Results 1  10
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22
HighSNR power offset in multiantenna communication
 IEEE Transactions on Information Theory
, 2005
"... Abstract—The analysis of the multipleantenna capacity in the high regime has hitherto focused on the high slope (or maximum multiplexing gain), which quantifies the multiplicative increase as a function of the number of antennas. This traditional characterization is unable to assess the impact of ..."
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Cited by 91 (18 self)
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Abstract—The analysis of the multipleantenna capacity in the high regime has hitherto focused on the high slope (or maximum multiplexing gain), which quantifies the multiplicative increase as a function of the number of antennas. This traditional characterization is unable to assess the impact of prominent channel features since, for a majority of channels, the slope equals the minimum of the number of transmit and receive antennas. Furthermore, a characterization based solely on the slope captures only the scaling but it has no notion of the power required for a certain capacity. This paper advocates a more refined characterization whereby, as a function of �f, the high capacity is expanded as an affine function where the impact of channel features such as antenna correlation, unfaded components, etc., resides in the zeroorder term or power offset. The power offset, for which we find insightful closedform expressions, is shown to play a chief role for levels of practical interest. Index Terms—Antenna correlation, channel capacity, coherent communication, fading channels, high analysis, multiantenna arrays, Ricean channels.
Capacity of MIMO systems with semicorrelated flat fading
 IEEE Trans. on Info. Theory
, 2003
"... Abstract—The primary contribution of this work lies in the derivation of the exact characteristic function (and hence, the mean and variance) of the capacity of multipleinput multipleoutput (MIMO) systems for semicorrelated flatfading channels. A Gaussian approximation to the exact capacity resu ..."
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Cited by 70 (10 self)
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Abstract—The primary contribution of this work lies in the derivation of the exact characteristic function (and hence, the mean and variance) of the capacity of multipleinput multipleoutput (MIMO) systems for semicorrelated flatfading channels. A Gaussian approximation to the exact capacity results is suggested and evaluated for its accuracy. We show that over a range of correlation levels this approximation is adequate even for moderate numbers of transmit and receive antennas. Index Terms—Multipleinput multipleoutput (MIMO) systems, Shannon capacity, spatial correlation. I.
On the capacity of doubly correlated MIMO channels
 IEEE Trans. on Wireless Comm
, 2006
"... Abstract — In this paper, we analyze the capacity of multipleinput multipleoutput (MIMO) Rayleighfading channels in the presence of spatial fading correlation at both the transmitter and the receiver, assuming the channel is unknown at the transmitter and perfectly known at the receiver. We first ..."
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Cited by 25 (8 self)
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Abstract — In this paper, we analyze the capacity of multipleinput multipleoutput (MIMO) Rayleighfading channels in the presence of spatial fading correlation at both the transmitter and the receiver, assuming the channel is unknown at the transmitter and perfectly known at the receiver. We first derive the determinant representation for the exact characteristic function of the capacity, which is then used to determine the trace representations for the mean, variance, skewness, kurtosis, and other higherorder statistics (HOS). These results allow us to exactly evaluate two relevant informationtheoretic capacity measures—ergodic capacity and outage capacity—and the HOS of the capacity for such a MIMO channel. The analytical framework presented in the paper is valid for arbitrary numbers of antennas, and generalizes the previously known results for independent and identically distributed or onesided correlated MIMO channels to the case when fading correlation exists on both sides. We verify our analytical results by comparing them with Monte Carlo simulations for a correlation model based on realistic channel measurements as well as a classical exponential correlation model. Index Terms — Channel capacity, higherorder statistics (HOS), multipleinput multipleoutput (MIMO) system, Rayleigh fading, spatial fading correlation. I.
On the condition number distribution of complex wishart matrices
, 2010
"... Abstract—This paper investigates the distribution of the condition number of complex Wishart matrices. Two closely related measures are considered: the standard condition number (SCN) and the Demmel condition number (DCN), both of which have important applications in the context of multipleinput m ..."
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Cited by 20 (1 self)
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Abstract—This paper investigates the distribution of the condition number of complex Wishart matrices. Two closely related measures are considered: the standard condition number (SCN) and the Demmel condition number (DCN), both of which have important applications in the context of multipleinput multipleoutput (MIMO) communication systems, as well as in various branches of mathematics. We first present a novel generic framework for the SCN distribution which accounts for both central and noncentral Wishart matrices of arbitrary dimension. This result is a simple unified expression which involves only a single scalar integral, and therefore allows for fast and efficient computation. For the case of dual Wishart matrices, we derive new exact polynomial expressions for both the SCN and DCN distributions. We also formulate a new closedform expression for the tail SCN distribution which applies for correlated central Wishart matrices of arbitrary dimension and demonstrates an interesting connection to the maximum eigenvalue moments of Wishart matrices of smaller dimension. Based on our analytical results, we gain valuable insights into the statistical behavior of the channel conditioning for various MIMO fading scenarios, such as uncorrelated/semicorrelated Rayleigh fading and Ricean fading. Index Terms—MIMO systems, complex Wishart matrices, condition number, joint eigenvalue distribution.
