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\n \n\n \n \n J. Hachem; U. Niesen; and S. Diggavi.\n\n\n \n \n \n \n Caching for Interference Networks: A Separation Architecture.\n \n \n \n\n\n \n\n\n\n Edge Caching for Mobile Networks. 2020.\n \n\n\n\n
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@article{hachem2020caching,\n author = {Hachem, J. and Niesen, U. and Diggavi, S.},\n editor = {Poor, Vince and Chen, Wei},\n journal = {Edge Caching for Mobile Networks},\n publisher = {Institute of Engineering and Technology (IET) Press},\n tags = {BookChap,CCWN,IT,ANIT,WiNetnew,SCS},\n title = {Caching for Interference Networks: A Separation Architecture},\n type = {3},\n year = {2020}\n}\n\n
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\n \n\n \n \n J. Hachem; U. Niesen; and S. Diggavi.\n\n\n \n \n \n \n \n Energy-Efficiency Gains of Caching for Interference Channels.\n \n \n \n \n\n\n \n\n\n\n IEEE Communications Letters, 22(7): 1434-1437. July 2018.\n \n\n\n\n
\n\n\n\n \n \n \"Energy-Efficiency arxiv\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@article{8335768,\n abstract = {This letter initiates the study of energy-efficiency gains provided by caching. We focus on the cache-aided Gaussian interference channel in the low-SNR regime. We propose a strategy that creates content overlaps at the transmitter caches to allow for co-operation between the transmitters. This co-operation yields a beamforming gain, which has to be traded off against a multicasting gain. We evaluate the performance of this strategy and show its approximate optimality in both the single-receiver case and the single-transmitter case.},\n author = {J. {Hachem} and U. {Niesen} and S. {Diggavi}},\n doi = {10.1109/LCOMM.2018.2822694},\n issn = {1558-2558},\n journal = {IEEE Communications Letters},\n keywords = {array signal processing;cache storage;channel capacity;energy conservation;Gaussian channels;multicast communication;radio networks;radiofrequency interference;telecommunication power management;wireless channels;energy-efficiency gains;cache-aided Gaussian interference channel;low-SNR regime;transmitter caches;co-operation yields;beamforming gain;multicasting gain;Transmitters;Receivers;Multicast communication;Array signal processing;Libraries;Interference channels;Network coding;wireless networks;content distribution networks},\n month = {July},\n number = {7},\n pages = {1434-1437},\n tags = {journal,CCWN,IT,ANIT,WiNetnew,SCS},\n title = {Energy-Efficiency Gains of Caching for Interference Channels},\n type = {2},\n url_arxiv = {https://arxiv.org/abs/1808.00653},\n volume = {22},\n year = {2018}\n}\n\n
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\n This letter initiates the study of energy-efficiency gains provided by caching. We focus on the cache-aided Gaussian interference channel in the low-SNR regime. We propose a strategy that creates content overlaps at the transmitter caches to allow for co-operation between the transmitters. This co-operation yields a beamforming gain, which has to be traded off against a multicasting gain. We evaluate the performance of this strategy and show its approximate optimality in both the single-receiver case and the single-transmitter case.\n
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\n \n\n \n \n Jad Hachem; Urs Niesen; and Suhas N Diggavi.\n\n\n \n \n \n \n \n Degrees of freedom of cache-aided wireless interference networks.\n \n \n \n \n\n\n \n\n\n\n IEEE Transactions on Information Theory, 64(7): 5359–5380. 2018.\n \n\n\n\n
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@article{hachem2018degrees,\n abstract = {We study the role of caches in wireless interference networks. We focus on content caching and delivery across a Gaussian interference network, where both transmitters and receivers are equipped with caches. We provide a constant-factor approximation of the system's degrees of freedom (DoF), for arbitrary number of transmitters, number of receivers, content library size, receiver cache size, and transmitter cache size (as long as the transmitters combined can store the entire content library among them). We demonstrate approximate optimality with respect to information-theoretic bounds that do not impose any restrictions on the caching and delivery strategies. Our characterization reveals three key insights. First, the approximate DoF is achieved using a strategy that separates the physical and network layers. This separation architecture is thus approximately optimal. Second, we show that increasing transmitter cache memory beyond what