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311
Spectral Efficiency in the Wideband Regime
, 2002
"... The tradeoff of spectral efficiency (b/s/Hz) versus energy perinformation bit is the key measure of channel capacity in the wideband powerlimited regime. This paper finds the fundamental bandwidthpower tradeoff of a general class of channels in the wideband regime characterized by low, but nonz ..."
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Cited by 393 (29 self)
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The tradeoff of spectral efficiency (b/s/Hz) versus energy perinformation bit is the key measure of channel capacity in the wideband powerlimited regime. This paper finds the fundamental bandwidthpower tradeoff of a general class of channels in the wideband regime characterized by low, but nonzero, spectral efficiency and energy per bit close to the minimum value required for reliable communication. A new criterion for optimality of signaling in the wideband regime is proposed, which, in contrast to the traditional criterion, is meaningful for finitebandwidth communication.
Mutual information and minimum meansquare error in Gaussian channels
 IEEE TRANS. INFORM. THEORY
, 2005
"... This paper deals with arbitrarily distributed finitepower input signals observed through an additive Gaussian noise channel. It shows a new formula that connects the inputoutput mutual information and the minimum meansquare error (MMSE) achievable by optimal estimation of the input given the out ..."
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Cited by 285 (32 self)
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This paper deals with arbitrarily distributed finitepower input signals observed through an additive Gaussian noise channel. It shows a new formula that connects the inputoutput mutual information and the minimum meansquare error (MMSE) achievable by optimal estimation of the input given the output. That is, the derivative of the mutual information (nats) with respect to the signaltonoise ratio (SNR) is equal to half the MMSE, regardless of the input statistics. This relationship holds for both scalar and vector signals, as well as for discretetime and continuoustime noncausal MMSE estimation. This fundamental informationtheoretic result has an unexpected consequence in continuoustime nonlinear estimation: For any input signal with finite power, the causal filtering MMSE achieved at SNR is equal to the average value of the noncausal smoothing MMSE achieved with a channel whose signaltonoise ratio is chosen uniformly distributed between 0 and SNR.
Sparse solution of underdetermined linear equations by stagewise orthogonal matching pursuit
, 2006
"... Finding the sparsest solution to underdetermined systems of linear equations y = Φx is NPhard in general. We show here that for systems with ‘typical’/‘random ’ Φ, a good approximation to the sparsest solution is obtained by applying a fixed number of standard operations from linear algebra. Our pr ..."
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Cited by 278 (23 self)
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Finding the sparsest solution to underdetermined systems of linear equations y = Φx is NPhard in general. We show here that for systems with ‘typical’/‘random ’ Φ, a good approximation to the sparsest solution is obtained by applying a fixed number of standard operations from linear algebra. Our proposal, Stagewise Orthogonal Matching Pursuit (StOMP), successively transforms the signal into a negligible residual. Starting with initial residual r0 = y, at the sth stage it forms the ‘matched filter ’ Φ T rs−1, identifies all coordinates with amplitudes exceeding a speciallychosen threshold, solves a leastsquares problem using the selected coordinates, and subtracts the leastsquares fit, producing a new residual. After a fixed number of stages (e.g. 10), it stops. In contrast to Orthogonal Matching Pursuit (OMP), many coefficients can enter the model at each stage in StOMP while only one enters per stage in OMP; and StOMP takes a fixed number of stages (e.g. 10), while OMP can take many (e.g. n). StOMP runs much faster than competing proposals for sparse solutions, such as ℓ1 minimization and OMP, and so is attractive for solving largescale problems. We use phase diagrams to compare algorithm performance. The problem of recovering a ksparse vector x0 from (y, Φ) where Φ is random n × N and y = Φx0 is represented by a point (n/N, k/n)
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 257 (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.
Scaling up MIMO: Opportunities and challenges with very large arrays
 IEEE Signal Process. Mag
, 2013
"... N.B.: When citing this work, cite the original article. ©2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to ..."
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Cited by 214 (26 self)
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N.B.: When citing this work, cite the original article. ©2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Multipleantenna channel hardening and its implications for rate feedback and scheduling
 IEEE Transactions on Information Theory
, 2004
"... Wireless data traffic is expected to grow over the next few years and the technologies that will provide data services are still being debated. One possibility is to use multiple antennas at basestations and terminals to get very high spectral efficiencies in rich scattering environments. Such multi ..."
