The Experts below are selected from a list of 87 Experts worldwide ranked by ideXlab platform
Giuseppe Caire - One of the best experts on this subject based on the ideXlab platform.
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order optiMal rate of caching and coded Multicasting with randoM deMands
IEEE Transactions on Information Theory, 2017Co-Authors: Antonia M Tulino, Jaime Llorca, Giuseppe CaireAbstract:We consider the canonical shared link caching network forMed by a source node, hosting a library of $M$ inforMation Messages (files), connected via a noiseless Multicast link to $n$ user nodes, each equipped with a cache of size $M$ files. Users request files independently at randoM according to an a-priori known deMand distribution q. A coding scheMe for this network consists of two phases: cache placeMent and delivery. The cache placeMent is a Mapping of the library files onto the user caches that can be optiMized as a function of the deMand statistics, but is agnostic of the actual deMand realization. After the user deMands are revealed, during the delivery phase the source sends a codeword (function of the library files, cache placeMent, and deMands) to the users, such that each user retrieves its requested file with arbitrarily high probability. The goal is to MiniMize the average transMission length of the delivery phase, referred to as rate (expressed in channel syMbols per file). In the case of deterMinistic deMands, the optiMal Min-Max rate has been characterized within a constant Multiplicative factor, independent of the network paraMeters. The case of randoM deMands was previously addressed by applying the order-optiMal Min-Max scheMe separately within groups of files requested with siMilar probability. However, no coMplete characterization of order-optiMality was previously provided for randoM deMands under the average rate perforMance criterion. In this paper, we consider the randoM deMand setting and, for the special yet relevant case of a Zipf deMand distribution, we provide a coMprehensive characterization of the order-optiMal rate for all regiMes of the systeM paraMeters, as well as an explicit placeMent and delivery scheMe achieving order-optiMal rates. We present also nuMerical results that confirM the superiority of our scheMe with respect to previously proposed scheMes for the saMe setting.
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order optiMal rate of caching and coded Multicasting with randoM deMands
arXiv: Information Theory, 2015Co-Authors: Antonia M Tulino, Jaime Llorca, Giuseppe CaireAbstract:We consider the canonical {\eM shared link network} forMed by a source node, hosting a library of $M$ inforMation Messages (files), connected via a noiseless coMMon link to $n$ destination nodes (users), each with a cache of size M files. Users request files at randoM and independently, according to a given a-priori deMand distribution $\qv$. A coding scheMe for this network consists of a caching placeMent (i.e., a Mapping of the library files into the user caches) and delivery scheMe (i.e., a Mapping for the library files and user deMands into a coMMon Multicast codeword) such that, after the codeword transMission, all users can retrieve their requested file. The rate of the scheMe is defined as the {\eM average} codeword length norMalized with respect to the length of one file, where expectation is taken over the randoM user deMands. For the saMe shared link network, in the case of deterMinistic deMands, the optiMal Min-Max rate has been characterized within a uniforM bound, independent of the network paraMeters. In particular, fractional caching (i.e., storing file segMents) and using linear network coding has been shown to provide a Min-Max rate reduction proportional to 1/M with respect to standard scheMes such as unicasting or "naive" uncoded Multicasting. The case of randoM deMands was previously considered by applying the saMe order-optiMal Min-Max scheMe separately within groups of files requested with siMilar probability. However, no order-optiMal guarantee was provided for randoM deMands under the average rate perforMance criterion. In this paper, we consider the randoM deMand setting and provide general achievability and converse results. In particular, we consider a faMily of scheMes that coMbine randoM fractional caching according to a probability distribution $\pv$ that depends on the deMand distribution $\qv$, with a linear coded delivery scheMe based on ...
Antonia M Tulino - One of the best experts on this subject based on the ideXlab platform.
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order optiMal rate of caching and coded Multicasting with randoM deMands
IEEE Transactions on Information Theory, 2017Co-Authors: Antonia M Tulino, Jaime Llorca, Giuseppe CaireAbstract:We consider the canonical shared link caching network forMed by a source node, hosting a library of $M$ inforMation Messages (files), connected via a noiseless Multicast link to $n$ user nodes, each equipped with a cache of size $M$ files. Users request files independently at randoM according to an a-priori known deMand distribution q. A coding scheMe for this network consists of two phases: cache placeMent and delivery. The cache placeMent is a Mapping of the library files onto the user caches that can be optiMized as a function of the deMand statistics, but is agnostic of the actual deMand realization. After the user deMands are revealed, during the delivery phase the source sends a codeword (function of the library files, cache placeMent, and deMands) to the users, such that each user retrieves its requested file with arbitrarily high probability. The goal is to MiniMize the average transMission length of the delivery phase, referred to as rate (expressed in channel syMbols per file). In the case of deterMinistic deMands, the optiMal Min-Max rate has been characterized within a constant Multiplicative factor, independent of the network paraMeters. The case of randoM deMands was previously addressed by applying the order-optiMal Min-Max scheMe separately within groups of files requested with siMilar probability. However, no coMplete characterization of order-optiMality was previously provided for randoM deMands under the average rate perforMance criterion. In this paper, we consider the randoM deMand setting and, for the special yet relevant case of a Zipf deMand distribution, we provide a coMprehensive characterization of the order-optiMal rate for all regiMes of the systeM paraMeters, as well as an explicit placeMent and delivery scheMe achieving order-optiMal rates. We present also nuMerical results that confirM the superiority of our scheMe with respect to previously proposed scheMes for the saMe setting.
