188 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
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
A General Rate Duality of the MIMO Multiple Access Channel and the MIMO Broadcast Channel
We present a general rate duality between the multiple access channel (MAC)
and the broadcast channel (BC) which is applicable to systems with and without
nonlinear interference cancellation. Different to the state-of-the-art rate
duality with interference subtraction from Vishwanath et al., the proposed
duality is filter-based instead of covariance-based and exploits the arising
unitary degree of freedom to decorrelate every point-to-point link. Therefore,
it allows for noncooperative stream-wise decoding which reduces complexity and
latency. Moreover, the conversion from one domain to the other does not exhibit
any dependencies during its computation making it accessible to a parallel
implementation instead of a serial one. We additionally derive a rate duality
for systems with multi-antenna terminals when linear filtering without
interference (pre-)subtraction is applied and the different streams of a single
user are not treated as self-interference. Both dualities are based on a
framework already applied to a mean-square-error duality between the MAC and
the BC. Thanks to this novel rate duality, any rate-based optimization with
linear filtering in the BC can now be handled in the dual MAC where the arising
expressions lead to more efficient algorithmic solutions than in the BC due to
the alignment of the channel and precoder indices.Comment: Submitted to IEEE Globecom 2008; Fixed dimensions of channel matrix
H_k and covariance matrix Z_k, slightly modified conclusio
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