200 research outputs found
Asymptotic Mutual Information Statistics of Separately-Correlated Rician Fading MIMO Channels
Precise characterization of the mutual information of MIMO systems is
required to assess the throughput of wireless communication channels in the
presence of Rician fading and spatial correlation. Here, we present an
asymptotic approach allowing to approximate the distribution of the mutual
information as a Gaussian distribution in order to provide both the average
achievable rate and the outage probability. More precisely, the mean and
variance of the mutual information of the separatelycorrelated Rician fading
MIMO channel are derived when the number of transmit and receive antennas grows
asymptotically large and their ratio approaches a finite constant. The
derivation is based on the replica method, an asymptotic technique widely used
in theoretical physics and, more recently, in the performance analysis of
communication (CDMA and MIMO) systems. The replica method allows to analyze
very difficult system cases in a comparatively simple way though some authors
pointed out that its assumptions are not always rigorous. Being aware of this,
we underline the key assumptions made in this setting, quite similar to the
assumptions made in the technical literature using the replica method in their
asymptotic analyses. As far as concerns the convergence of the mutual
information to the Gaussian distribution, it is shown that it holds under some
mild technical conditions, which are tantamount to assuming that the spatial
correlation structure has no asymptotically dominant eigenmodes. The accuracy
of the asymptotic approach is assessed by providing a sizeable number of
numerical results. It is shown that the approximation is very accurate in a
wide variety of system settings even when the number of transmit and receive
antennas is as small as a few units.Comment: - submitted to the IEEE Transactions on Information Theory on Nov.
19, 2006 - revised and submitted to the IEEE Transactions on Information
Theory on Dec. 19, 200
A Deterministic Equivalent for the Analysis of Non-Gaussian Correlated MIMO Multiple Access Channels
Large dimensional random matrix theory (RMT) has provided an efficient
analytical tool to understand multiple-input multiple-output (MIMO) channels
and to aid the design of MIMO wireless communication systems. However, previous
studies based on large dimensional RMT rely on the assumption that the transmit
correlation matrix is diagonal or the propagation channel matrix is Gaussian.
There is an increasing interest in the channels where the transmit correlation
matrices are generally nonnegative definite and the channel entries are
non-Gaussian. This class of channel models appears in several applications in
MIMO multiple access systems, such as small cell networks (SCNs). To address
these problems, we use the generalized Lindeberg principle to show that the
Stieltjes transforms of this class of random matrices with Gaussian or
non-Gaussian independent entries coincide in the large dimensional regime. This
result permits to derive the deterministic equivalents (e.g., the Stieltjes
transform and the ergodic mutual information) for non-Gaussian MIMO channels
from the known results developed for Gaussian MIMO channels, and is of great
importance in characterizing the spectral efficiency of SCNs.Comment: This paper is the revision of the original manuscript titled "A
Deterministic Equivalent for the Analysis of Small Cell Networks". We have
revised the original manuscript and reworked on the organization to improve
the presentation as well as readabilit
On the capacity achieving covariance matrix for Rician MIMO channels: an asymptotic approach
The capacity-achieving input covariance matrices for coherent block-fading
correlated MIMO Rician channels are determined. In this case, no closed-form
expressions for the eigenvectors of the optimum input covariance matrix are
available. An approximation of the average mutual information is evaluated in
this paper in the asymptotic regime where the number of transmit and receive
antennas converge to . New results related to the accuracy of the
corresponding large system approximation are provided. An attractive
optimization algorithm of this approximation is proposed and we establish that
it yields an effective way to compute the capacity achieving covariance matrix
for the average mutual information. Finally, numerical simulation results show
that, even for a moderate number of transmit and receive antennas, the new
approach provides the same results as direct maximization approaches of the
average mutual information, while being much more computationally attractive.Comment: 56 pp. Extended version of the published article in IEEE Inf. Th.
(march 2010) with more proof
On the precoder design of flat fading MIMO systems equipped with MMSE receivers: a large system approach
This paper is devoted to the design of precoders maximizing the ergodic
mutual information (EMI) of bi-correlated flat fading MIMO systems equiped with
MMSE receivers. The channel state information and the second order statistics
of the channel are assumed available at the receiver side and at the
transmitter side respectively. As the direct maximization of the EMI needs the
use of non attractive algorithms, it is proposed to optimize an approximation
of the EMI, introduced recently, obtained when the number of transmit and
receive antennas and converge to at the same rate. It is
established that the relative error between the actual EMI and its
approximation is a term. It is shown that the left
singular eigenvectors of the optimum precoder coincide with the eigenvectors of
the transmit covariance matrix, and its singular values are solution of a
certain maximization problem. Numerical experiments show that the mutual
information provided by this precoder is close from what is obtained by
maximizing the true EMI, but that the algorithm maximizing the approximation is
much less computationally intensive.Comment: Submitted to IEEE Transactions on Information Theor
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