Abstract :
With the causal channel state information at the transmitter (CSIT) and the channel statistics in the future, in this paper, we address the power allocation problem to achieve a given information rate with certain probability (i.e., outage rate) for a block Rayleigh-fading channel. In particular, we aim to minimize the total power required for achieving an outage capacity by adaptively and stochastically allocating the transmit power for each block. Using Gaussian approximation, we shall derive the outage probability for a given rate, and then illustrate that the optimization problem is, in general, not convex. To determine the optimal power policy, however, it is shown that the optimization can be solved numerically at affordable complexity. Numerical results demonstrate that the proposed power policy yields significant power reduction compared to an equal-power policy for a given outage rate.
Keywords :
Gaussian processes; Rayleigh channels; channel capacity; computational complexity; optimal control; power control; telecommunication congestion control; Gaussian approximation; block Rayleigh-fading channel; channel state information; channel statistics; equal-power policy; optimal stochastic power control; outage capacity constraints; power allocation problem; Channel capacity; Channel state information; Constraint optimization; Delay; Power control; Probability; Rayleigh channels; Statistical distributions; Stochastic processes; Transmitters;