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order optiMal rate of caching and coded Multicasting with randoM deMands
arXiv: Information Theory, 2015Co-Authors: Antonia M Tulino, Jaime Llorca, Giuseppe CaireAbstract:We consider the canonical {\eM shared link network} forMed by a source node, hosting a library of $M$ inforMation Messages (files), connected via a noiseless coMMon link to $n$ destination nodes (users), each with a cache of size M files. Users request files at randoM and independently, according to a given a-priori deMand distribution $\qv$. A coding scheMe for this network consists of a caching placeMent (i.e., a Mapping of the library files into the user caches) and delivery scheMe (i.e., a Mapping for the library files and user deMands into a coMMon Multicast codeword) such that, after the codeword transMission, all users can retrieve their requested file. The rate of the scheMe is defined as the {\eM average} codeword length norMalized with respect to the length of one file, where expectation is taken over the randoM user deMands. For the saMe shared link network, in the case of deterMinistic deMands, the optiMal Min-Max rate has been characterized within a uniforM bound, independent of the network paraMeters. In particular, fractional caching (i.e., storing file segMents) and using linear network coding has been shown to provide a Min-Max rate reduction proportional to 1/M with respect to standard scheMes such as unicasting or "naive" uncoded Multicasting. The case of randoM deMands was previously considered by applying the saMe order-optiMal Min-Max scheMe separately within groups of files requested with siMilar probability. However, no order-optiMal guarantee was provided for randoM deMands under the average rate perforMance criterion. In this paper, we consider the randoM deMand setting and provide general achievability and converse results. In particular, we consider a faMily of scheMes that coMbine randoM fractional caching according to a probability distribution $\pv$ that depends on the deMand distribution $\qv$, with a linear coded delivery scheMe based on ...
J C Belfiore - One of the best experts on this subject based on the ideXlab platform.
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a new faMily of full rate fully diverse space tiMe codes based on galois theory
International Symposium on Information Theory, 2002Co-Authors: S Galliou, J C BelfioreAbstract:We introduce in this paper a new faMily of space-tiMe codes. These codes are linear, thus they can be decoded via the sphere decoding algorithM or any interference cancellation algorithM. They are full rate, Meaning that the systeM transMits M inforMation syMbols per channel use, M being the nuMber of transMit antennas. They are also fully diverse, and inforMation lossless. Thus, the new faMily of spacetiMe codes presented here appears as a well-suited solution for high data rate transMission systeMs.
Jaime Llorca - One of the best experts on this subject based on the ideXlab platform.
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order optiMal rate of caching and coded Multicasting with randoM deMands
IEEE Transactions on Information Theory, 2017Co-Authors: Antonia M Tulino, Jaime Llorca, Giuseppe CaireAbstract:We consider the canonical shared link caching network forMed by a source node, hosting a library of $M$ inforMation Messages (files), connected via a noiseless Multicast link to $n$ user nodes, each equipped with a cache of size $M$ files. Users request files independently at randoM according to an a-priori known deMand distribution q. A coding scheMe for this network consists of two phases: cache placeMent and delivery. The cache placeMent is a Mapping of the library files onto the user caches that can be optiMized as a function of the deMand statistics, but is agnostic of the actual deMand realization. After the user deMands are revealed, during the delivery phase the source sends a codeword (function of the library files, cache placeMent, and deMands) to the users, such that each user retrieves its requested file with arbitrarily high probability. The goal is to MiniMize the average transMission length of the delivery phase, referred to as rate (expressed in channel syMbols per file). In the case of deterMinistic deMands, the optiMal Min-Max rate has been characterized within a constant Multiplicative factor, independent of the network paraMeters. The case of randoM deMands was previously addressed by applying the order-optiMal Min-Max scheMe separately within groups of files requested with siMilar probability. However, no coMplete characterization of order-optiMality was previously provided for randoM deMands under the average rate perforMance criterion. In this paper, we consider the randoM deMand setting and, for the special yet relevant case of a Zipf deMand distribution, we provide a coMprehensive characterization of the order-optiMal rate for all regiMes of the systeM paraMeters, as well as an explicit placeMent and delivery scheMe achieving order-optiMal rates. We present also nuMerical results that confirM the superiority of our scheMe with respect to previously proposed scheMes for the saMe setting.
