Robust adaptive modulation with imperfect channel information

Adaptive modulation is a promising technique to increase system throughput considerably. However, it relies on perfect channel state information (CSI), and is sensitive to errors in CSI. In this work, we maximize the system transmission rate based on a lower bound of average bit error rate (BER) while satisfying the transmit power and BER constraint. In order to further enhance the system throughput, adaptive modulation scheme is combined with a robust transmit beamformer to obtain extra diversity gain. Moreover, to pay the penalty for the lower bound of the average BER, we introduce a probabilistic constraint by keeping a low outage probability of signal-to-noise ratio (SNR). Simulation results show that the proposed scheme provides the maximum system throughput compared with several state-of-the-art robust adaptive schemes, and always guarantees the target BER.

[1]  Georgios B. Giannakis,et al.  Optimal transmitter eigen-beamforming and space-time block coding based on channel correlations , 2003, IEEE Transactions on Information Theory.

[2]  Georgios B. Giannakis,et al.  Adaptive Modulation for multiantenna transmissions with channel mean feedback , 2004, IEEE Transactions on Wireless Communications.

[3]  John G. Proakis,et al.  Probability, random variables and stochastic processes , 1985, IEEE Trans. Acoust. Speech Signal Process..

[4]  Timothy N. Davidson,et al.  Robust transmit eigen beamforming based on imperfect channel state information , 2004, IEEE Transactions on Signal Processing.

[5]  Georgios B. Giannakis,et al.  Multiantenna adaptive modulation with beamforming based on bandwidth-constrained feedback , 2005, IEEE Transactions on Communications.

[6]  Mikael Gidlund,et al.  A Sub-optimal Eigenvalue-Based Adaptive Modulation Scheme for Broadband MIMO-OFDM Systems , 2008, 6th Annual Communication Networks and Services Research Conference (cnsr 2008).

[7]  Pei-Jung Chung,et al.  A Probabilistic Constraint Approach for Robust Transmit Beamforming With Imperfect Channel Information , 2009, IEEE Transactions on Signal Processing.

[8]  Joseph M. Kahn,et al.  Fading correlation and its effect on the capacity of multielement antenna systems , 2000, IEEE Trans. Commun..

[9]  Bruno O. Shubert,et al.  Random variables and stochastic processes , 1979 .

[10]  Bernard Mulgrew,et al.  Robust transmit beamforming based on probabilistic constraint , 2008, 2008 16th European Signal Processing Conference.

[11]  I. Miller.  Probability, Random Variables, and Stochastic Processes , 1966 .

[12]  Andrea J. Goldsmith,et al.  Degrees of freedom in adaptive modulation: a unified view , 2001, IEEE Trans. Commun..

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

[14]  Abbas Jamalipour,et al.  Wireless communications , 2005, GLOBECOM '05. IEEE Global Telecommunications Conference, 2005..

[15]  Joseph M. Kahn,et al.  Fading correlation and its effect on the capacity of multi-element antenna systems , 1998, ICUPC '98. IEEE 1998 International Conference on Universal Personal Communications. Conference Proceedings (Cat. No.98TH8384).

[16]  Daniel Pérez Palomar,et al.  A robust maximin approach for MIMO communications with imperfect channel state information based on convex optimization , 2006, IEEE Transactions on Signal Processing.

[17]  Dennis Goeckel,et al.  Adaptive coding for time-varying channels using outdated fading estimates , 1999, IEEE Trans. Commun..

[18]  Alexandra Duel-Hallen,et al.  Combined adaptive modulation and transmitter diversity using long range prediction for flat fading mobile radio channels , 2001, GLOBECOM'01. IEEE Global Telecommunications Conference (Cat. No.01CH37270).