded scheme alone nor a separation-based scheme alone is sufficient.
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the achievable distortion region of bivariate Gaussian Source on Gaussian broadcast channel
arXiv: Information Theory, 2010Co-Authors: Chao Tian, Suhas Diggavi, Shlomo ShamaiAbstract:We provide a complete characterization of the achievable distortion region for the problem of sending a bivariate Gaussian Source over bandwidth-matched Gaussian broadcast channels, where each receiver is interested in only one component of the Source. This setting naturally generalizes the simple single Gaussian Source bandwidth-matched broadcast problem for which the uncoded scheme is known to be optimal. We show that a hybrid scheme can achieve the optimum for the bivariate case, but neither an uncoded scheme alone nor a separation-based scheme alone is sufficient. We further show that in this joint Source channel coding setting, the Gaussian setting is the worst scenario among the Sources and channel noises with the same covariances.
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approximate characterizations for the Gaussian Source broadcast distortion region
arXiv: Information Theory, 2009Co-Authors: Chao Tian, Suhas Diggavi, Shlomo ShamaiAbstract:We consider the joint Source-channel coding problem of sending a Gaussian Source on a K-user Gaussian broadcast channel with bandwidth mismatch. A new outer bound to the achievable distortion region is derived using the technique of introducing more than one additional auxiliary random variable, which was previously used to derive sum-rate lower bound for the symmetric Gaussian multiple description problem. By combining this outer bound with the achievability result based on Source-channel separation, we provide approximate characterizations of the achievable distortion region within constant multiplicative factors. Furthermore, we show that the results can be extended to general broadcast channels, and the performance of the Source-channel separation based approach is also within the same constant multiplicative factors of the optimum.
Ertem Tuncel - One of the best experts on this subject based on the ideXlab platform.
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On the energy-distortion tradeoff for the Gaussian broadcast problem
2016 IEEE International Symposium on Information Theory (ISIT), 2016Co-Authors: Erman Koken, Ertem TuncelAbstract:The energy-distortion tradeoff for the transmission of a white Gaussian Source over the additive white Gaussian broadcast channel is investigated by translating the known upper and lower bounds into the infinite bandwidth regime. While a gap continues to exist between the bounds in this regime, it is shown that in a certain region on the distortion plane, the energy difference between the best known upper and lower bounds is quantifiably small.
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joint Source channel coding for broadcasting correlated Sources
International Symposium on Information Theory, 2016Co-Authors: Erman Koken, Ertem TuncelAbstract:We consider the lossy transmission of a memoryless bivariate Gaussian Source over an average-power-constrained bandwidth-mismatched Gaussian broadcast channel with two receivers where each receiver is interested in only one component. We propose new hybrid digital/analog coding schemes which are demonstrated to outperform the previously known schemes.
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on the distortion energy tradeoff for zero delay transmission of a Gaussian Source over the awgn channel
Information Theory Workshop, 2015Co-Authors: Erman Koken, Ertem Tuncel, Deniz GunduzAbstract:An achievable scheme for zero-delay transmission of an i.i.d. Gaussian Source over an additive white Gaussian channel with no bandwidth limitation is introduced, and its energy-distortion performance is analyzed. By the nature of the problem, one must transmit each Source sample separately but can use the channel infinitely many times. We introduce an outage concept, and analyze the expected distortion conditioned on no outage. We show that the proposed scheme can approach to the asymptotical decay for large enough energy for arbitrary outage probability. The proposed scheme builds on separation of Source and channel coding, whereby the Source is quantized with a high-resolution optimal quantizer. In the high energy-to-noise ratio (ENR) regime, the minimum energy required to obtain a given distortion level in the proposed scheme can approach arbitrarily close the Shannon bound, which can only be achieved using infinite delay.
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on the asymptotic distortion energy tradeoff for zero delay transmission of a Gaussian Source over the awgn channel
International Symposium on Information Theory, 2015Co-Authors: Erman Koken, Ertem Tuncel, Deniz GunduzAbstract:An achievable scheme for zero-delay transmission of an i.i.d. Gaussian Source over an additive white Gaussian noise channel with no bandwidth limitation is introduced, and its energy-distortion performance is analyzed. By the nature of the problem, one must transmit each Source sample separately but can use the channel infinitely many times. The proposed scheme builds on separation of Source and channel coding, whereby the Source is quantized into “equiprobable” cells so that the output can be seen as a message suitable for channel coding. Moreover, as the number of quantization cells go to infinity, the channel capacity can be approached with arbitrarily small error. In the high energy-to-noise ratio regime, the minimum energy required to obtain a given distortion level in the proposed scheme can come as close as 3dB to the Shannon bound, which can only be achieved using infinite delay.
