Robust downlink power control using worst-case performance optimization

In this paper, a new robust downlink power control solution based on worst-case performance optimization is developed. Our approach depends on explicit modeling of uncertainties in the downlink channel correlation (DCC) matrices, worst-case performance optimization and guarantees that the quality of service (QoS) constraints are satisfied for all users using minimum amount of power. An iterative algorithm to find the optimum power allocation is proposed. The key to this algorithm is to solve an optimization problem to obtain worst-case uncertainty matrices. When the uncertainty is small enough to guarantee that the DCC matrices are positive semidefinite, we obtain a closed-form solution of the subproblem. When the uncertainty is large, we transform this intractable problem into a convex problem. Simulation results show that our proposed robust downlink power control using the approach of worst-case performance optimization reduces the transmission power effectively under imperfect knowledge of the channel condition.

[1]  Shahram Shahbazpanahi,et al.  Robust power adjustment for transmit beamforming in cellular communication systems , 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..

[2]  Shahrokh Valaee,et al.  A covariance fitting approach to parametric localization of multiple incoherently distributed sources , 2004, IEEE Transactions on Signal Processing.

[3]  Arogyaswami Paulraj,et al.  Base station transmitting antenna arrays for multipath environments , 1996, Signal Process..

[4]  Seyong Kwon,et al.  Adaptive beamforming from the generalized eigenvalue problem with a linear complexity for a wideband CDMA channel , 1999, Gateway to 21st Century Communications Village. VTC 1999-Fall. IEEE VTS 50th Vehicular Technology Conference (Cat. No.99CH36324).

[5]  Zhi-Quan Luo,et al.  Robust adaptive beamforming using worst-case performance optimization via Second-Order Cone programming , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[6]  Zhi-Quan Luo,et al.  Robust adaptive beamforming for general-rank signal models , 2003, IEEE Trans. Signal Process..

[7]  Preben E. Mogensen,et al.  A stochastic model of the temporal and azimuthal dispersion seen at the base station in outdoor propagation environments , 2000, IEEE Trans. Veh. Technol..

[8]  Zhi-Quan Luo,et al.  Robust adaptive beamforming using worst-case performance optimization: a solution to the signal mismatch problem , 2003, IEEE Trans. Signal Process..

[9]  Mats Bengtsson Robust and constrained downlink beamforming , 2000, 2000 10th European Signal Processing Conference.

[10]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[11]  Holger Boche,et al.  A new approach to power adjustment for spatial covariance based downlink beamforming , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

[12]  Shahram Shahbazpanahi,et al.  Robust downlink power adjustment in cellular communication systems with antenna arrays at base stations , 2003, 2003 4th IEEE Workshop on Signal Processing Advances in Wireless Communications - SPAWC 2003 (IEEE Cat. No.03EX689).

[13]  A.B. Gershman,et al.  Robust adaptive beamforming using worst-case performance optimization , 2003, The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers, 2003.

[14]  L. C. Godara,et al.  Handbook of Antennas in Wireless Communications , 2001 .

[15]  Lloyd J. Griffiths,et al.  A projection approach for robust adaptive beamforming , 1994, IEEE Trans. Signal Process..

[16]  A. Czylwik,et al.  Robust downlink beamforming based upon outage probability criterion [cellular radio] , 2004, IEEE 60th Vehicular Technology Conference, 2004. VTC2004-Fall. 2004.