6 research outputs found
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
From Spectrum Pooling to Space Pooling: Opportunistic Interference Alignment in MIMO Cognitive Networks
We describe a non-cooperative interference alignment (IA) technique which
allows an opportunistic multiple input multiple output (MIMO) link (secondary)
to harmlessly coexist with another MIMO link (primary) in the same frequency
band. Assuming perfect channel knowledge at the primary receiver and
transmitter, capacity is achieved by transmiting along the spatial directions
(SD) associated with the singular values of its channel matrix using a
water-filling power allocation (PA) scheme. Often, power limitations lead the
primary transmitter to leave some of its SD unused. Here, it is shown that the
opportunistic link can transmit its own data if it is possible to align the
interference produced on the primary link with such unused SDs. We provide both
a processing scheme to perform IA and a PA scheme which maximizes the
transmission rate of the opportunistic link. The asymptotes of the achievable
transmission rates of the opportunistic link are obtained in the regime of
large numbers of antennas. Using this result, it is shown that depending on the
signal-to-noise ratio and the number of transmit and receive antennas of the
primary and opportunistic links, both systems can achieve transmission rates of
the same order.Comment: Submitted to IEEE Trans. in Signal Processing. Revised on 23-11-0
CMI analysis and precoding designs for correlated multi-hop MIMO channels
Conditional mutual information (CMI) analysis and precoding design for generally correlated wireless multi-hop multi-input multi-output (MIMO) channels are presented in this paper. Although some particular scenarios have been examined in existing publications, this paper investigates a generally correlated transmission system having spatially correlated channel, mutually correlated source symbols, and additive colored Gaussian noise (ACGN). First, without precoding techniques, we derive the optimized source symbol covariances upon mutual information maximization. Secondly, we apply a precoding technique and then design the precoder in two cases: maximizing the mutual information and minimizing the detection error. Since the optimal design for the end-to-end system cannot be analytically obtained in closed form due to the non-monotonic nature, we relax the optimization problem and attain sub-optimal designs in closed form. Simulation results show that without precoding, the average mutual information obtained by the asymptotic design is very close to the one obtained by the optimal design, while saving a huge computational complexity. When having the proposed precoding matrices, the end-to-end mutual information significantly increases while it does not require resources of the system such as transmission power or bandwidth
Asymptotic Capacity and Optimal Precoding in MIMO Multi-Hop Relay Networks
A multi-hop relaying system is analyzed where data sent by a multi-antenna
source is relayed by successive multi-antenna relays until it reaches a
multi-antenna destination. Assuming correlated fading at each hop, each relay
receives a faded version of the signal from the previous level, performs linear
precoding and retransmits it to the next level. Using free probability theory
and assuming that the noise power at relaying levels-- but not at destination--
is negligible, the closed-form expression of the asymptotic instantaneous
end-to-end mutual information is derived as the number of antennas at all
levels grows large. The so-obtained deterministic expression is independent
from the channel realizations while depending only on channel statistics.
Moreover, it also serves as the asymptotic value of the average end-to-end
mutual information. The optimal singular vectors of the precoding matrices that
maximize the average mutual information with finite number of antennas at all
levels are also provided. It turns out that the optimal precoding singular
vectors are aligned to the eigenvectors of the channel correlation matrices.
Thus they can be determined using only the known channel statistics. As the
optimal precoding singular vectors are independent from the system size, they
are also optimal in the asymptotic regime.Comment: 45 pages, 7 figures, submitted to IEEE Transactions on Information
Theory, December 200