368 research outputs found
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
Robust Linear Precoder Design for Multi-cell Downlink Transmission
Coordinated information processing by the base stations of multi-cell
wireless networks enhances the overall quality of communication in the network.
Such coordinations for optimizing any desired network-wide quality of service
(QoS) necessitate the base stations to acquire and share some channel state
information (CSI). With perfect knowledge of channel states, the base stations
can adjust their transmissions for achieving a network-wise QoS optimality. In
practice, however, the CSI can be obtained only imperfectly. As a result, due
to the uncertainties involved, the network is not guaranteed to benefit from a
globally optimal QoS. Nevertheless, if the channel estimation perturbations are
confined within bounded regions, the QoS measure will also lie within a bounded
region. Therefore, by exploiting the notion of robustness in the worst-case
sense some worst-case QoS guarantees for the network can be asserted. We adopt
a popular model for noisy channel estimates that assumes that estimation noise
terms lie within known hyper-spheres. We aim to design linear transceivers that
optimize a worst-case QoS measure in downlink transmissions. In particular, we
focus on maximizing the worst-case weighted sum-rate of the network and the
minimum worst-case rate of the network. For obtaining such transceiver designs,
we offer several centralized (fully cooperative) and distributed (limited
cooperation) algorithms which entail different levels of complexity and
information exchange among the base stations.Comment: 38 Pages, 7 Figures, To appear in the IEEE Transactions on Signal
Processin
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
Multi-user spatial diversity techniques for wireless communication systems
Multiple antennas at the transmitter and receiver, formally known as multiple-input
multiple-output (MIMO) systems have the potential to either increase the data rates
through spatial multiplexing or enhance the quality of services through exploitation
of diversity. In this thesis, the problem of downlink spatial multiplexing, where a
base station (BS) serves multiple users simultaneously in the same frequency band is
addressed. Spatial multiplexing techniques have the potential to make huge saving
in the bandwidth utilization. We propose spatial diversity techniques with and without
the assumption of perfect channel state information (CSI) at the transmitter.
We start with proposing improvement to signal-to-leakage ratio (SLR) maximization
based spatial multiplexing techniques for both fiat fading and frequency selective
channels. [Continues.
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