Fundamentals of statistical signal processing: estimation theory
Fundamentals of statistical signal processing: estimation theory
An efficient square-root algorithm for BLAST
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 02
Estimation of continuous flat fading MIMO channels
IEEE Transactions on Wireless Communications
Capacity regions for wireless ad hoc networks
IEEE Transactions on Wireless Communications
Convergence of proportional-fair sharing algorithms under general conditions
IEEE Transactions on Wireless Communications
Opportunistic beamforming using dumb antennas
IEEE Transactions on Information Theory
How much training is needed in multiple-antenna wireless links?
IEEE Transactions on Information Theory
On the capacity of MIMO broadcast channels with partial side information
IEEE Transactions on Information Theory
The Capacity Region of the Gaussian Multiple-Input Multiple-Output Broadcast Channel
IEEE Transactions on Information Theory
Adaptive clustering for mobile wireless networks
IEEE Journal on Selected Areas in Communications
IEEE Journal on Selected Areas in Communications
Opportunistic transmission scheduling with resource-sharing constraints in wireless networks
IEEE Journal on Selected Areas in Communications
Downlink capacity evaluation of cellular networks with known-interference cancellation
IEEE Journal on Selected Areas in Communications
On the optimality of multiantenna broadcast scheduling using zero-forcing beamforming
IEEE Journal on Selected Areas in Communications
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In this paper, we consider a time-slotted MIMO point-to-multipoint network, which, for example, could represent either a cellular downlink, or a cluster in a wireless mesh network. The transmitter sends an independent data stream from each transmit antenna to communicate simultaneously to a subset of the receivers in each slot. The transmitter sends training symbols at the beginning of each slot so that each receiver can estimate the channel and determine the data rate it could potentially receive from each transmit antenna after configuring its antenna weights appropriately. For this purpose, we develop a maximum-likelihood estimator of the signal to interference plus noise ratio (SINR) from the received training symbols. The transmitter decides which receivers to serve in each slot to maximize the minimum normalized average data rate realized by each receiver. This scheduling decision is made based on estimated SINR information fed back by receivers. Through some numerical examples, we discuss some general issues with regard to exploitation of multi-user diversity in the context of imperfect channel state information. For example, the scheduler introduces a bias for positive SINR estimation errors, which is important to take into account when the receivers declare a potential data rate in each slot.