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new hybrid digital analog schemes for transmission of a Gaussian Source over a Gaussian channel
IEEE Transactions on Information Theory, 2010Co-Authors: Yang Gao, Ertem TuncelAbstract:Two new schemes are proposed for transmitting a Gaussian Source over a Gaussian channel. These schemes directly generalize previous results of Bross and Puri A scaled version of either the Source itself or the quantization error is superimposed on the digital information, and thus serves as effective channel state information (CSI) unknown to the receiver. It is shown that for any power allocation between the coded and uncoded components of transmission, optimal distortion can be achieved by a continuum of auxiliary random variables (rather than only Costa's) if the decoded auxiliary codeword is properly used. This observation provides a new degree of freedom in point-to-point transmission. This freedom, in turn, can be utilized in multiterminal scenarios, as is demonstrated with an example.
Suhas Diggavi - One of the best experts on this subject based on the ideXlab platform.
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matched multiuser Gaussian Source channel communications via uncoded schemes
International Symposium on Information Theory, 2015Co-Authors: Chao Tian, Jun Chen, Suhas Diggavi, Shlomo ShamaiAbstract:We investigate whether uncoded schemes are optimal for Gaussian Sources on multiuser Gaussian channels. Particularly, we consider two problems: the first is to send correlated Gaussian Sources on a Gaussian broadcast channel where each receiver is interested in reconstructing only one Source component (or one specific linear function of the Sources) under the mean squared error distortion measure; the second is to send correlated Gaussian Sources on a Gaussian multiple-access channel, where each transmitter observes a noisy combination of the Source, and the receiver wishes to reconstruct the individual Source components (or individual linear functions) under the mean squared error distortion measure. It is shown that when the channel parameters match certain general conditions, the induced distortion tuples are on the boundary of the achievable distortion region, and thus optimal. Instead of following the conventional approach of attempting to characterize the achievable distortion region, we ask the question whether and how a match can be effectively determined. This decision problem formulation helps to circumvent the difficult optimization problem often embedded in region characterization problems, and it also leads us to focus on the critical conditions in the outer bounds that make the inequalities become equalities, which effectively decouples the overall problem into several simpler sub-problems.
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the achievable distortion region of sending a bivariate Gaussian Source on the Gaussian broadcast channel
IEEE Transactions on Information Theory, 2011Co-Authors: Chao Tian, Suhas Diggavi, Shlomo ShamaiAbstract:We provide a complete characterization of the achievable distortion region for the problem of sending a bivariate Gaussian Source over bandwidth-matched Gaussian broadcast channels, where each receiver is interested in only one component of the Source. This setting naturally generalizes the simple single Gaussian Source bandwidth-matched broadcast problem for which the uncoded scheme is known to be optimal. We show that a hybrid scheme can achieve the optimum for the bivariate case, but neither an uncoded scheme alone nor a separation-based scheme alone is sufficient. We further show that in this joint Source channel coding setting, the Gaussian scenario is the worst scenario among the Sources and channel noises with the same covariances.
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the achievable distortion region of bivariate Gaussian Source on Gaussian broadcast channel
International Symposium on Information Theory, 2010Co-Authors: Chao Tian, Suhas Diggavi, Shlomo ShamaiAbstract:We provide a complete characterization of the achievable distortion region for the problem of sending a bivariate Gaussian Source over a bandwidth-matched Gaussian broadcast channel, where each receiver is interested in only one component of the Source. This setting naturally generalizes the simple single Gaussian Source bandwidth-matched broadcast problem for which the uncoded scheme is known to be optimal. We show that a hybrid scheme can achieve the optimum for the bivariate case, but neither an uncoded scheme alone nor a separation-based scheme alone is sufficient.
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the achievable distortion region of bivariate Gaussian Source on Gaussian broadcast channel
arXiv: Information Theory, 2010Co-Authors: Chao Tian, Suhas Diggavi, Shlomo ShamaiAbstract:We provide a complete characterization of the achievable distortion region for the problem of sending a bivariate Gaussian Source over bandwidth-matched Gaussian broadcast channels, where each receiver is interested in only one component of the Source. This setting naturally generalizes the simple single Gaussian Source bandwidth-matched broadcast problem for which the uncoded scheme is known to be optimal. We show that a hybrid scheme can achieve the optimum for the bivariate case, but neither an uncoded scheme alone nor a separation-based scheme alone is sufficient. We further show that in this joint Source channel coding setting, the Gaussian setting is the worst scenario among the Sources and channel noises with the same covariances.
