768 research outputs found
On the Capacity Achieving Covariance Matrix for Frequency Selective MIMO Channels Using the Asymptotic Approach
In this contribution, an algorithm for evaluating the capacity-achieving
input covariance matrices for frequency selective Rayleigh MIMO channels is
proposed. In contrast with the flat fading Rayleigh cases, no closed-form
expressions for the eigenvectors of the optimum input covariance matrix are
available. Classically, both the eigenvectors and eigenvalues are computed
numerically and the corresponding optimization algorithms remain
computationally very demanding. In this paper, it is proposed to optimize
(w.r.t. the input covariance matrix) a large system approximation of the
average mutual information derived by Moustakas and Simon. An algorithm based
on an iterative water filling scheme is proposed, and its convergence is
studied. 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.Comment: presented at ISIT 2010 Conference, Austin, Texas, June 13-18, 2010 (5
pages, 1 figure, 2 tables
Asymptotic Analysis of Double-Scattering Channels
We consider a multiple-input multiple-output (MIMO) multiple access channel
(MAC), where the channel between each transmitter and the receiver is modeled
by the doubly-scattering channel model. Based on novel techniques from random
matrix theory, we derive deterministic approximations of the mutual
information, the signal-to-noise-plus-interference-ratio (SINR) at the output
of the minimum-mean-square-error (MMSE) detector and the sum-rate with MMSE
detection which are almost surely tight in the large system limit. Moreover, we
derive the asymptotically optimal transmit covariance matrices. Our simulation
results show that the asymptotic analysis provides very close approximations
for realistic system dimensions.Comment: 5 pages, 2 figures, submitted to the Annual Asilomar Conference on
Signals, Systems, and Computers, Pacific Grove, CA, USA, 201
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