Convex Optimization
Robust downlink power control in wireless cellular systems
EURASIP Journal on Wireless Communications and Networking - Special issue on multiuser MIMO networks
Tractable Approximations to Robust Conic Optimization Problems
Mathematical Programming: Series A and B
Convex Approximations of Chance Constrained Programs
SIAM Journal on Optimization
Design of Fair Multi-user Transceivers with QoS and Imperfect CSI
CNSR '08 Proceedings of the Communication Networks and Services Research Conference
On Safe Tractable Approximations of Chance-Constrained Linear Matrix Inequalities
Mathematics of Operations Research
Linear precoding via conic optimization for fixed MIMO receivers
IEEE Transactions on Signal Processing
Multiple Antenna Broadcast Channels With Shape Feedback and Limited Feedback
IEEE Transactions on Signal Processing - Part I
Robust Downlink Beamforming Based on Outage Probability Specifications
IEEE Transactions on Wireless Communications
MIMO Broadcast Channels With Finite-Rate Feedback
IEEE Transactions on Information Theory
Transmit beamforming and power control for cellular wireless systems
IEEE Journal on Selected Areas in Communications
IEEE Journal on Selected Areas in Communications
On the Design of Linear Transceivers for Multiuser Systems with Channel Uncertainty
IEEE Journal on Selected Areas in Communications
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We consider a broadcast channel (BC) in which the base station is equipped with multiple antennas and each user has a single antenna. We study the design of systems with linear precoders and probabilistically-constrained Quality of Service (QoS) requirements for each user, in scenarios with imperfect channel state information (CSI) at the transmitter. Each user's QoS is expressed as an upper bound on the outage probability of the received signal-to-interference-plus-noise ratio. Given a total power constraint on the transmitter, we consider the design of a linear precoder so as to maximize the minimum QoS requirement of all users. We propose stochastic models for the uncertainty in the CSI of each user that are suitable for uncertainties resulting from estimation errors, and those resulting from quantization errors in systems with quantized feedback of the CSI. We formulate the design problem as a chance constrained optimization problem, and we adopt a conservative approach that yields deterministic quasi-convex formulations that are efficiently-solvable. Our simulations indicate that the proposed methods can significantly increase the minimum QoS of all users when the QoS requirements are formulated as outage constraints.