Vector quantization and signal compression
Vector quantization and signal compression
Design and analysis of transmit-beamforming based on limited-rate feedback
IEEE Transactions on Signal Processing
On beamforming with finite rate feedback in multiple-antenna systems
IEEE Transactions on Information Theory
Grassmannian beamforming for multiple-input multiple-output wireless systems
IEEE Transactions on Information Theory
MIMO Broadcast Channels With Finite-Rate Feedback
IEEE Transactions on Information Theory
Multi-Antenna Downlink Channels with Limited Feedback and User Selection
IEEE Journal on Selected Areas in Communications
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Focusing on time correlation of real communication channels, a channel quantization algorithm based on finite state vector quantization (FSVQ) is proposed. Firstly channels are partitioned into finite states, then codebooks corresponding to each state are constructed, which are used to quantize channels transferred from corresponding states. Further, the state transition function is designed to ensure the synchronization between transmitter and receiver. The proposed algorithm can achieve improved performance with the same feedback load compared with classical memoryless channel quantizer without consideration of the influence of time correlation. Simulation results verify the effectiveness of the proposed algorithm.