Matrix analysis
On Limits of Wireless Communications in a Fading Environment when UsingMultiple Antennas
Wireless Personal Communications: An International Journal
Convex Optimization
MIMO transceiver design via majorization theory
Foundations and Trends in Communications and Information Theory
Worst-case robust MIMO transmission with imperfect channel knowledge
IEEE Transactions on Signal Processing
Robust QoS-constrained optimization of downlink multiuser MISO systems
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
A competitive minimax approach to robust estimation of random parameters
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Optimal designs for space-time linear precoders and decoders
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Robust transmit eigen beamforming based on imperfect channel state information
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Transmitter optimization and optimality of beamforming for multiple antenna systems
IEEE Transactions on Wireless Communications
Optimization of the MIMO Compound Capacity
IEEE Transactions on Wireless Communications
Space-time block codes from orthogonal designs
IEEE Transactions on Information Theory
The Optimality of Transmit Beamforming: A Unified View
IEEE Transactions on Information Theory
Efficient use of side information in multiple-antenna data transmission over fading channels
IEEE Journal on Selected Areas in Communications
Wireless Personal Communications: An International Journal
Wireless Personal Communications: An International Journal
Hi-index | 35.68 |
Beamforming is a simple transmit strategy that uses only one eigen-direction in multiple-input multiple-output channels. This simplicity makes beamforming a competitive strategy in practice, but at the same time poses a doubt on the sensitivity of beamforming to the imperfectness of the channel state information at the transmitter (CSIT). This paper studies beamforming from the perspective of worst-case robustness. We show that beamforming can achieve the maximum received signal-to-noise ratio (SNR) or guarantees a given received SNR with the minimum transmit power, in the worst channel within an elliptical uncertainty region defined by the weighted spectral norm. This result further implies that beamforming has the ability to combat against the imperfectness of CSIT, especially for small channel dimensions or small channel uncertainty.