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604
Supporting Stored Video: Reducing Rate Variability and EndtoEnd Resource Requirements through Optimal Smoothing
 IEEE/ACM Transactions on Networking
, 1998
"... Variablebitrate compressed video can exhibit significant, multipletimescale bit rate variability. In this paper we consider the transmission of stored video from a server to a client across a network, and explore how the client buffer space can be used most effectively toward reducing the variab ..."
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Cited by 219 (17 self)
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Variablebitrate compressed video can exhibit significant, multipletimescale bit rate variability. In this paper we consider the transmission of stored video from a server to a client across a network, and explore how the client buffer space can be used most effectively toward reducing the variability of the transmitted bit rate. Two basic results are presented. First, we show how to achieve the greatest possible reduction in rate variability when sending stored video to a client with given buffer size. We formally establish the optimality of our approach and illustrate its performance over a set of long MPEG1 encoded video traces. Second, we evaluate the impact of optimal smoothing on the network resources needed for video transport, under two network service models: Deterministic Guaranteed service [1, 31] and Renegotiated CBR (RCBR) service [9]. Under both models the impact of optimal smoothing is dramatic. 1 Introduction A broad range of applications is enabled by the capac...
Capacity Scaling in MIMO Wireless Systems Under Correlated Fading
 IEEE TRANS. INFORM. THEORY
, 2002
"... Previous studies have shown that singleuser systems employingelement antenna arrays at both the transmitter and the receiver can achieve a capacity proportional to , assuming independent Rayleigh fading between antenna pairs. In this paper, we explore the capacity of dualantennaarray systems und ..."
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Cited by 183 (2 self)
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Previous studies have shown that singleuser systems employingelement antenna arrays at both the transmitter and the receiver can achieve a capacity proportional to , assuming independent Rayleigh fading between antenna pairs. In this paper, we explore the capacity of dualantennaarray systems under correlated fading via theoretical analysis and raytracing simulations. We derive and compare expressions for the asymptotic growth rate of capacity with antennas for both independent and correlated fading cases; the latter is derived under some assumptions about the scaling of the fading correlation structure. In both cases, the theoretic capacity growth is linear in but the growth rate is 1020% smaller in the presence of correlated fading. We analyze our assumption of separable transmit/receive correlations via simulations based on a raytracing propagation model. Results show that empirical capacities converge to the limit capacity predicted from our asymptotic theory even at moderate n=16. We present results for both the cases when the transmitter does and does not know the channel realization.
Balancing Histogram Optimality and Practicality for Query Result Size Estimation
, 1995
"... Many current database systems use histograms to approximate the frequency distribution of values in the attributes of relations and based on them estimate query result sizes and access plan costs. In choosing among the various histograms, one has to balance between two conflicting goals: optimality, ..."
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Cited by 135 (14 self)
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Many current database systems use histograms to approximate the frequency distribution of values in the attributes of relations and based on them estimate query result sizes and access plan costs. In choosing among the various histograms, one has to balance between two conflicting goals: optimality, so that generated estimates have the least error, and practicality, so that histograms can be constructed and maintained efficiently. In this paper, we present both theoretical and experimental results on several issues related to this tradeoff. Our overall conclusion is that the most effective approach is to focus on the class of histograms that accurately maintain the frequencies of a few attribute values and assume the uniform distribution for the rest, and choose for each relation the histogram in that class that is optimal for a selfjoin query. 1 Introduction Query optimizers of relational database systems decide on the most efficient access plan for a given query based on a variety...
Joint TxRx beamforming design for multicarrier MIMO channels: a unified framework for convex optimization
 IEEE TRANS. SIGNAL PROCESSING
, 2003
"... This paper addresses the joint design of transmit and receive beamforming or linear processing (commonly termed linear precoding at the transmitter and equalization at the receiver) for multicarrier multipleinput multipleoutput (MIMO) channels under a variety of design criteria. Instead of consid ..."
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Cited by 127 (12 self)
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This paper addresses the joint design of transmit and receive beamforming or linear processing (commonly termed linear precoding at the transmitter and equalization at the receiver) for multicarrier multipleinput multipleoutput (MIMO) channels under a variety of design criteria. Instead of considering each design criterion in a separate way, we generalize the existing results by developing a unified framework based on considering two families of objective functions that embrace most reasonable criteria to design a communication system: Schurconcave and Schurconvex functions. Once the optimal structure of the transmitreceive processing is known, the design problem simplifies and can be formulated within the powerful framework of convex optimization theory, in which a great number of interesting design criteria can be easily accommodated and efficiently solved, even though closedform expressions may not exist. From this perspective, we analyze a variety of design criteria, and in particular, we derive optimal beamvectors in the sense of having minimum average bit error rate (BER). Additional constraints on the peaktoaverage ratio (PAR) or on the signal dynamic range are easily included in the design. We propose two multilevel waterfilling practical solutions that perform very close to the optimal in terms of average BER with a low implementation complexity. If cooperation among the processing operating at different carriers is allowed, the performance improves significantly. Interestingly, with carrier cooperation, it turns out that the exact optimal solution in terms of average BER can be obtained in closed form.
