On transceiver design and channel quantization for downlink multiuser MIMO systems with limited feedback

We consider a MIMO broadcast channel where both the transmitter and receivers are equipped with multiple antennas. Channel state information at the transmitter (CSIT) is obtained through limited (i.e., finite-bandwidth) feedback from the receivers that index a set of precoding vectors contained in a predefined codebook. We propose a novel transceiver architecture based on zero-forcing beamforming and linear receiver combining. The receiver combining and quantization for CSIT feedback are jointly designed in order to maximize the expected SINR for each user. We provide an analytic characterization of the achievable throughput in the case of many users and show how additional receive antennas or higher multiuser diversity can reduce the required feedback rate to achieve a target throughput.We also propose a design methodology for generating codebooks tailored for arbitrary spatial correlation statistics. The resulting codebooks have a tree structure that can be utilized in time-correlated MIMO channels to significantly reduce feedback overhead. Simulation results show the effectiveness of the overall transceiver design strategy and codebook design methodology compared to prior techniques in a variety of correlation environments.

[1]  Federico Boccardi,et al.  A Near-Optimum Technique using Linear Precoding for the MIMO Broadcast Channel , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

[2]  M. J. Gans,et al.  On Limits of Wireless Communications in a Fading Environment when Using Multiple Antennas , 1998, Wirel. Pers. Commun..

[3]  Rohit U. Nabar,et al.  Introduction to Space-Time Wireless Communications , 2003 .

[4]  Andrea J. Goldsmith,et al.  Multi-Antenna Downlink Channels with Limited Feedback and User Selection , 2007, IEEE Journal on Selected Areas in Communications.

[5]  Michael L. Honig,et al.  Asymptotic capacity of beamforming with limited feedback , 2004, International Symposium onInformation Theory, 2004. ISIT 2004. Proceedings..

[6]  N.D. Sidiropoulos,et al.  On downlink beamforming with greedy user selection: performance analysis and a simple new algorithm , 2005, IEEE Transactions on Signal Processing.

[7]  Michael L. Honig,et al.  Signature optimization for CDMA with limited feedback , 2005, IEEE Transactions on Information Theory.

[8]  M. Trivellato,et al.  Multiuser eigenmode transmission for mimo broadcast channels with limited feedback , 2007, 2007 IEEE 8th Workshop on Signal Processing Advances in Wireless Communications.

[9]  Robert W. Heath,et al.  Grassmannian beamforming on correlated MIMO channels , 2004, IEEE Global Telecommunications Conference, 2004. GLOBECOM '04..

[10]  Nevio Benvenuto,et al.  Algorithms for Communications Systems and their Applications , 2021 .

[11]  Martin Haardt,et al.  Zero-forcing methods for downlink spatial multiplexing in multiuser MIMO channels , 2004, IEEE Transactions on Signal Processing.

[12]  Alexei Ashikhmin,et al.  Grassmannian Packings for Efficient Quantization in MIMO Broadcast Systems , 2007, 2007 IEEE International Symposium on Information Theory.

[13]  Alireza Bayesteh,et al.  On the User Selection for MIMO Broadcast Channels , 2005, IEEE Transactions on Information Theory.

[14]  Robert W. Heath,et al.  Shifting the MIMO Paradigm , 2007, IEEE Signal Processing Magazine.

[15]  Ross D. Murch,et al.  A transmit preprocessing technique for multiuser MIMO systems using a decomposition approach , 2004, IEEE Transactions on Wireless Communications.

[16]  Federico Boccardi,et al.  Hierarchical Quantization and its Application to Multiuser Eigenmode Transmissions for MIMO Broadcast Channels with Limited Feedback , 2007, 2007 IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications.

[17]  Jari Salo,et al.  MATLAB implementation of the 3GPP Spatial Channel Model Extended (SCME) , 2006 .

[18]  Robert W. Heath,et al.  Grassmannian beamforming for multiple-input multiple-output wireless systems , 2003, IEEE Trans. Inf. Theory.

[19]  Federico Boccardi,et al.  User Selection Schemes for MIMO Broadcast Channels with Limited Feedback , 2007, 2007 IEEE 65th Vehicular Technology Conference - VTC2007-Spring.

[20]  M. Trivellato,et al.  Joint low-rate feedback and channel quantization for the MIMO broadcast channel , 2007, AFRICON 2007.

[21]  Harish Viswanathan,et al.  Downlink capacity evaluation of cellular networks with known-interference cancellation , 2003, IEEE J. Sel. Areas Commun..

[22]  Antonia Maria Tulino,et al.  Random Matrix Theory and Wireless Communications , 2004, Found. Trends Commun. Inf. Theory.

[23]  Andrea J. Goldsmith,et al.  On the optimality of multiantenna broadcast scheduling using zero-forcing beamforming , 2006, IEEE Journal on Selected Areas in Communications.

[24]  M. V. Clark,et al.  Theoretical reliability of MMSE linear diversity combining in Rayleigh-fading additive interference channels , 1998, IEEE Trans. Commun..

[25]  Emre Telatar,et al.  Capacity of Multi-antenna Gaussian Channels , 1999, Eur. Trans. Telecommun..

[26]  Nihar Jindal Antenna combining for the MIMO downlink channel , 2008, IEEE Transactions on Wireless Communications.