is needed to exactly store the entire library between all transmitters does not provide more than a constant-factor benefit to the DoF. A consequence is that transmit zero-forcing is not needed for approximate optimality. Third, we derive an interesting tradeoff between the receiver memory and the number of transmitters needed for approximately maximal performance. In particular, if each receiver can store a constant fraction of the content library, then only a constant number of transmitters are needed. Our solution to the caching problem requires formulating and solving a new communication problem, the symmetric multiple multicast X-channel, for which we provide an exact DoF characterization.},\n author = {Hachem, Jad and Niesen, Urs and Diggavi, Suhas N},\n journal = {IEEE Transactions on Information Theory},\n number = {7},\n pages = {5359--5380},\n publisher = {IEEE},\n tags = {journal,CCWN,IT,WiNetnew,SCS,ANIT},\n title = {Degrees of freedom of cache-aided wireless interference networks},\n type = {2},\n url_arxiv = {https://arxiv.org/abs/1606.03175},\n doi = {10.1109/TIT.2018.2825321},\n volume = {64},\n year = {2018}\n}\n\n
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\n We study the role of caches in wireless interference networks. We focus on content caching and delivery across a Gaussian interference network, where both transmitters and receivers are equipped with caches. We provide a constant-factor approximation of the system's degrees of freedom (DoF), for arbitrary number of transmitters, number of receivers, content library size, receiver cache size, and transmitter cache size (as long as the transmitters combined can store the entire content library among them). We demonstrate approximate optimality with respect to information-theoretic bounds that do not impose any restrictions on the caching and delivery strategies. Our characterization reveals three key insights. First, the approximate DoF is achieved using a strategy that separates the physical and network layers. This separation architecture is thus approximately optimal. Second, we show that increasing transmitter cache memory beyond what is needed to exactly store the entire library between all transmitters does not provide more than a constant-factor benefit to the DoF. A consequence is that transmit zero-forcing is not needed for approximate optimality. Third, we derive an interesting tradeoff between the receiver memory and the number of transmitters needed for approximately maximal performance. In particular, if each receiver can store a constant fraction of the content library, then only a constant number of transmitters are needed. Our solution to the caching problem requires formulating and solving a new communication problem, the symmetric multiple multicast X-channel, for which we provide an exact DoF characterization.\n
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\n \n\n \n \n C. Tian; J. Chen; S. N. Diggavi; and S. Shamai Shitz.\n\n\n \n \n \n \n Matched Multiuser Gaussian Source Channel Communications via Uncoded Schemes.\n \n \n \n\n\n \n\n\n\n IEEE Transactions on Information Theory, 63(7): 4155-4171. July 2017.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@article{7920290,\n abstract = {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.},\n author = {C. {Tian} and J. {Chen} and S. N. {Diggavi} and S. {Shamai Shitz}},\n doi = {10.1109/TIT.2017.2701807},\n issn = {1557-9654},\n journal = {IEEE Transactions on Information Theory},\n keywords = {broadcast channels;Gaussian channels;mean square error methods;multiuser channels;matched multiuser Gaussian source channel communications;uncoded schemes;Gaussian broadcast channel;mean squared error distortion measure;correlated Gaussian sources;Gaussian multiple-access channel;mean squared error distortion;distortion tuples;optimization problem;region characterization problems;Distortion;Distortion measurement;Optimization;Receivers;Noise measurement;Decoding;Encoding;Broadcast;multiple access;combined source-channel coding},\n month = {July},\n number = {7},\n pages = {4155-4171},\n tags = {journal,IT,SCS},\n title = {Matched Multiuser Gaussian Source Channel Communications via Uncoded Schemes},\n type = {2},\n volume = {63},\n year = {2017}\n}\n\n
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\n 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.\n
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\n \n\n \n \n Chao Tian; Jun Chen; S.N. Diggavi; and S. Shamai.\n\n\n \n \n \n \n \n Optimality and Approximate Optimality of Source-Channel Separation in Networks.\n \n \n \n \n\n\n \n\n\n\n Information Theory, IEEE Transactions on, 60(2): 904-918. Feb 2014.\n \n\n\n\n
