  We consider the decentralized power optimization problem for Gaussian
fast-fading multiple access channel (MAC) so that the average sum-throughput is
maximized. In our MAC setup, each transmitter has access to only its own fading
coefficient or channel state information (CSI) while the receiver has full CSI
available at all instants. Unlike centralized MAC (full CSIT MAC) where the
optimal powers are known explicitly, the analytical solution for optimal
decentralized powers does not seem feasible. In this letter, we specialize
alternating-maximization (AM) method for numerically computing the optimal
powers and ergodic capacity of the decentralized MAC for general fading
statistics and average power constraints. For illustration, we apply our AM
method to compute the capacity of MAC channels with fading distributions such
as Rayleigh, Rician etc.
