15 research outputs found
Delay Constrained Throughput Analysis of a Correlated MIMO Wireless Channel
The maximum traffic arrival rate at the network for a given delay guarantee
(delay constrained throughput) has been well studied for wired channels.
However, few results are available for wireless channels, especially when
multiple antennas are employed at the transmitter and receiver. In this work,
we analyze the network delay constrained throughput of a multiple input
multiple output (MIMO) wireless channel with time-varying spatial correlation.
The MIMO channel is modeled via its virtual representation, where the
individual spatial paths between the antenna pairs are Gilbert-Elliot channels.
The whole system is then described by a K-State Markov chain, where K depends
upon the degree of freedom (DOF) of the channel. We prove that the DOF based
modeling is indeed accurate. Furthermore, we study the impact of the delay
requirements at the network layer, violation probability and the number of
antennas on the throughput under different fading speeds and signal strength.Comment: Submitted to ICCCN 2011, 8 pages, 5 figure
Why Does a Kronecker Model Result in Misleading Capacity Estimates?
Many recent works that study the performance of multi-input multi-output
(MIMO) systems in practice assume a Kronecker model where the variances of the
channel entries, upon decomposition on to the transmit and the receive
eigen-bases, admit a separable form. Measurement campaigns, however, show that
the Kronecker model results in poor estimates for capacity. Motivated by these
observations, a channel model that does not impose a separable structure has
been recently proposed and shown to fit the capacity of measured channels
better. In this work, we show that this recently proposed modeling framework
can be viewed as a natural consequence of channel decomposition on to its
canonical coordinates, the transmit and/or the receive eigen-bases. Using tools
from random matrix theory, we then establish the theoretical basis behind the
Kronecker mismatch at the low- and the high-SNR extremes: 1) Sparsity of the
dominant statistical degrees of freedom (DoF) in the true channel at the
low-SNR extreme, and 2) Non-regularity of the sparsity structure (disparities
in the distribution of the DoF across the rows and the columns) at the high-SNR
extreme.Comment: 39 pages, 5 figures, under review with IEEE Trans. Inform. Theor