Limited feedback beamforming over temporally-correlated channels
IEEE Transactions on Signal Processing
Accurate estimation of ICA weight matrix by implicit constraint imposition using lie group
IEEE Transactions on Neural Networks
Limited feedback multiuser MIMO techniques for time-correlated channels
EURASIP Journal on Advances in Signal Processing - Multiuser MIMO Transmission with Limited Feedback, Cooperation, and Coordination
Grassmannian predictive coding for delayed limited feedback MIMO systems
Allerton'09 Proceedings of the 47th annual Allerton conference on Communication, control, and computing
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Event-driven optimal feedback control for multiantenna beamforming
IEEE Transactions on Signal Processing
Robust precoding with Bayesian error modeling for limited feedback MU-MISO systems
IEEE Transactions on Signal Processing
Differential feedback of MIMO channel gram matrices based on geodesic curves
IEEE Transactions on Wireless Communications
Decentralized limited-feedback multiuser MIMO for temporally correlated channels
Journal of Electrical and Computer Engineering
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In this paper, we propose two efficient low-complexity quantization methods for multiple-input multiple-output (MIMO) systems with finite-rate feedback based on proper parameterization of the information to be fed back followed by quantization in the new parameter domain. For a MIMO channel which has multiple orthonormal vectors as channel spatial information, we exploit the geometrical structure of orthonormality while quantizing the spatial information matrix. The parameterization is of two types: one is in terms of a set of unit-norm vectors with different lengths, and the other is in terms of a minimal number of scalar parameters. These parameters are shown to be independent for the i.i.d. flat-fading Rayleigh channel, facilitating efficient quantization. In the first scheme, each of the unit-norm vectors is independently quantized with a finite number of bits using an optimal vector quantization (VQ) technique. Bit allocation is needed between the vectors, and the optimum bit allocation depends on the operating SNR of the system. In the second scheme, the scalar parameters are quantized. In slowly time-varying channels, the scalar parameters are also found to be smoothly changing over time, leading to the development of a simple quantization and feedback method using adaptive delta modulation. The results show that the proposed feedback scheme has a channel tracking feature and achieves a capacity very close to perfect feedback with a reasonable feedback rate