713 research outputs found
Wireless MIMO Switching: Weighted Sum Mean Square Error and Sum Rate Optimization
This paper addresses joint transceiver and relay design for a wireless
multiple-input-multiple-output (MIMO) switching scheme that enables data
exchange among multiple users. Here, a multi-antenna relay linearly precodes
the received (uplink) signals from multiple users before forwarding the signal
in the downlink, where the purpose of precoding is to let each user receive its
desired signal with interference from other users suppressed. The problem of
optimizing the precoder based on various design criteria is typically
non-convex and difficult to solve. The main contribution of this paper is a
unified approach to solve the weighted sum mean square error (MSE) minimization
and weighted sum rate maximization problems in MIMO switching. Specifically, an
iterative algorithm is proposed for jointly optimizing the relay's precoder and
the users' receive filters to minimize the weighted sum MSE. It is also shown
that the weighted sum rate maximization problem can be reformulated as an
iterated weighted sum MSE minimization problem and can therefore be solved
similarly to the case of weighted sum MSE minimization. With properly chosen
initial values, the proposed iterative algorithms are asymptotically optimal in
both high and low signal-to-noise ratio (SNR) regimes for MIMO switching,
either with or without self-interference cancellation (a.k.a., physical-layer
network coding). Numerical results show that the optimized MIMO switching
scheme based on the proposed algorithms significantly outperforms existing
approaches in the literature.Comment: This manuscript is under 2nd review of IEEE Transactions on
Information Theor
Hybrid Beamforming for Large Antenna Arrays with Phase Shifter Selection
This paper proposes an asymptotically optimal hybrid beamforming solution for
large antenna arrays by exploiting the properties of the singular vectors of
the channel matrix. It is shown that the elements of the channel matrix with
Rayleigh fading follow a normal distribution when large antenna arrays are
employed. The proposed beamforming algorithm is effective in both sparse and
rich propagation environments, and is applicable for both point-to-point and
multiuser scenarios. In addition, a closed-form expression and a lower-bound
for the achievable rates are derived when analog and digital phase shifters are
employed. It is shown that the performance of the hybrid beamformers using
phase shifters with more than 2-bits resolution is comparable with analog phase
shifting. A novel phase shifter selection scheme that reduces the power
consumption at the phase shifter network is proposed when the wireless channel
is modeled by Rayleigh fading. Using this selection scheme, the spectral
efficiency can be increased as the power consumption in the phase shifter
network reduces. Compared to the scenario that all of the phase shifters are in
operation, the simulation results indicate that the spectral efficiency
increases when up to 50% of phase shifters are turned off.Comment: Accepted to Transactions on Wireless Communications, 201
Large System Analysis of Linear Precoding in Correlated MISO Broadcast Channels under Limited Feedback
In this paper, we study the sum rate performance of zero-forcing (ZF) and
regularized ZF (RZF) precoding in large MISO broadcast systems under the
assumptions of imperfect channel state information at the transmitter and
per-user channel transmit correlation. Our analysis assumes that the number of
transmit antennas and the number of single-antenna users are large
while their ratio remains bounded. We derive deterministic approximations of
the empirical signal-to-interference plus noise ratio (SINR) at the receivers,
which are tight as . In the course of this derivation, the
per-user channel correlation model requires the development of a novel
deterministic equivalent of the empirical Stieltjes transform of large
dimensional random matrices with generalized variance profile. The
deterministic SINR approximations enable us to solve various practical
optimization problems. Under sum rate maximization, we derive (i) for RZF the
optimal regularization parameter, (ii) for ZF the optimal number of users,
(iii) for ZF and RZF the optimal power allocation scheme and (iv) the optimal
amount of feedback in large FDD/TDD multi-user systems. Numerical simulations
suggest that the deterministic approximations are accurate even for small
.Comment: submitted to IEEE Transactions on Information Theor
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