Analysis of Multiuser Diversity in

Research in recent years has been focusing on the role of multiuser diversity in enhancing the throughput of wireless networks. Channel fading is now seen as a source of randomization that can be exploited by a smart scheduler with partial channel information, for example, in terms of data rates requested by the users. In this paper, we analyze the performance of a multiuser diversity system, taking into account the feedback errors due to channel variability. Channel estimation errors are modeled as Gaussian random variables with variance depending on the Doppler spread. Based on a block fading channel model, we present an expression for the throughput, both as a function of the key system parameters, such as packet length and data rate thresholds, and channel characteristics, such as Doppler spread. From the analysis of the performance, we present a tradeoff between multiuser diversity and mobility, and also between rate adaptivity and channel estimation errors. It is shown that multiuser diversity gain is reduced for increasing receiver mobility, and that the throughput loss depends also on the distribution of the data rate thresholds. Finally, we use the expressions derived in the paper in order to adaptively reduce the loss due to feedback errors. Given a set of possible data rates, the users can choose the most suitable one based not only on the set of thresholds and signal strength, but also on mobility conditions and system parameters, such as packet length.

[1]  Raymond Knopp,et al.  Information capacity and power control in single-cell multiuser communications , 1995, Proceedings IEEE International Conference on Communications ICC '95.

[2]  Laurence B. Milstein,et al.  On the effect of imperfect interleaving for the Gilbert-Elliott channel , 1999, IEEE Trans. Commun..

[3]  Akbar M. Sayeed,et al.  Pilot-based estimation of time-varying multipath channels for coherent CDMA receivers , 2002, IEEE Trans. Signal Process..

[4]  Norman C. Beaulieu,et al.  Infinite series representations of the bivariate Rayleigh and Nakagami-m distributions , 1997, IEEE Trans. Commun..

[5]  Hong Shen Wang,et al.  Finite-state Markov channel-a useful model for radio communication channels , 1995 .

[6]  Matthew S. Grob,et al.  CDMA/HDR: a bandwidth-efficient high-speed wireless data service for nomadic users , 2000, IEEE Commun. Mag..

[7]  B. Hassibi,et al.  On the Throughput of Broadcast Channels with Imperfect CSI , 2006, 2006 IEEE 7th Workshop on Signal Processing Advances in Wireless Communications.

[8]  Laurence B. Milstein,et al.  Multiuser diversity-mobility tradeoff: modeling and performance analysis of a proportional fair scheduling , 2002, Global Telecommunications Conference, 2002. GLOBECOM '02. IEEE.

[9]  L. B. Milstein,et al.  ARQ error control for fading mobile radio channels , 1997 .

[10]  L. B. Milstein,et al.  On the accuracy of a first-order Markov model for data transmission on fading channels , 1995, Proceedings of ICUPC '95 - 4th IEEE International Conference on Universal Personal Communications.

[11]  David Tse,et al.  Optimal power allocation over parallel Gaussian broadcast channels , 1997, Proceedings of IEEE International Symposium on Information Theory.

[12]  Giuseppe Caire,et al.  Transmit Diversity Versus Opportunistic Beamforming in Data Packet Mobile Downlink Transmission , 2007, IEEE Transactions on Communications.

[13]  Babak Hassibi,et al.  The Effect of Channel Estimation Error on the Throughput of Broadcast Channels , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[14]  Pravin Varaiya,et al.  Capacity of fading channels with channel side information , 1997, IEEE Trans. Inf. Theory.

[15]  David Tse,et al.  Opportunistic beamforming using dumb antennas , 2002, IEEE Trans. Inf. Theory.

[16]  Aria Nosratinia,et al.  Exploiting multiuser diversity with only 1-bit feedback , 2005, IEEE Wireless Communications and Networking Conference, 2005.

[17]  W. C. Jakes,et al.  Microwave Mobile Communications , 1974 .