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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 59 (13 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.
The capacity of a MIMO Ricean channel is monotonic in the singular values of the mean
 in Proceedings of the 5th International ITG Conference on Source and Channel Coding (SCC
, 2004
"... We consider a discretetime memoryless MultipleInput MultipleOutput (MIMO) fading channel where the fading matrix can be written as the sum of a deterministic (lineofsight) matrix D and a random matrix ˜ H whose entries are IID zeromean unitvariance complex circularlysymmetric Gaussian random ..."
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Cited by 26 (4 self)
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We consider a discretetime memoryless MultipleInput MultipleOutput (MIMO) fading channel where the fading matrix can be written as the sum of a deterministic (lineofsight) matrix D and a random matrix ˜ H whose entries are IID zeromean unitvariance complex circularlysymmetric Gaussian random variables. It is demonstrated that if the realization of the fading matrix is known at the receiver but not at the transmitter, then the capacity of this channel under an average power constraint is monotonically nondecreasing in the singular values of D. This complements a recent result of Kim and Lapidoth [1] demonstrating the monotonicity of the mutual information corresponding to isotropically distributed Gaussian input vectors. We also show that the optimal covariance matrix of the Gaussian input vector has the same eigenvectors as D † D. 1
Optimal transmit covariance for MIMO channels with statistical transmitter side informaiton
 in IEEE Int. Symp. on Inform. Theory, ISIT’05
, 2005
"... Information ..."
On the capacity of MIMO Rice channels
 in Proceedings of the 42nd Allerton Conference
, 2004
"... The asymptotic in the number of antennas theoretic capacity of a MIMO (Multiple Input Multiple Output) system is derived when considering Rice distribution entries. Assuming perfect knowledge of the channel at the receiver, analytical expressions of the capacity are derived in the case of per ..."
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Cited by 8 (2 self)
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The asymptotic in the number of antennas theoretic capacity of a MIMO (Multiple Input Multiple Output) system is derived when considering Rice distribution entries. Assuming perfect knowledge of the channel at the receiver, analytical expressions of the capacity are derived in the case of perfect and partial (based on the mean and limiting eigenvalue distribution of the mean) knowledge at the transmitter. Remarkably, the capacity depends only on a few meaningful parameters, namely, the limiting eigenvalue distribution of the mean matrix, the signal to noise ratio (SNR), the Ricean factor, and the system load. These results show in particular that, for a given SNR and in contrast to the SISO (Single Input Single Output) case, the MIMO Rice channel does not always outperform the MIMO Rayleigh channel in terms of capacity. Moreover, the results are also useful to quantify the effect of feedback on general MIMO systems.
Mutual information and eigenvalue distribution of MIMO Ricean channels
 in Proc. Int. Symp. Information Theory and Its Applications (ISITA’04
, 2004
"... This paper presents an explicit expression for the marginal probability density distribution of the unordered eigenvalues of a noncentral Wishart matrix HH † where H can represent a multipleinput multipleoutput channel obeying the Ricean law. By integrating over this marginal density distribution, ..."
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Cited by 6 (3 self)
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This paper presents an explicit expression for the marginal probability density distribution of the unordered eigenvalues of a noncentral Wishart matrix HH † where H can represent a multipleinput multipleoutput channel obeying the Ricean law. By integrating over this marginal density distribution, the corresponding ergodic mutual information is characterized also in explicit form. 1.
A geometrical investigation of the rank1 ricean mimo channel at high snr
 in IEEE Int. Symp. on Info. Theo. (ISIT
, 2004
"... We investigate the highSNR probability density function of the mutual information of the Ricean MIMO channel for Gaussian code books and the case where the channel’s fixed component has rank 1. The purpose of this paper is threefold: 1) We propose an illustrative geometrical technique characterizi ..."