Capacity bounds via duality with applications to multipleantenna systems on flatfading channels
 IEEE Trans. Inform. Theory
, 2003
"... A general technique is proposed for the derivation of upper bounds on channel capacity. The technique is based on a dual expression for channel capacity where the maximization (of mutual information) over distributions on the channel input alphabet is replaced with a minimization (of average relativ ..."
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Cited by 107 (37 self)
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A general technique is proposed for the derivation of upper bounds on channel capacity. The technique is based on a dual expression for channel capacity where the maximization (of mutual information) over distributions on the channel input alphabet is replaced with a minimization (of average relative entropy) over distributions on the channel output alphabet. Every choice of an output distribution — even if not the channel image of some input distribution — leads to an upper bound on mutual information. The proposed approach is used in order to study multiantenna flat fading channels with memory where the realization of the fading process is unknown at the transmitter and unknown (or only partially known) at the receiver. It is demonstrated that, for high signaltonoise ratio (SNR), the capacity of such channels typically grows only doublelogarithmically in the SNR. This is in stark contrast to the case with perfect receiver side information where capacity grows logarithmically in the SNR. To better understand this phenomenon
The Critical Transmitting Range for Connectivity in Sparse Wireless Ad Hoc Networks
, 2003
"... In this paper, we analyze the critical transmitting range for connectivity in wireless ad hoc networks. More specifically, we consider the following problem: assume n nodes, each capable of communicating with nodes within a radius of r, are randomly and uniformly distributed in a ddimensional re ..."
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Cited by 100 (12 self)
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In this paper, we analyze the critical transmitting range for connectivity in wireless ad hoc networks. More specifically, we consider the following problem: assume n nodes, each capable of communicating with nodes within a radius of r, are randomly and uniformly distributed in a ddimensional region with a side of length l; how large must the transmitting range r be to ensure that the resulting network is connected with high probability? First, we consider this problem for stationary networks, and we provide tight upper and lower bounds on the critical transmitting range for onedimensional networks, and nontight bounds for two and threedimensional networks. Due to the presence of the geometric parameter l in the model, our results can be applied to dense as well as sparse ad hoc networks, contrary to existing theoretical results that apply only to dense networks. We also investigate several related questions through extensive simulations. First, we evaluate the relationship between the critical transmitting range and the minimum transmitting range that ensures formation of a connected component containing a large fraction (e.g. 90%) of the nodes. Then, we consider the mobile version of the
Learning the kernel function via regularization
 Journal of Machine Learning Research
, 2005
"... We study the problem of finding an optimal kernel from a prescribed convex set of kernels K for learning a realvalued function by regularization. We establish for a wide variety of regularization functionals that this leads to a convex optimization problem and, for square loss regularization, we ch ..."
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Cited by 96 (7 self)
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We study the problem of finding an optimal kernel from a prescribed convex set of kernels K for learning a realvalued function by regularization. We establish for a wide variety of regularization functionals that this leads to a convex optimization problem and, for square loss regularization, we characterize the solution of this problem. We show that, although K may be an uncountable set, the optimal kernel is always obtained as a convex combination of at most m+2 basic kernels, where m is the number of data examples. In particular, our results apply to learning the optimal radial kernel or the optimal dot product kernel. 1.
The Mathematics Of Eigenvalue Optimization
, 2003
"... Optimization problems involving the eigenvalues of symmetric and nonsymmetric matrices present a fascinating mathematical challenge. Such problems arise often in theory and practice, particularly in engineering design, and are amenable to a rich blend of classical mathematical techniques and contemp ..."
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Cited by 92 (13 self)
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Optimization problems involving the eigenvalues of symmetric and nonsymmetric matrices present a fascinating mathematical challenge. Such problems arise often in theory and practice, particularly in engineering design, and are amenable to a rich blend of classical mathematical techniques and contemporary optimization theory. This essay presents a personal choice of some central mathematical ideas, outlined for the broad optimization community. I discuss the convex analysis of spectral functions and invariant matrix norms, touching briey on semide nite representability, and then outlining two broader algebraic viewpoints based on hyperbolic polynomials and Lie algebra. Analogous nonconvex notions lead into eigenvalue perturbation theory. The last third of the article concerns stability, for polynomials, matrices, and associated dynamical systems, ending with a section on robustness. The powerful and elegant language of nonsmooth analysis appears throughout, as a unifying narrative thread.
The History of Histograms (abridged)
 PROC. OF VLDB CONFERENCE
, 2003
"... The history of histograms is long and rich, full of detailed information in every step. It includes the course of histograms in diFFerent scientific fields, the successes and failures of histograms in approximating and compressing information, their adoption by industry, and solutions that hav ..."
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Cited by 85 (0 self)
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The history of histograms is long and rich, full of detailed information in every step. It includes the course of histograms in diFFerent scientific fields, the successes and failures of histograms in approximating and compressing information, their adoption by industry, and solutions that have been given on a great variety of histogramrelated problems. In this paper and in the same spirit of the histogram techniques themselves, we compress their entire history (including their "future history" as currently anticipated) in the given/fixed space budget, mostly recording details for the periods, events, and results with the highest (personallybiased) interest. In a limited set of experiments, the semantic distance between the compressed and the full form of the history was found relatively small!