1,411 research outputs found
Robust Sum MSE Optimization for Downlink Multiuser MIMO Systems with Arbitrary Power Constraint: Generalized Duality Approach
This paper considers linear minimum meansquare- error (MMSE) transceiver
design problems for downlink multiuser multiple-input multiple-output (MIMO)
systems where imperfect channel state information is available at the base
station (BS) and mobile stations (MSs). We examine robust sum mean-square-error
(MSE) minimization problems. The problems are examined for the generalized
scenario where the power constraint is per BS, per BS antenna, per user or per
symbol, and the noise vector of each MS is a zero-mean circularly symmetric
complex Gaussian random variable with arbitrary covariance matrix. For each of
these problems, we propose a novel duality based iterative solution. Each of
these problems is solved as follows. First, we establish a novel sum average
meansquare- error (AMSE) duality. Second, we formulate the power allocation
part of the problem in the downlink channel as a Geometric Program (GP). Third,
using the duality result and the solution of GP, we utilize alternating
optimization technique to solve the original downlink problem. To solve robust
sum MSE minimization constrained with per BS antenna and per BS power problems,
we have established novel downlink-uplink duality. On the other hand, to solve
robust sum MSE minimization constrained with per user and per symbol power
problems, we have established novel downlink-interference duality. For the
total BS power constrained robust sum MSE minimization problem, the current
duality is established by modifying the constraint function of the dual uplink
channel problem. And, for the robust sum MSE minimization with per BS antenna
and per user (symbol) power constraint problems, our duality are established by
formulating the noise covariance matrices of the uplink and interference
channels as fixed point functions, respectively.Comment: IEEE TSP Journa
Linear Transceiver design for Downlink Multiuser MIMO Systems: Downlink-Interference Duality Approach
This paper considers linear transceiver design for downlink multiuser
multiple-input multiple-output (MIMO) systems. We examine different transceiver
design problems. We focus on two groups of design problems. The first group is
the weighted sum mean-square-error (WSMSE) (i.e., symbol-wise or user-wise
WSMSE) minimization problems and the second group is the minimization of the
maximum weighted mean-squareerror (WMSE) (symbol-wise or user-wise WMSE)
problems. The problems are examined for the practically relevant scenario where
the power constraint is a combination of per base station (BS) antenna and per
symbol (user), and the noise vector of each mobile station is a zero-mean
circularly symmetric complex Gaussian random variable with arbitrary covariance
matrix. For each of these problems, we propose a novel downlink-interference
duality based iterative solution. Each of these problems is solved as follows.
First, we establish a new mean-square-error (MSE) downlink-interference
duality. Second, we formulate the power allocation part of the problem in the
downlink channel as a Geometric Program (GP). Third, using the duality result
and the solution of GP, we utilize alternating optimization technique to solve
the original downlink problem. For the first group of problems, we have
established symbol-wise and user-wise WSMSE downlink-interference duality.Comment: IEEE TSP Journa
Robust THP Transceiver Designs for Multiuser MIMO Downlink with Imperfect CSIT
In this paper, we present robust joint non-linear transceiver designs for
multiuser multiple-input multiple-output (MIMO) downlink in the presence of
imperfections in the channel state information at the transmitter (CSIT). The
base station (BS) is equipped with multiple transmit antennas, and each user
terminal is equipped with one or more receive antennas. The BS employs
Tomlinson-Harashima precoding (THP) for inter-user interference
pre-cancellation at the transmitter. We consider robust transceiver designs
that jointly optimize the transmit THP filters and receive filter for two
models of CSIT errors. The first model is a stochastic error (SE) model, where
the CSIT error is Gaussian-distributed. This model is applicable when the CSIT
error is dominated by channel estimation error. In this case, the proposed
robust transceiver design seeks to minimize a stochastic function of the sum
mean square error (SMSE) under a constraint on the total BS transmit power. We
propose an iterative algorithm to solve this problem. The other model we
consider is a norm-bounded error (NBE) model, where the CSIT error can be
specified by an uncertainty set. This model is applicable when the CSIT error
is dominated by quantization errors. In this case, we consider a worst-case
design. For this model, we consider robust i) minimum SMSE, ii)
MSE-constrained, and iii) MSE-balancing transceiver designs. We propose
iterative algorithms to solve these problems, wherein each iteration involves a
pair of semi-definite programs (SDP). Further, we consider an extension of the
proposed algorithm to the case with per-antenna power constraints.Comment: Accepted for publication in EURASIP Journal on Advances in Signal
Processing: Special Issue on Multiuser MIMO Transmission with Limited
Feedback, Cooperation, and Coordinatio
Transceiver design for single-cell and multi-cell downlink multiuser MIMO systems
This thesis designs linear transceivers for the down link multiple user
multiple input multiple output single-cell and multiple-cell systems. The
transceivers are designed by assuming perfect and imperfect channel state
information at the BS and mobile stations (MS). Different signal to
interference plus noise ratio, mean square error and rate-based design criteria
are considered. These design criteria are formulated by considering total BS,
per BS antenna, per user, per symbol or a combination of per BS antenna and per
user (symbol) power constraints. To solve these problems generalized down link
up link and down link interference duality approaches are proposed.
We have also shown that the weighted sum rate maximization problem can be
equivalently formulated as weighted sum mean square error minimization problem
with additional optimization variables and constraints. We also develop
distributed transceiver design algorithms to solve weighted sum rate and mean
square error optimization problems for coordinated BS systems. The distributed
transceiver design algorithms employ modify matrix fractional minimization and
Lagrangian dual decomposition methods.Comment: PhD Thesi
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