\n\n\n\n \n \n \"Optimality arxiv\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{6671968,\n abstract = {We consider the source-channel separation architecture for lossy source coding in communication networks. It is shown that the separation approach is optimal in two general scenarios and is approximately optimal in a third scenario. The two scenarios for which separation is optimal complement each other: the first is when the memoryless sources at source nodes are arbitrarily correlated, each of which is to be reconstructed at possibly multiple destinations within certain distortions, but the channels in this network are synchronized, orthogonal, and memoryless point-to-point channels; the second is when the memoryless sources are mutually independent, each of which is to be reconstructed only at one destination within a certain distortion, but the channels are general, including multi-user channels, such as multiple access, broadcast, interference, and relay channels, possibly with feedback. The third scenario, for which we demonstrate approximate optimality of source-channel separation, generalizes the second scenario by allowing each source to be reconstructed at multiple destinations with different distortions. For this case, the loss from optimality using the separation approach can be upper-bounded when a difference distortion measure is taken, and in the special case of quadratic distortion measure, this leads to universal constant bounds.},\n author = {Chao Tian and Jun Chen and Diggavi, S.N. and Shamai, S.},\n doi = {10.1109/TIT.2013.2291787},\n issn = {0018-9448},\n journal = {Information Theory, IEEE Transactions on},\n month = {Feb},\n number = {2},\n pages = {904-918},\n tags = {journal,SrcChan,IT},\n title = {Optimality and Approximate Optimality of Source-Channel Separation in Networks},\n type = {2},\n url_arxiv = {http://arxiv.org/abs/1004.2648},\n volume = {60},\n year = {2014}\n}\n\n
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\n We consider the source-channel separation architecture for lossy source coding in communication networks. It is shown that the separation approach is optimal in two general scenarios and is approximately optimal in a third scenario. The two scenarios for which separation is optimal complement each other: the first is when the memoryless sources at source nodes are arbitrarily correlated, each of which is to be reconstructed at possibly multiple destinations within certain distortions, but the channels in this network are synchronized, orthogonal, and memoryless point-to-point channels; the second is when the memoryless sources are mutually independent, each of which is to be reconstructed only at one destination within a certain distortion, but the channels are general, including multi-user channels, such as multiple access, broadcast, interference, and relay channels, possibly with feedback. The third scenario, for which we demonstrate approximate optimality of source-channel separation, generalizes the second scenario by allowing each source to be reconstructed at multiple destinations with different distortions. For this case, the loss from optimality using the separation approach can be upper-bounded when a difference distortion measure is taken, and in the special case of quadratic distortion measure, this leads to universal constant bounds.\n
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\n \n\n \n \n A Khisti; S.N. Diggavi; and Gregory W. Wornell.\n\n\n \n \n \n \n Secret-Key Generation Using Correlated Sources and Channels.\n \n \n \n\n\n \n\n\n\n Information Theory, IEEE Transactions on, 58(2): 652-670. Feb 2012.\n \n\n\n\n
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@article{kdw_j11,\n abstract = {We study the secret-key capacity in a joint source-channel coding setup-the terminals are connected over a discrete memoryless channel and have access to side information, modelled as a pair of discrete memoryless source sequences. As our main result, we establish the upper and lower bounds on the secret-key capacity. In the lower bound expression, the equivocation terms of the source and channel components are functionally additive even though the coding scheme generates a single secret-key by jointly taking into account the source and channel equivocations. Our bounds coincide, thus establishing the capacity, when the underlying wiretap channel can be decomposed into a set of independent, parallel, and reversely degraded channels. For the case of parallel Gaussian channels and jointly Gaussian sources we show that Gaussian codebooks achieve the secret-key capacity. In addition, when the eavesdropper also observes a correlated side information sequence, we establish the secret-key capacity when both the source and channel of the eavesdropper are a degraded version of the legitimate receiver. We finally also treat the case when a public discussion channel is available, propose a separation based coding scheme, and establish its optimality when the channel output symbols of the legitimate receiver and eavesdropper are conditionally independent given the input.