564 research outputs found
Capacity and Power Scaling Laws for Finite Antenna MIMO Amplify-and-Forward Relay Networks
In this paper, we present a novel framework that can be used to study the
capacity and power scaling properties of linear multiple-input multiple-output
(MIMO) antenna amplify-and-forward (AF) relay networks. In
particular, we model these networks as random dynamical systems (RDS) and
calculate their Lyapunov exponents. Our analysis can be applied to systems
with any per-hop channel fading distribution, although in this contribution we
focus on Rayleigh fading. Our main results are twofold: 1) the total transmit
power at the th node will follow a deterministic trajectory through the
network governed by the network's maximum Lyapunov exponent, 2) the capacity of
the th eigenchannel at the th node will follow a deterministic trajectory
through the network governed by the network's th Lyapunov exponent. Before
concluding, we concentrate on some applications of our results. In particular,
we show how the Lyapunov exponents are intimately related to the rate at which
the eigenchannel capacities diverge from each other, and how this relates to
the amplification strategy and number of antennas at each relay. We also use
them to determine the extra cost in power associated with each extra
multiplexed data stream.Comment: 16 pages, 9 figures. Accepted for publication in IEEE Transactions on
Information Theor
Crystallization in large wireless networks
We analyze fading interference relay networks where M single-antenna
source-destination terminal pairs communicate concurrently and in the same
frequency band through a set of K single-antenna relays using half-duplex
two-hop relaying. Assuming that the relays have channel state information
(CSI), it is shown that in the large-M limit, provided K grows fast enough as a
function of M, the network "decouples" in the sense that the individual
source-destination terminal pair capacities are strictly positive. The
corresponding required rate of growth of K as a function of M is found to be
sufficient to also make the individual source-destination fading links converge
to nonfading links. We say that the network "crystallizes" as it breaks up into
a set of effectively isolated "wires in the air". A large-deviations analysis
is performed to characterize the "crystallization" rate, i.e., the rate (as a
function of M,K) at which the decoupled links converge to nonfading links. In
the course of this analysis, we develop a new technique for characterizing the
large-deviations behavior of certain sums of dependent random variables. For
the case of no CSI at the relay level, assuming amplify-and-forward relaying,
we compute the per source-destination terminal pair capacity for M,K converging
to infinity, with K/M staying fixed, using tools from large random matrix
theory.Comment: 30 pages, 6 figures, submitted to journal IEEE Transactions on
Information Theor
Asymptotic Capacity and Optimal Precoding Strategy of Multi-Level Precode & Forward in Correlated Channels
We analyze a multi-level MIMO relaying system where a multiple-antenna
transmitter sends data to a multipleantenna receiver through several relay
levels, also equipped with multiple antennas. Assuming correlated fading in
each hop, each relay receives a faded version of the signal transmitted by the
previous level, performs precoding on the received signal and retransmits it to
the next level. Using free probability theory and assuming that the noise power
at the relay levels - but not at the receiver - is negligible, a closed-form
expression of the end-to-end asymptotic instantaneous mutual information is
derived as the number of antennas in all levels grow large with the same rate.
This asymptotic expression is shown to be independent from the channel
realizations, to only depend on the channel statistics and to also serve as the
asymptotic value of the end-to-end average mutual information. We also provide
the optimal singular vectors of the precoding matrices that maximize the
asymptotic mutual information : the optimal transmit directions represented by
the singular vectors of the precoding matrices are aligned on the eigenvectors
of the channel correlation matrices, therefore they can be determined only
using the known statistics of the channel matrices and do not depend on a
particular channel realization.Comment: 5 pages, 3 figures, to be published in proceedings of IEEE
Information Theory Workshop 200
- …