Results 11  20
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7,858
Phase transition of the largest eigenvalue for nonnull complex sample covariance matrices
, 2008
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Grassmannian beamforming for multipleinput multipleoutput wireless systems
 IEEE TRANS. INFORM. THEORY
, 2003
"... Transmit beamforming and receive combining are simple methods for exploiting the significant diversity that is available in multipleinput and multipleoutput (MIMO) wireless systems. Unfortunately, optimal performance requires either complete channel knowledge or knowledge of the optimal beamformi ..."
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Cited by 329 (39 self)
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Transmit beamforming and receive combining are simple methods for exploiting the significant diversity that is available in multipleinput and multipleoutput (MIMO) wireless systems. Unfortunately, optimal performance requires either complete channel knowledge or knowledge of the optimal
Eigenvalues of large sample covariance matrices of spiked population models
, 2006
"... We consider a spiked population model, proposed by Johnstone, whose population eigenvalues are all unit except for a few fixed eigenvalues. The question is to determine how the sample eigenvalues depend on the nonunit population ones when both sample size and population size become large. This pape ..."
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Cited by 163 (8 self)
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We consider a spiked population model, proposed by Johnstone, whose population eigenvalues are all unit except for a few fixed eigenvalues. The question is to determine how the sample eigenvalues depend on the nonunit population ones when both sample size and population size become large
The effect upon channel capacity in wireless communications of perfect and imperfect knowledge of the channel
 IEEE Trans. Inf. Theory
, 2000
"... Abstract—We present a model for timevarying communication singleaccess and multipleaccess channels without feedback. We consider the difference between mutual information when the receiver knows the channel perfectly and mutual information when the receiver only has an estimate of the channel. We ..."
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Cited by 274 (5 self)
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of the channel to the loss in mutual information due to imperfect knowledge of the measured channel. Index Terms—Channel uncertainty, multipleaccess channels, mutual information, timevarying channels, wireless communications. I.
Linear Multiuser Receivers: Effective Interference, Effective Bandwidth and User Capacity
 IEEE Trans. Inform. Theory
, 1999
"... Multiuser receivers improve the performance of spreadspectrum and antennaarray systems by exploiting the structure of the multiaccess interference when demodulating the signal of a user. Much of the previous work on the performance analysis of multiuser receivers has focused on their ability to re ..."
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Cited by 358 (13 self)
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Multiuser receivers improve the performance of spreadspectrum and antennaarray systems by exploiting the structure of the multiaccess interference when demodulating the signal of a user. Much of the previous work on the performance analysis of multiuser receivers has focused on their ability to reject worst case interference. Their performance in a powercontrolled network and the resulting user capacity are less wellunderstood. In this paper, we show that in a large system with each user using random spreading sequences, the limiting interference effects under several linear multiuser receivers can be decoupled, such that each interferer can be ascribed a level of effective interference that it provides to the user to be demodulated. Applying these results to the uplink of a single powercontrolled cell, we derive an effective bandwidth characterization of the user capacity: the signaltointerference requirements of all the users can be met if and only if the sum of the effective bandwidths of the users is less than the total number of degrees of freedom in the system. The effective bandwidth of a user depends only on its own SIR requirement, and simple expressions are derived for three linear receivers: the conventional matched filter, the decorrelator, and the MMSE receiver. The effective bandwidths under the three receivers serve as a basis for performance comparison.
Compressive Sensing and Structured Random Matrices
 RADON SERIES COMP. APPL. MATH XX, 1–95 © DE GRUYTER 20YY
"... These notes give a mathematical introduction to compressive sensing focusing on recovery using ℓ1minimization and structured random matrices. An emphasis is put on techniques for proving probabilistic estimates for condition numbers of structured random matrices. Estimates of this type are key to ..."
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Cited by 162 (19 self)
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These notes give a mathematical introduction to compressive sensing focusing on recovery using ℓ1minimization and structured random matrices. An emphasis is put on techniques for proving probabilistic estimates for condition numbers of structured random matrices. Estimates of this type are key
Frequency Domain Equalization for SingleCarrier Broadband Wireless Systems
 IEEE Commun. Mag
, 2002
"... this document does not refer to rms delay spread, but rather to thetotal time span of the measurable channel impulse response. 2% of the measured paths had rms delay spreads of over 2 s.; the average was 0.14 s. A 2 s. rms delay spread could be equivalent to a channel impulse response spanning rough ..."
Abstract

Cited by 294 (6 self)
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this document does not refer to rms delay spread, but rather to thetotal time span of the measurable channel impulse response. 2% of the measured paths had rms delay spreads of over 2 s.; the average was 0.14 s. A 2 s. rms delay spread could be equivalent to a channel impulse response spanning roughly 810 s
The capacity region of the Gaussian multipleinput multipleoutput broadcast channel
 IEEE TRANS. INF. THEORY
, 2006
"... The Gaussian multipleinput multipleoutput (MIMO) broadcast channel (BC) is considered. The dirtypaper coding (DPC) rate region is shown to coincide with the capacity region. To that end, a new notion of an enhanced broadcast channel is introduced and is used jointly with the entropy power inequa ..."
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Cited by 340 (7 self)
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The Gaussian multipleinput multipleoutput (MIMO) broadcast channel (BC) is considered. The dirtypaper coding (DPC) rate region is shown to coincide with the capacity region. To that end, a new notion of an enhanced broadcast channel is introduced and is used jointly with the entropy power inequality, to show that a superposition of Gaussian codes is optimal for the degraded vector broadcast channel and that DPC is optimal for the nondegraded case. Furthermore, the capacity region is characterized under a wide range of input constraints, accounting, as special cases, for the total power and the perantenna power constraints.
Sum capacity of the vector Gaussian broadcast channel and uplinkdownlink duality
 IEEE Trans. on Inform. Theory
, 1912
"... We characterize the sum capacity of the vector Gaussian broadcast channel by showing that the existing inner bound of Marton and the existing upper bound of Sato are tight for this channel. We exploit an intimate fourway connection between the vector broadcast channel, the corresponding pointtopo ..."
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Cited by 323 (2 self)
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We characterize the sum capacity of the vector Gaussian broadcast channel by showing that the existing inner bound of Marton and the existing upper bound of Sato are tight for this channel. We exploit an intimate fourway connection between the vector broadcast channel, the corresponding point
Eigenvalue variance bounds for Wigner and covariance random matrices
 RMTA
"... Abstract. This work is concerned with finite range bounds on the variance of individual eigenvalues of Wigner random matrices, in the bulk and at the edge of the spectrum, as well as for some intermediate eigenvalues. Relying on the GUE example, which needs to be investigated first, the main bounds ..."
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Cited by 5 (1 self)
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Abstract. This work is concerned with finite range bounds on the variance of individual eigenvalues of Wigner random matrices, in the bulk and at the edge of the spectrum, as well as for some intermediate eigenvalues. Relying on the GUE example, which needs to be investigated first, the main
Results 11  20
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7,858