},\n author = {Khisti, A and Diggavi, S.N. and Wornell, Gregory W.},\n doi = {10.1109/TIT.2011.2173629},\n file = {:papers:secret_keygen.pdf},\n issn = {0018-9448},\n journal = {Information Theory, IEEE Transactions on},\n label = {kdw_j11},\n month = {Feb},\n number = {2},\n pages = {652-670},\n tags = {journal,ITsecrecy,KeyGen,IT,WiNetSec,SrcChanSec},\n title = {Secret-Key Generation Using Correlated Sources and Channels},\n type = {2},\n volume = {58},\n year = {2012}\n}\n\n
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\n We study the secret-key capacity in a joint source-channel coding setup-the terminals are connected over a discrete memoryless channel and have access to side information, modelled as a pair of discrete memoryless source sequences. As our main result, we establish the upper and lower bounds on the secret-key capacity. In the lower bound expression, the equivocation terms of the source and channel components are functionally additive even though the coding scheme generates a single secret-key by jointly taking into account the source and channel equivocations. Our bounds coincide, thus establishing the capacity, when the underlying wiretap channel can be decomposed into a set of independent, parallel, and reversely degraded channels. For the case of parallel Gaussian channels and jointly Gaussian sources we show that Gaussian codebooks achieve the secret-key capacity. In addition, when the eavesdropper also observes a correlated side information sequence, we establish the secret-key capacity when both the source and channel of the eavesdropper are a degraded version of the legitimate receiver. We finally also treat the case when a public discussion channel is available, propose a separation based coding scheme, and establish its optimality when the channel output symbols of the legitimate receiver and eavesdropper are conditionally independent given the input.\n
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\n\n\n\n \n \n \"Approximate arxiv\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{TDSj10a,\n abstract = {We show that source-channel separation is approximately optimal for transmitting\na Gaussian source over a bandwidth mismatched Gaussian channel, for quadratic distortion\nmeasures. Furthermore, we show that the results can be extended to\ngeneral broadcast channels, and the performance of the source-channel\nseparation based approach is also within the same\nconstant multiplicative factors of the optimum.},\n author = {C. Tian and  S N. Diggavi and S. Shamai(Shitz)},\n file = {:papers:gaussianscbc_final.pdf},\n journal = {IEEE Transactions on Information Theory},\n label = {tds_j11a},\n month = {January},\n note = {},\n number = {1},\n pages = {124-136},\n tags = {journal,SrcChan,ApproxIT,NDC,IT},\n title = {Approximate Characterizations for the Gaussian Broadcasting Distortion Region},\n type = {2},\n url_arxiv = {http://arxiv.org/abs/0906.3183},\n volume = {57},\n year = {2011}\n}\n\n
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\n We show that source-channel separation is approximately optimal for transmitting a Gaussian source over a bandwidth mismatched Gaussian channel, for quadratic distortion measures. 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.\n
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@inproceedings{MTDp10,\n abstract = {Lossless transmission of a set of correlated sources\nover a deterministic relay network is considered for two traffic\nrequirements. In distributed multicast, the set of sources are\nto be delivered to a set of destinations. The source exchange\nrequires all the nodes with access to sources to be able to\nreconstruct all other sources observed at other nodes. We develop\nachievable regions and outer bounds for both these situations. For\nlinear deterministic networks, these bounds coincide, yielding a\ncharacterization.},\n author = {S. Mohajer and C. Tian and S.N. Diggavi},\n booktitle = {IEEE Information Theory Workshop (ITW) Cairo},\n file = {:papers:mtd_itw10_final.pdf},\n month = {January},\n note = {},\n pages = {},\n tags = {conf,DetApprox,ITapprox,WiNet,IT,WiNetInfFlow,SrcChan,SrcChanSep,NDC,InfExch,SelConf},\n title = {On source transmission over deterministic relay networks},\n type = {4},\n year = {2010}\n}\n\n