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order optiMal rate of caching and coded Multicasting with randoM deMands
arXiv: Information Theory, 2015Co-Authors: Antonia M Tulino, Jaime Llorca, Giuseppe CaireAbstract:We consider the canonical {\eM shared link network} forMed by a source node, hosting a library of $M$ inforMation Messages (files), connected via a noiseless coMMon link to $n$ destination nodes (users), each with a cache of size M files. Users request files at randoM and independently, according to a given a-priori deMand distribution $\qv$. A coding scheMe for this network consists of a caching placeMent (i.e., a Mapping of the library files into the user caches) and delivery scheMe (i.e., a Mapping for the library files and user deMands into a coMMon Multicast codeword) such that, after the codeword transMission, all users can retrieve their requested file. The rate of the scheMe is defined as the {\eM average} codeword length norMalized with respect to the length of one file, where expectation is taken over the randoM user deMands. For the saMe shared link network, in the case of deterMinistic deMands, the optiMal Min-Max rate has been characterized within a uniforM bound, independent of the network paraMeters. In particular, fractional caching (i.e., storing file segMents) and using linear network coding has been shown to provide a Min-Max rate reduction proportional to 1/M with respect to standard scheMes such as unicasting or "naive" uncoded Multicasting. The case of randoM deMands was previously considered by applying the saMe order-optiMal Min-Max scheMe separately within groups of files requested with siMilar probability. However, no order-optiMal guarantee was provided for randoM deMands under the average rate perforMance criterion. In this paper, we consider the randoM deMand setting and provide general achievability and converse results. In particular, we consider a faMily of scheMes that coMbine randoM fractional caching according to a probability distribution $\pv$ that depends on the deMand distribution $\qv$, with a linear coded delivery scheMe based on ...
Xiaodong Wang - One of the best experts on this subject based on the ideXlab platform.
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Multiuser Diversity Gain in Cognitive Networks
arXiv: Information Theory, 2010Co-Authors: Ali Tajer, Xiaodong WangAbstract:DynaMic allocation of resources to the \eMph{best} link in large Multiuser networks offers considerable iMproveMent in spectral efficiency. This gain, often referred to as \eMph{Multiuser diversity gain}, can be cast as double-logarithMic growth of the network throughput with the nuMber of users. In this paper we consider large cognitive networks granted concurrent spectruM access with license-holding users. The priMary network affords to share its under-utilized spectruM bands with the secondary users. We assess the optiMal Multiuser diversity gain in the cognitive networks by quantifying how the suM-rate throughput of the network scales with the nuMber of secondary users. For this purpose we look at the optiMal pairing of spectruM bands and secondary users, which is supervised by a central entity fully aware of the instantaneous channel conditions, and show that the throughput of the cognitive network scales double-logarithMically with the nuMber of secondary users ($N$) and linearly with the nuMber of available spectruM bands ($M$), i.e., $M\log\log N$. We then propose a \eMph{distributed} spectruM allocation scheMe, which does not necessitate a central controller or any inforMation exchange between different secondary users and still obeys the optiMal throughput scaling law. This scheMe requires that \eMph{soMe} secondary transMitter-receiver pairs exchange $\log M$ inforMation bits aMong theMselves. We also show that the aggregate aMount of inforMation exchange between secondary transMitter-receiver pairs is {\eM asyMptotically} equal to $M\log M$. Finally, we show that our distributed scheMe guarantees fairness aMong the secondary users, Meaning that they are equally likely to get access to an available spectruM band.
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Multiuser diversity gain in cognitive networks
IEEE ACM Transactions on Networking, 2010Co-Authors: Ali Tajer, Xiaodong WangAbstract:DynaMic allocation of resources to the best link in large Multiuser networks offers considerable iMproveMent in spectral efficiency. This gain, often referred to as Multiuser diversity gain, can be cast as double-logarithMic growth of the network throughput with the nuMber of users. In this paper, we consider large cognitive networks granted concurrent spectruM access with license-holding users. The priMary network affords to share its underutilized spectruM bands with the secondary users. We assess the optiMal Multiuser diversity gain in the cognitive networks by quantifying how the suM-rate throughput of the network scales with the nuMber of secondary users. For this purpose, we look at the optiMal pairing of spectruM bands and secondary users, which is supervised by a central entity fully aware of the instantaneous channel conditions, and show that the throughput of the cognitive network scales double-logarithMically with the nuMber of secondary users (N) and linearly with the nuMber of available spectruM bands (M), i.e., M log log N. We then propose a distributed spectruM allocation scheMe, which does not necessitate a central controller or any inforMation exchange aMong different secondary users and still obeys the optiMal throughput scaling law. This scheMe requires that soMe secondary transMitter-receiver pairs exchange log M inforMation bits aMong theMselves. We also show that the aggregate aMount of inforMation exchange between secondary transMitter-receiver pairs is asyMptotically equal to M log M. Finally, we show that our distributed scheMe guarantees fairness aMong the secondary users, Meaning that they are equally likely to get access to an available spectruM band.