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approximate characterizations for the Gaussian Source broadcast distortion region
arXiv: Information Theory, 2009Co-Authors: Chao Tian, Suhas Diggavi, Shlomo ShamaiAbstract:We consider the joint Source-channel coding problem of sending a Gaussian Source on a K-user Gaussian broadcast channel with bandwidth mismatch. A new outer bound to the achievable distortion region is derived using the technique of introducing more than one additional auxiliary random variable, which was previously used to derive sum-rate lower bound for the symmetric Gaussian multiple description problem. By combining this outer bound with the achievability result based on Source-channel separation, we provide approximate characterizations of the achievable distortion region within constant multiplicative factors. Furthermore, we show that the results can be extended to general broadcast channels, and the performance of the Source-channel separation based approach is also within the same constant multiplicative factors of the optimum.
Sarah Sadavoy - One of the best experts on this subject based on the ideXlab platform.
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the jcmt gould belt survey scuba 2 data reduction methods and Gaussian Source recovery analysis
Astrophysical Journal Supplement Series, 2018Co-Authors: Helen Kirk, J Hatchell, Doug Johnstone, David Berry, Tim Jenness, J Buckle, Steve Mairs, Erik Rosolowsky, James Di Francesco, Sarah SadavoyAbstract:The James Clerk Maxwell Telescope (JCMT) Gould Belt Survey (GBS) was one of the first legacy surveys with the JCMT in Hawaii, mapping 47 deg2 of nearby (<500 pc) molecular clouds in dust continuum emission at 850 and 450 μm, as well as a more limited area in lines of various CO isotopologues. While molecular clouds and the material that forms stars have structures on many size scales, their larger-scale structures are difficult to observe reliably in the submillimeter regime using ground-based facilities. In this paper, we quantify the extent to which three subsequent data reduction methods employed by the JCMT GBS accurately recover emission structures of various size scales, in particular, dense cores, which are the focus of many GBS science goals. With our current best data reduction procedure, we expect to recover 100% of structures with Gaussian σ sizes of ≤30'' and intensity peaks of at least five times the local noise for isolated peaks of emission. The measured sizes and peak fluxes of these compact structures are reliable (within 15% of the input values), but Source recovery and reliability both decrease significantly for larger emission structures and fainter peaks. Additional factors such as Source crowding have not been tested in our analysis. The most recent JCMT GBS data release includes pointing corrections, and we demonstrate that these tend to decrease the sizes and increase the peak intensities of compact Sources in our data set, mostly at a low level (several percent), but occasionally with notable improvement.
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the jcmt gould belt survey scuba 2 data reduction methods and Gaussian Source recovery analysis
arXiv: Astrophysics of Galaxies, 2018Co-Authors: Helen Kirk, J Hatchell, Doug Johnstone, David Berry, Tim Jenness, J Buckle, Steve Mairs, Erik Rosolowsky, James Di Francesco, Sarah SadavoyAbstract:The JCMT Gould Belt Survey was one of the first Legacy Surveys with the James Clerk Maxwell Telescope in Hawaii, mapping 47 square degrees of nearby (< 500 pc) molecular clouds in both dust continuum emission at 850 $\mu$m and 450 $\mu$m, as well as a more-limited area in lines of various CO isotopologues. While molecular clouds and the material that forms stars have structures on many size scales, their larger-scale structures are difficult to observe reliably in the submillimetre regime using ground-based facilities. In this paper, we quantify the extent to which three subsequent data-reduction methods employed by the JCMT GBS accurately recover emission structures of various size scales, in particular, dense cores which are the focus of many GBS science goals. With our current best data-reduction procedure, we expect to recover 100% of structures with Gaussian sigma sizes of $\le$30" and intensity peaks of at least five times the local noise for isolated peaks of emission. The measured sizes and peak fluxes of these compact structures are reliable (within 15% of the input values), but Source recovery and reliability both decrease significantly for larger emission structures and for fainter peaks. Additional factors such as Source crowding have not been tested in our analysis. The most recent JCMT GBS data release includes pointing corrections, and we demonstrate that these tend to decrease the sizes and increase the peak intensities of compact Sources in our dataset, mostly at a low level (several percent), but occasionally with notable improvement.