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\n Lossless transmission of a set of correlated sources over a deterministic relay network is considered for two traffic requirements. In distributed multicast, the set of sources are to be delivered to a set of destinations. The source exchange requires all the nodes with access to sources to be able to reconstruct all other sources observed at other nodes. We develop achievable regions and outer bounds for both these situations. For linear deterministic networks, these bounds coincide, yielding a characterization.\n
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\n \n\n \n \n C. Tian; J. Chen; S N. Diggavi; and S. Shamai.\n\n\n \n \n \n \n Optimality and approximate optimality of source-channel separation in networks.\n \n \n \n\n\n \n\n\n\n In Proc. of IEEE ISIT 2010, Austin, Texas, pages 495–499, June 2010. \n \n\n\n\n
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@inproceedings{TCDSc10a,\n author = {C. Tian and  J. Chen and S N. Diggavi and S. Shamai},\n booktitle = {Proc. of IEEE ISIT 2010, Austin, Texas},\n month = {June},\n note = {},\n pages = {495--499},\n tags = {conf,SrcChan,ITapprox,NDC,IT},\n title = {Optimality and approximate optimality of source-channel \nseparation in networks},\n type = {4},\n year = {2010}\n}\n\n
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\n \n\n \n \n C. Tian; J. Chen; S N. Diggavi; and S. Shamai.\n\n\n \n \n \n \n On source-channel separation in networks.\n \n \n \n\n\n \n\n\n\n In International Conference on Signal Processing and Communications (SPCOM), pages 1–5, June 2010. \n \n\n\n\n
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@inproceedings{TCDSc10b,\n abstract = {We consider the source-channel separation architecture\nfor lossy source coding in communication networks. It\nis shown that the separation approach is optimal when the\nmemoryless sources at source nodes are arbitrarily correlated,\neach of which is to be reconstructed at possibly multiple\ndestinations within certain distortions, and the channels in this\nnetwork are synchronized, orthogonal and memoryless (i.e., noisy\ngraphs).},\n author = {C. Tian and  J. Chen and S N. Diggavi and S. Shamai},\n booktitle = {International Conference on Signal Processing and Communications (SPCOM)},\n file = {:papers:tcdsspcom10.pdf},\n month = {June},\n note = {},\n pages = {1--5},\n tags = {conf,SrcChan,ITapprox,NDC,IT,SelConf},\n title = {On source-channel separation in networks},\n type = {4},\n year = {2010}\n}\n\n
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\n We consider the source-channel separation architecture for lossy source coding in communication networks. It is shown that the separation approach is optimal when the memoryless sources at source nodes are arbitrarily correlated, each of which is to be reconstructed at possibly multiple destinations within certain distortions, and the channels in this network are synchronized, orthogonal and memoryless (i.e., noisy graphs).\n
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\n \n\n \n \n C. Tian; S N. Diggavi; and S. Shamai.\n\n\n \n \n \n \n The achievable distortion region of bivariate Gaussian source on Gaussian broadcast channel.\n \n \n \n\n\n \n\n\n\n In Proc. of IEEE ISIT 2010, Austin, Texas, pages 146–150, June 2010. \n \n\n\n\n
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@inproceedings{TDSc10a,\n author = {C. Tian and  S N. Diggavi and S. Shamai},\n booktitle = {Proc. of IEEE ISIT 2010, Austin, Texas},\n month = {June},\n note = {},\n pages = {146--150},\n tags = {conf,SrcChan,NDC,IT},\n title = {The achievable distortion region of bivariate Gaussian source on \nGaussian broadcast channel},\n type = {4},\n year = {2010}\n}\n\n
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\n \n\n \n \n C. Tian; S N. Diggavi; and S. Shamai.\n\n\n \n \n \n \n An Approximate Characterization For the Gaussian Broadcasting Distortion Region.\n \n \n \n\n\n \n\n\n\n In IEEE International Symposium on Information Theory (ISIT), Seoul, Korea, pages 2477–2481, June 2009. \n \n\n\n\n
