6,873 research outputs found
On channel estimation and optimal training design for amplify and forward relay networks
10.1109/GLOCOM.2007.763GLOBECOM - IEEE Global Telecommunications Conference4015-401
How to Understand LMMSE Transceiver Design for MIMO Systems From Quadratic Matrix Programming
In this paper, a unified linear minimum mean-square-error (LMMSE) transceiver
design framework is investigated, which is suitable for a wide range of
wireless systems. The unified design is based on an elegant and powerful
mathematical programming technology termed as quadratic matrix programming
(QMP). Based on QMP it can be observed that for different wireless systems,
there are certain common characteristics which can be exploited to design LMMSE
transceivers e.g., the quadratic forms. It is also discovered that evolving
from a point-to-point MIMO system to various advanced wireless systems such as
multi-cell coordinated systems, multi-user MIMO systems, MIMO cognitive radio
systems, amplify-and-forward MIMO relaying systems and so on, the quadratic
nature is always kept and the LMMSE transceiver designs can always be carried
out via iteratively solving a number of QMP problems. A comprehensive framework
on how to solve QMP problems is also given. The work presented in this paper is
likely to be the first shoot for the transceiver design for the future
ever-changing wireless systems.Comment: 31 pages, 4 figures, Accepted by IET Communication
Distributed Space-Time Coding Based on Adjustable Code Matrices for Cooperative MIMO Relaying Systems
An adaptive distributed space-time coding (DSTC) scheme is proposed for
two-hop cooperative MIMO networks. Linear minimum mean square error (MMSE)
receive filters and adjustable code matrices are considered subject to a power
constraint with an amplify-and-forward (AF) cooperation strategy. In the
proposed adaptive DSTC scheme, an adjustable code matrix obtained by a feedback
channel is employed to transform the space-time coded matrix at the relay node.
The effects of the limited feedback and the feedback errors are assessed.
Linear MMSE expressions are devised to compute the parameters of the adjustable
code matrix and the linear receive filters. Stochastic gradient (SG) and
least-squares (LS) algorithms are also developed with reduced computational
complexity. An upper bound on the pairwise error probability analysis is
derived and indicates the advantage of employing the adjustable code matrices
at the relay nodes. An alternative optimization algorithm for the adaptive DSTC
scheme is also derived in order to eliminate the need for the feedback. The
algorithm provides a fully distributed scheme for the adaptive DSTC at the
relay node based on the minimization of the error probability. Simulation
results show that the proposed algorithms obtain significant performance gains
as compared to existing DSTC schemes.Comment: 6 figure
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