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Cited by 156 (2 self)
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Wireless data traffic is expected to grow over the next few years and the technologies that will provide data services are still being debated. One possibility is to use multiple antennas at basestations and terminals to get very high spectral efficiencies in rich scattering environments. Such multipleinput multipleoutput (MIMO) channels can then be used in conjunction with scheduling and ratefeedback algorithms to further increase channel throughput. This paper provides an analysis of the expected gains due to scheduling and bits needed for rate feedback. Our analysis requires an accurate approximation of the distribution of the MIMO channel mutual information. Because the exact distribution of the mutual information in a Rayleigh fading environment is difficult to analyze, we prove a central limit theorem for MIMO channels with a large number of antennas. While the growth in average mutual information (capacity) of a MIMO channel with the number of antennas is well understood, it turns out that the variance of the mutual information can grow very slowly or even shrink as the number of antennas grows. We discuss implications of this “channelhardening ” result for data and voice services, scheduling and rate feedback. We also briefly discuss the implications when shadow fading effects are included. Index Terms—Wireless communications, transmit diversity, receive diversity, fading channels 1
Zigzag decoding: Combating hidden terminals in wireless networks
, 2008
"... This paper presents ZigZag, an 802.11 receiver design that combats hidden terminals. ZigZag’s core contribution is a new form of interference cancellation that exploits asynchrony across successive collisions. Specifically, 802.11 retransmissions, in the case of hidden terminals, cause successive co ..."
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Cited by 154 (9 self)
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This paper presents ZigZag, an 802.11 receiver design that combats hidden terminals. ZigZag’s core contribution is a new form of interference cancellation that exploits asynchrony across successive collisions. Specifically, 802.11 retransmissions, in the case of hidden terminals, cause successive collisions. These collisions have different interferencefree stretches at their start, which ZigZag exploits to bootstrap its decoding. ZigZag makes no changes to the 802.11 MAC and introduces no overhead when there are no collisions. But, when senders collide, ZigZag attains the same throughput as if the colliding packets were a priori scheduled in separate time slots. We build a prototype of ZigZag in GNU Radio. In a testbed of 14 USRP nodes, ZigZag reduces the average packet loss rate at hidden terminals from 72.6% to about 0.7%.
Iterative multiuser joint decoding: unified framework and asymptotic analysis
 IEEE Trans. Inform. Theory
, 2002
"... Abstract—We present a framework for iterative multiuser joint decoding of codedivision multipleaccess (CDMA) signals, based on the factorgraph representation and on the sumproduct algorithm. In this framework, known parallel and serial, hard and soft interference cancellation algorithms are der ..."
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Cited by 119 (3 self)
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Abstract—We present a framework for iterative multiuser joint decoding of codedivision multipleaccess (CDMA) signals, based on the factorgraph representation and on the sumproduct algorithm. In this framework, known parallel and serial, hard and soft interference cancellation algorithms are derived in a unified way. The asymptotic performance of these algorithms in the limit of large code block length can be rigorously analyzed by using density evolution. We show that, for random spreading in the largesystem limit, density evolution is considerably simplified. Moreover, by making a Gaussian approximation of the decoder soft output, we show that the behavior of iterative multiuser joint decoding is approximately characterized by the stable fixed points of a simple onedimensional nonlinear dynamical system. Index Terms—Density evolution, interference cancellation, iterative decoding, multiuser detection (MUD). I.
Impact of antenna correlation on the capacity of multiantenna channels
 IEEE TRANS. INFORM. THEORY
, 2005
"... This paper applies random matrix theory to obtain analytical characterizations of the capacity of correlated multiantenna channels. The analysis is not restricted to the popular separable correlation model, but rather it embraces a more general representation that subsumes most of the channel model ..."
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Cited by 101 (6 self)
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This paper applies random matrix theory to obtain analytical characterizations of the capacity of correlated multiantenna channels. The analysis is not restricted to the popular separable correlation model, but rather it embraces a more general representation that subsumes most of the channel models that have been treated in the literature. For arbitrary signaltonoise ratios @ A, the characterization is conducted in the regime of large numbers of antennas. For the low and high regions, in turn, we uncover compact capacity expansions that are valid for arbitrary numbers of antennas and that shed insight on how antenna correlation impacts the tradeoffs among power, bandwidth, and rate.