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@inproceedings{TDSj09,\n author = {C. Tian and S N. Diggavi and S. Shamai,},\n booktitle = {IEEE International Symposium on Information Theory (ISIT), Seoul, Korea},\n month = {June},\n note = {},\n pages = {2477--2481},\n tags = {conf,SrcChan,ApproxIT,NDC,IT},\n title = {An Approximate Characterization For the Gaussian Broadcasting Distortion Region},\n type = {4},\n year = {2009}\n}\n\n
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\n \n\n \n \n C. Tian; A. Steiner; S. Shamai(Shitz); and S N. Diggavi.\n\n\n \n \n \n \n Successive Refinement via Broadcasting: Optimizing Expected Distortion of a Gaussian Source over a Gaussian Fading Channel.\n \n \n \n\n\n \n\n\n\n IEEE Transactions on Information Theory, 54(7): 2903–2918. July 2008.\n \n\n\n\n
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@article{TSSDj08,\n abstract = {We consider the problem of transmitting a Gaussian\nsource on a slowly fading Gaussian channel, subject to the mean\nsquared error distortion measure.  We propose an\nefficient algorithm to compute the optimal expected distortion at the\nreceiver in linear time O(M), when the total number of possible discrete fading\nstates is M. We also provide a derivation of the optimal\npower allocation when the fading state is a continuum, using the\nclassical variational method.},\n author = {C. Tian and A. Steiner and S. Shamai(Shitz) and S N. Diggavi},\n file = {:papers:distortionbc_tssdfinal.pdf},\n journal = {IEEE Transactions on Information Theory},\n month = {July},\n note = {},\n number = {7},\n pages = {2903--2918},\n tags = {journal,SrcChan,IT},\n title = {Successive Refinement via Broadcasting: Optimizing Expected Distortion of a Gaussian Source over a Gaussian Fading Channel},\n type = {2},\n volume = {54},\n year = {2008}\n}\n\n
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\n We consider the problem of transmitting a Gaussian source on a slowly fading Gaussian channel, subject to the mean squared error distortion measure. We propose an efficient algorithm to compute the optimal expected distortion at the receiver in linear time O(M), when the total number of possible discrete fading states is M. We also provide a derivation of the optimal power allocation when the fading state is a continuum, using the classical variational method.\n
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\n \n\n \n \n A. Khisti; S N. Diggavi; and G W. Wornell.\n\n\n \n \n \n \n Secret key generation with correlated sources and noisy channels.\n \n \n \n\n\n \n\n\n\n In IEEE International Symposium on Information Theory (ISIT), Toronto, Canada, pages 1005–1009, July 2008. \n \n\n\n\n
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@inproceedings{KDWj08,\n author = {A. Khisti and S N. Diggavi and G W. Wornell,},\n booktitle = {IEEE International Symposium on Information Theory (ISIT), Toronto, Canada},\n month = {July},\n note = {},\n pages = {1005--1009},\n tags = {conf,ITsecrecy,KeyGen,IT,WiNetSec,SrcChanSec},\n title = {Secret key generation with correlated sources and noisy channels},\n type = {4},\n year = {2008}\n}\n\n
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\n \n\n \n \n C. Tian; A. Steiner; S. Shamai; and S N. Diggavi.\n\n\n \n \n \n \n Expected distortion for Gaussian source with broadcast transmission strategy over a fading channel.\n \n \n \n\n\n \n\n\n\n In IEEE Information Theory Workshop (ITW) Bergen, Norway, pages 42–46, July 2007. \n \n\n\n\n
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@inproceedings{TSSDj07,\n author = {C. Tian and A. Steiner and S. Shamai and S N. Diggavi},\n booktitle = {IEEE Information Theory Workshop (ITW) Bergen, Norway},\n month = {July},\n note = {},\n pages = {42--46},\n tags = {conf,SrcChan,IT},\n title = {Expected distortion for Gaussian source with broadcast transmission strategy over a fading channel},\n type = {4},\n year = {2007}\n}\n\n
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\n \n\n \n \n S. Dusad; S N. Diggavi; and A R. Calderbank.\n\n\n \n \n \n \n Cross Layer Utility of Diversity Embedded Codes.\n \n \n \n\n\n \n\n\n\n In IEEE Conference on Information Sciences and Systems, Princeton, March 2006. \n invited paper\n\n\n\n
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@inproceedings{DDCj06,\n author = {S. Dusad and S N. Diggavi and A R. Calderbank},\n booktitle = {IEEE Conference on Information Sciences and Systems, Princeton},\n month = {March},\n note = {invited paper},\n pages = {},\n tags = {conf,DivEmb,OppComm,SrcChan},\n title = {Cross Layer Utility of Diversity Embedded Codes},\n type = {4},\n year = {2006}\n}\n\n
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