266 research outputs found
A Rate-Splitting Approach To Robust Multiuser MISO Transmission
For multiuser MISO systems with bounded uncertainties in the Channel State
Information (CSI), we consider two classical robust design problems: maximizing
the minimum rate subject to a transmit power constraint, and power minimization
under a rate constraint. Contrary to conventional strategies, we propose a
Rate-Splitting (RS) strategy where each message is divided into two parts, a
common part and a private part. All common parts are packed into one super
common message encoded using a shared codebook and decoded by all users, while
private parts are independently encoded and retrieved by their corresponding
users. We prove that RS-based designs achieve higher max-min Degrees of Freedom
(DoF) compared to conventional designs (NoRS) for uncertainty regions that
scale with SNR. For the special case of non-scaling uncertainty regions, RS
contrasts with NoRS and achieves a non-saturating max-min rate. In the power
minimization problem, RS is shown to combat the feasibility problem arising
from multiuser interference in NoRS. A robust design of precoders for RS is
proposed, and performance gains over NoRS are demonstrated through simulations.Comment: To appear in ICASSP 201
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
- …