Performance analysis of multiuser downlink space-time scheduling for TDD systems with imperfect CSIT

This paper studies the effect of imperfect channel state information (CSIT) on the performance of multiple-antenna downlink scheduling for time-division-duplex system. The base station is equipped with n/sub T/ transmit antennas and there are K mobiles in the system, each with single receive antenna. We propose an analytical framework to study the multiantenna downlink scheduling problem in the presence of imperfect CSIT at the base station. We found that with ideal CSIT, the space-time scheduler can achieve significant system capacity with respect to n/sub T/ due to increased spatial channels. However, at moderate CSIT estimation error, the system performance using the ideal scheduling algorithm (designed for perfect CSI) saturates quickly with respect to n/sub T/ and signal-to-noise ration (SNR) increases. This is because in the presence of imperfect CSIT, the scheduled data rate of a user may exceed the actual channel capacity and resulting in packet transmission outage. To realize the potential spatial multiplexing gain over n/sub T/ and SNR, we propose an analytical framework to take into account of the packet transmission outage and propose scheduling solutions matching the imperfect CSIT situations. We found that, by considering the statistics of CSIT errors into the design, the proposed schemes provide significant system performance enhancement.

[1]  Harish Viswanathan,et al.  Rate scheduling in multiple antenna downlink wireless systems , 2005, IEEE Transactions on Communications.

[2]  Shlomo Shamai,et al.  The capacity region of the Gaussian MIMO broadcast channel , 2004, International Symposium onInformation Theory, 2004. ISIT 2004. Proceedings..

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

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

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

[6]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[7]  K. Rohani,et al.  Application of MIMO and proportional fair scheduling to CDMA downlink packet data channels , 2002, Proceedings IEEE 56th Vehicular Technology Conference.

[8]  Shlomo Shamai,et al.  On the Achievable Throughput of a Multiantenna , 2003 .

[9]  Pawel Kulakowski Channel adaptive technologies and cross layer designs for wireless systems with multiple antennas [Book Review] , 2006, IEEE Communications Magazine.

[10]  K. V. S. Hari,et al.  On the variations in capacity of MIMO communication systems to channel perturbations , 2002, 2002 IEEE International Conference on Personal Wireless Communications.

[11]  Babak Hassibi,et al.  How much training is needed in multiple-antenna wireless links? , 2003, IEEE Trans. Inf. Theory.

[12]  R. M. Buehrer,et al.  On the performance of scheduling over space-time architectures , 2002, Proceedings IEEE 56th Vehicular Technology Conference.

[13]  Vincent K. N. Lau,et al.  Optimal downlink space-time scheduling design with convex utility functions-multiple-antenna systems with orthogonal spatial multiplexing , 2005, IEEE Transactions on Vehicular Technology.

[14]  Vincent K. N. Lau,et al.  Optimal multi-user space time scheduling for wireless communications , 2002, Proceedings IEEE 56th Vehicular Technology Conference.

[15]  Muriel Médard,et al.  The effect upon channel capacity in wireless communications of perfect and imperfect knowledge of the channel , 2000, IEEE Trans. Inf. Theory.