Optimal Power Control in Decentralized Gaussian Multiple Access Channels

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.Comment: 4 pages, 4 figures, accepted for publication to IEEE Communication letter

On the Ergodic Sum-Capacity of Decentralized Multiple Access Channels

We consider a fast fading AWGN multiple-access channel (MAC) with full receiver CSI and distributed CSI at the transmitters. The objective is to evaluate the ergodic sum-capacity of this decentralized model, under identical average powers and channel statistics across users. While an optimal water-filling solution can be found for centralized MACs with full CSI at all terminals, such an explicit solution is not considered feasible in distributed CSI models. Our main contribution is an upper-bound on the ergodic sum-capacity when each transmitter is aware only of its own fading coefficients. Interestingly, our techniques also suggest an appropriate lower bound. These bounds are shown to be very close to each other, suggesting the tight nature of the results