MIMO networks: the effect of interference
 IEEE Trans. Inf. Theory
, 2009
"... Abstract—Multipleinput multipleoutput (MIMO) systems are being considered as one of the key enabling technologies for future wireless networks. However, the decrease in capacity due to the presence of interferers in MIMO networks is not well understood. In this paper, we develop an analytical fram ..."
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Cited by 20 (2 self)
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Abstract—Multipleinput multipleoutput (MIMO) systems are being considered as one of the key enabling technologies for future wireless networks. However, the decrease in capacity due to the presence of interferers in MIMO networks is not well understood. In this paper, we develop an analytical framework to characterize the capacity of MIMO communication systems in the presence of multiple MIMO cochannel interferers and noise. We consider the situation in which transmitters have no channel state information, and all links undergo Rayleigh fading. We first generalize the determinant representation of hypergeometric functions with matrix arguments to the case when the argument matrices have eigenvalues of arbitrary multiplicity. This enables the derivation of the distribution of the eigenvalues of Gaussian quadratic forms and Wishart matrices with arbitrary correlation, with application to both singleuser and multiuser MIMO systems. In particular, we derive the ergodic mutual information for MIMO systems in the presence of multiple MIMO interferers. Our analysis is valid for any number of interferers, each with arbitrary number of antennas having possibly unequal power levels. This framework, therefore, accommodates the study of distributed MIMO systems and accounts for different spatial positions of the MIMO interferers. Index Terms—Eigenvalues distribution, Gaussian quadratic forms, hypergeometric functions of matrix arguments, interference, multipleinput multipleoutput (MIMO), Wishart matrices. I.
Exact capacity distributions for MIMO systems with small numbers of antennas
 IEEE Commun. Lett
, 2003
"... Abstract—It is well known that multiple input multiple output (MIMO) systems offer the promise of achieving very high spectrum efficiencies (many tens of bit/s/Hz) in a mobile environment. The gains in MIMO capacity are sensitive to the presence of spatial correlation introduced by the radio environ ..."
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Cited by 15 (3 self)
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Abstract—It is well known that multiple input multiple output (MIMO) systems offer the promise of achieving very high spectrum efficiencies (many tens of bit/s/Hz) in a mobile environment. The gains in MIMO capacity are sensitive to the presence of spatial correlation introduced by the radio environment. In this letter we consider the capacity outage performance of MIMO systems in correlated environments. For systems with large numbers of antennas Gaussian approximations are very accurate. Hence, we concentrate on systems with small numbers of antennas and derive exact densities and distribution functions for the capacity, which are simple and rapid to compute. Index Terms—Information rates, MIMO systems, wireless channel models. I.
Capacity of MIMO channels with onesided correlation
 in Proc. IEEE ISSSTA’2004
, 2004
"... Abstract — We present closedform expressions for the marginal density distribution of the unordered eigenvalues of HΦH † where Φ is an input covariance and H is a matrix representing a MIMO (multiinput multioutput) Rayleighfaded channel with onesided correlation at either end of the link, trans ..."
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Cited by 13 (4 self)
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Abstract — We present closedform expressions for the marginal density distribution of the unordered eigenvalues of HΦH † where Φ is an input covariance and H is a matrix representing a MIMO (multiinput multioutput) Rayleighfaded channel with onesided correlation at either end of the link, transmitter or receiver, with no constraints on the numbers of antennas therein. Using the foregoing distribution, we then derive analytical expressions for the capacity. The expressions found are evaluated through several examples conducted with correlation structures of practical interest. I.
Diversitymultiplexing tradeoff of double scattering MIMO channels
 IEEE Trans. Inf. Theory
, 2011
"... ..."
Spacetime power schedule for distributed MIMO links without instantaneous channel state information at the transmitting nodes
 IEEE Trans. Signal Processing
, 2008
"... A spacetime optimal power schedule for multiple distributed MIMO links without the knowledge of channel state information at transmitting nodes is proposed. This new approach exploits both the spatial and temporal freedoms of distributed MIMO links. A readily computable expression for the ergodic s ..."
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Cited by 6 (5 self)
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A spacetime optimal power schedule for multiple distributed MIMO links without the knowledge of channel state information at transmitting nodes is proposed. This new approach exploits both the spatial and temporal freedoms of distributed MIMO links. A readily computable expression for the ergodic sum capacity of the MIMO links is derived. Based on this expression, a projected gradient algorithm is developed to optimize the power allocation. For a symmetric set of MIMO links, it is observed that the spacetime optimal power schedule reduces to a uniform isotropic power schedule when nominal interference is low, or to an orthogonal isotropic power schedule when nominal interference is high. Furthermore, the transition region between the latter two schedules is seen to be very small in terms of nominal interferencetonoise ratio. Index Terms — MIMO systems, spacetime power schedule, wireless mesh networks. 1.