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Cited by 4 (0 self)
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We investigate the highSNR probability density function of the mutual information of the Ricean MIMO channel for Gaussian code books and the case where the channel’s fixed component has rank 1. The purpose of this paper is threefold: 1) We propose an illustrative geometrical technique characterizing the mutual information as the log of the random volume of a parallelotope spanned by the random MIMO channel matrix. 2) We then show that the density function of the rank1 Ricean MIMO channel approaches a noncentral Gaussian density in the large antenna limit. We provide expressions for the density function in the finite antenna case which shed light on the question why the mutual information has Gaussian behavior both in the Rayleigh and the Ricean case even for a small number of antennas. 3) Finally, we provide accurate approximations to the mean and the variance of the mutual information of the rank1Ricean MIMO channel which allows a thorough discussion of the impact of the Kfactor on capacity. I.
Optimal Transmit Covariance for Ergodic MIMO Channels
, 2005
"... In this paper we consider the computation of channel capacity for ergodic multipleinput multipleoutput channels with additive white Gaussian noise. Two scenarios are considered. Firstly, a timevarying channel is considered in which both the transmitter and the receiver have knowledge of the chann ..."
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Cited by 2 (1 self)
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In this paper we consider the computation of channel capacity for ergodic multipleinput multipleoutput channels with additive white Gaussian noise. Two scenarios are considered. Firstly, a timevarying channel is considered in which both the transmitter and the receiver have knowledge of the channel realization. The optimal transmission strategy is waterfilling over space and time. It is shown that this may be achieved in a causal, indeed instantaneous fashion. In the second scenario, only the receiver has perfect knowledge of the channel realization, while the transmitter has knowledge of the channel gain probability law. In this case we determine an optimality condition on the input covariance for ergodic Gaussian vector channels with arbitrary channel distribution under the condition that the channel gains are independent of the transmit signal. Using this optimality condition, we find an iterative algorithm for numerical computation of optimal input covariance matrices. Applications to correlated Rayleigh and Ricean channels are given. I.
Monotonicity Results for Coherent MIMO Ricean Channels
, 2004
"... A preorder on the lineofsight (LOS) matrices in coherent multipleinput multipleoutput (MIMO) Ricean fading channels is introduced. It is demonstrated that under this preorder, the information rate corresponding to zeromean multivariate circularly symmetric Gaussian inputs of arbitrary covariance ..."
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Cited by 1 (1 self)
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A preorder on the lineofsight (LOS) matrices in coherent multipleinput multipleoutput (MIMO) Ricean fading channels is introduced. It is demonstrated that under this preorder, the information rate corresponding to zeromean multivariate circularly symmetric Gaussian inputs of arbitrary covariance matrices is monotonic in the LOS matrix. This result implies the monotonicity of the information rates corresponding to isotropic Gaussian inputs and of channel capacity in the singular values of the LOS matrix. It is particularly useful in scenarios such as MIMO Ricean multiaccess channels, where the achievable rates depend on the LOS matrices of the different users and cannot be determined based on their corresponding singular values alone. 1
Monotonicity Results for Coherent SingleUser and MultipleAccess MIMO Rician Channels
"... Abstract — We introduce a preorder on the lineofsight (LOS) matrices in coherent multipleinput multipleoutput (MIMO) Rician fading channels. We demonstrate that under this preorder, the information rate and the rateR outage probability corresponding to zeromean multivariate circularly symmetri ..."
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Abstract — We introduce a preorder on the lineofsight (LOS) matrices in coherent multipleinput multipleoutput (MIMO) Rician fading channels. We demonstrate that under this preorder, the information rate and the rateR outage probability corresponding to zeromean multivariate circularly symmetric Gaussian inputs of arbitrary but fixed covariance matrices are monotonic in the LOS matrix. This result extends previous results obtained by Kim & Lapidoth, ISIT, 2003, and Hösli & Lapidoth, ITG Conference on SCC, 2004, i.e., our result implies the monotonicity of the information rates corresponding to isotropic Gaussian inputs and of channel capacity in the singular values of the LOS matrix. It is particularly useful in scenarios such as MIMO Rician multipleaccess channels, where the achievable rates depend on the LOS matrices of the different users and cannot be determined based on their corresponding singular values alone. We also prove a converse to the main result. That is, given two different LOS matrices, we show that if for all zeromean multivariate circularly symmetric Gaussian inputs the induced mutual information over one channel is at least as large as over the other channel, then the two LOS matrices can be ordered. I.