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69
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 100 (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.
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 Outage Capacity of Correlated MultiplePath MIMO Channels
, 2005
"... The use of multiantenna arrays in both transmission and reception has been shown to dramatically increase the throughput of wireless communication systems. As a result there has been considerable interest in characterizing the ergodic average of the mutual information for realistic correlated chan ..."
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Cited by 25 (1 self)
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The use of multiantenna arrays in both transmission and reception has been shown to dramatically increase the throughput of wireless communication systems. As a result there has been considerable interest in characterizing the ergodic average of the mutual information for realistic correlated channels. Here, an approach is presented that provides analytic expressions not only for the average, but also the higher cumulant moments of the distribution of the mutual information for zeromean Gaussian MIMO channels with the most general multipath covariance matrices when the channel is known at the receiver. These channels include multitap delay paths, as well as general channels with covariance matrices that cannot be written as a Kronecker product, such as dualpolarized antenna arrays with general correlations at both transmitter and receiver ends. The mathematical methods are formally valid for large antenna numbers, in which limit it is shown that all higher cumulant moments of the distribution, other than the first two scale to zero. Thus, it is confirmed that the distribution of the mutual information tends to a Gaussian, which enables one to calculate the outage capacity. These results are quite accurate even in the case of a few antennas, which makes this approach applicable to realistic situations.
Multiantenna capacity of sparse multipath channels
 IEEE TRANS. INFORM. THEORY
, 2006
"... Existing results on multiinput multioutput (MIMO) channel capacity implicitly assume a rich scattering environment in which the channel power scales quadratically with the number of antennas, resulting in linear capacity scaling with the number of antennas. While this assumption may be justified ..."
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Cited by 23 (6 self)
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Existing results on multiinput multioutput (MIMO) channel capacity implicitly assume a rich scattering environment in which the channel power scales quadratically with the number of antennas, resulting in linear capacity scaling with the number of antennas. While this assumption may be justified in systems with few antennas, it leads to violation of fundamental power conservation principles in the limit of large number of antennas. Furthermore, recent measurement results have shown that physical MIMO channels exhibit a sparse multipath structure, even for relatively few antenna dimensions. Motivated by these observations, we propose a framework for modeling sparse channels and study the coherent capacity of sparse MIMO channels from two perspectives: 1) capacity scaling with the number of antennas, and 2) capacity as a function of transmit SNR for a fixed number of antennas. The statistically independent degrees of freedom (DoF) in sparse channels are less than the number of signalspace dimensions and, as a result, sparse channels afford a fundamental new degree of freedom over which channel capacity can be optimized: the distribution of the DoF’s in the available signalspace dimensions. Our investigation is based on a family of sparse channel configurations whose capacity admits a simple and intuitive closedform approximation and reveals a new tradeoff between the multiplexing gain and the received SNR. We identify an ideal channel
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.
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 19 (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.
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 12 (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.
Achievable Sum Rate of MIMO MMSE Receivers: A General Analytic Framework 1
, 903
"... This paper investigates the achievable sum rate of multipleinput multipleoutput (MIMO) wireless systems employing linear minimum meansquared error (MMSE) receivers. We present a new analytic framework which unveils an interesting connection between the achievable sum rate with MMSE receivers and ..."
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Cited by 12 (0 self)
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This paper investigates the achievable sum rate of multipleinput multipleoutput (MIMO) wireless systems employing linear minimum meansquared error (MMSE) receivers. We present a new analytic framework which unveils an interesting connection between the achievable sum rate with MMSE receivers and the ergodic mutual information achieved with optimal receivers. This simple but powerful result enables the vast prior literature on ergodic MIMO mutual information to be directly applied to the analysis of MMSE receivers. The framework is particularized to various Rayleigh and Rician channel scenarios to yield new exact closedform expressions for the achievable sum rate, as well as simplified expressions in the asymptotic regimes of high and low signal to noise ratios. These expressions lead to the discovery of key insights into the performance of MIMO MMSE receivers under practical channel conditions.
Generic procedure for tightly bounding the capacity of MIMO correlated Rician fading channels
 IEEE Trans. Commun
, 2005
"... Abstract—No systematic procedure for tightly bounding the average capacity of multipleinput–multipleoutput (MIMO) correlated Rician fading channels is available in the literature. In addition to the involvement of a highly nonlinear logdeterminant operator in the conditional capacity expression, ..."
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Cited by 10 (0 self)
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Abstract—No systematic procedure for tightly bounding the average capacity of multipleinput–multipleoutput (MIMO) correlated Rician fading channels is available in the literature. In addition to the involvement of a highly nonlinear logdeterminant operator in the conditional capacity expression, the difficulty arises from the complicated noncentral Wishart distribution of channel sample matrix. In this paper, we tackle the problem with arbitrary antenna correlation existing either at the transmitter or at the receiver, but allowing for the numbers of the transmit and receive antennas to be arbitrary. By introducing an exact determinant expansion and by finding an explicit expression for the general moment of the determinant of the channel sample matrix, we obtain a general upper bound for the average channel capacity. To obtain a general lower bound, we construct and prove a multivariate convex function with each of its variables being the logdeterminant function of a complex noncentral Wishartdistributed matrix. We further show that the general bounds so obtained can be simplified to explicit expressions for Rician fading channels with arbitrary semicorrelation and a mean matrix of rank one. The new results are simple, easy to be used, and superior in tightness as evidenced by intensive numerical examples. Index Terms—Channel capacity, correlated Rician fading multipleinput–multipleoutput (MIMO) channels, lower bound, upper bound. I.
Asymptotic Outage Capacity of Multiantenna Channels
 2005 IEEE Int. Conf. Acoustics, Speech and Signal Processing
, 2005
"... This paper characterizes the asymptotic distribution of the inputoutput mutual information of multiantenna channels. Using recent results on random matrix theory, we prove asymptotic normality of the unnormalized mutual information for arbitrary signaltonoise ratios and fading distributions, allo ..."
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Cited by 9 (0 self)
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This paper characterizes the asymptotic distribution of the inputoutput mutual information of multiantenna channels. Using recent results on random matrix theory, we prove asymptotic normality of the unnormalized mutual information for arbitrary signaltonoise ratios and fading distributions, allowing for correlation between the antennas at either transmitter or receiver. 1.