Achievable throughput of multi-mode multiuser MIMO with imperfect CSI constraints

In the multiple-input multiple-output (MIMO) broadcast channel with imperfect channel state information (CSI), neither the capacity nor the optimal transmission technique have been fully discovered. In this paper, we derive achievable ergodic rates for a multi-antenna fading broadcast channel when CSI at the transmitter (CSIT) is delayed and quantized. It is shown that not all possible users should be supported with spatial division multiplexing due to the residual inter-user interference caused by imperfect CSIT. Based on the derived achievable rates, we propose a multi-mode transmission strategy to maximize the throughput, which adaptively adjusts the number of active users based on the channel statistics information.

[1]  N. Jindal,et al.  High SNR Analysis for MIMO Broadcast Channels: Dirty Paper Coding Versus Linear Precoding , 2006, IEEE Transactions on Information Theory.

[2]  Nihar Jindal,et al.  MIMO broadcast channels with finite rate feedback , 2006, GLOBECOM '05. IEEE Global Telecommunications Conference, 2005..

[3]  Giuseppe Caire,et al.  Multiuser MIMO Downlink Made Practical: Achievable Rates with Simple Channel State Estimation and Feedback Schemes , 2007, ArXiv.

[4]  Youjian Liu,et al.  Quantization Bounds on Grassmann Manifolds and Applications to MIMO Communications , 2006, IEEE Transactions on Information Theory.

[5]  Shlomo Shamai,et al.  On the Capacity of Fading MIMO Broadcast Channels with Imperfect Transmitter Side-Information , 2006, ArXiv.

[6]  Jun Zhang,et al.  Single-user MIMO vs. Multiuser MIMO in the broadcast channel with CSIT constraints , 2008, 2008 46th Annual Allerton Conference on Communication, Control, and Computing.

[7]  Robert W. Heath,et al.  An overview of limited feedback in wireless communication systems , 2008, IEEE Journal on Selected Areas in Communications.

[8]  Jeffrey G. Andrews,et al.  Mode Switching for MIMO Broadcast Channel Based on Delay and Channel Quantization , 2008, arXiv.org.

[9]  Giuseppe Caire,et al.  Multiuser MIMO Achievable Rates With Downlink Training and Channel State Feedback , 2007, IEEE Transactions on Information Theory.

[10]  Jeffrey G. Andrews,et al.  Mode Switching for the Multi-Antenna Broadcast Channel Based on Delay and Channel Quantization , 2008, EURASIP J. Adv. Signal Process..

[11]  David Gesbert,et al.  Efficient Metrics for Scheduling in MIMO Broadcast Channels with Limited Feedback , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

[12]  Michael D. Zoltowski,et al.  Multiple Antenna Broadcast Channels With Shape Feedback and Limited Feedback , 2007, IEEE Transactions on Signal Processing.

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

[14]  D. Gesbert,et al.  Distributed transmit mode selection for MISO broadcast channels with limited feedback: Switching from SDMA to TDMA , 2008, 2008 IEEE 9th Workshop on Signal Processing Advances in Wireless Communications.

[15]  David James Love,et al.  A Simple Dual-Mode Limited Feedback Multiuser Downlink System , 2009, IEEE Transactions on Communications.

[16]  Nihar Jindal,et al.  High SNR analysis of MIMO broadcast channels , 2005, Proceedings. International Symposium on Information Theory, 2005. ISIT 2005..

[17]  Youjian Liu,et al.  Quantization Bounds on Grassmann Manifolds and Applications to MIMO Systems , 2005 .

[18]  David James Love,et al.  On the performance of random vector quantization limited feedback beamforming in a MISO system , 2007, IEEE Transactions on Wireless Communications.

[19]  R. Clarke A statistical theory of mobile-radio reception , 1968 .

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

[21]  Nihar Jindal Finite Rate Feedback MIMO Broadcast Channels , 2006 .