Constrained Ergodic Rates Maximization for Mobile WiMAX with Statistical Channel Information

In some fading environments, there may not be a feedback link sufficiently fast to convey the full channel state information (CSI) to the transmitter. This paper considers resource allocation strategies for downlink multiuser mobile WiMAX systems, where the base station knows only the channel distribution information (CDI), but has no knowledge of the instantaneous channel realization. The base station uses CDI to assign subchannels and allocate power to users with the objective to maximize the ergodic weighted sum rate while satisfying minimum rate, long-term fairness and power constraints. We solve the underlying constrained optimization problem using the Lagrange dual decomposition framework. The proposed method has a complexity of O(KM) for K users and M subchannels. Simulation results are provided to compare the performance of this method with other allocation schemes and to illustrate the trade-off between maximized weighted sum rate and the constraints.