Vector quantization and signal compression
Vector quantization and signal compression
On Limits of Wireless Communications in a Fading Environment when UsingMultiple Antennas
Wireless Personal Communications: An International Journal
Interpolation based transmit beamforming for MIMO-OFDM with limited feedback
IEEE Transactions on Signal Processing
Quantifying the power loss when transmit beamforming relies on finite-rate feedback
IEEE Transactions on Wireless Communications
On the achievable throughput of a multiantenna Gaussian broadcast channel
IEEE Transactions on Information Theory
Grassmannian beamforming for multiple-input multiple-output wireless systems
IEEE Transactions on Information Theory
Technical solutions for the 3G long-term evolution
IEEE Communications Magazine
On the optimality of multiantenna broadcast scheduling using zero-forcing beamforming
IEEE Journal on Selected Areas in Communications
Systematic Codebook Designs for Quantized Beamforming in Correlated MIMO Channels
IEEE Journal on Selected Areas in Communications
Multi-Antenna Downlink Channels with Limited Feedback and User Selection
IEEE Journal on Selected Areas in Communications
Limited feedback in multiuser MIMO OFDM systems based on rate approximation
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
| Hi-index | 0.00 |
We consider a multiuser MIMO-OFDM downlink system with single antenna mobile terminals (MTs) where channel state information at the base station is provided through limited uplink feedback (FB). In order to reduce the FB rate and signal processing complexity, the available bandwidth is divided into resource blocks (RBs) whose number of subcarriers reflects the coherence bandwidth of the channel. This approach is very common in the standardization of 4th generation wireless communication systems and justifies an independent channel quantization per RB. Within this framework the paper contains two main contributions. Firstly we provide joint conditions on the channel coherence bandwidth and the FB rate per RB that allow for a simpler quantization of the RB channel matrix (spacefrequency) by a space vector, causing negligible performance loss in terms of system achievable throughput. This is accomplished after deriving a new metric for codebook design in RB channel quantization that exploits spatial and frequency correlation. As a second contribution we investigate the trade-off between accurate channel knowledge and frequency/multiuser diversity. It is seen that even for a moderate number of MTs in the network, concentrating all the available FB bits in characterizing only one RB provides a significant gain in system throughput over a more classical distributed approach and this result is validated both analytically and by simulations.