Efficient scheduling of multi-antenna broadcast systems

Abstract

In this thesis, we study the problem of efficiently scheduling users in a multi-antenna Gaussian broadcast channel with 1M transmit antennas and K independent receivers each with a single receive antenna. We first focus on a scenario with two transmit antennas and statistically identical users, and analyze the gap between the full sum capacity and the rate that can be achieved by transmitting to a suitably selected pair of users. In particular, we consider a scheme that picks the user with the largest channel gain., and selects a second user from the next L - 1 largest ones to form the best pair, taking the orientation of channel vectors into account as well. We prove that the expected rate gap converges to 1/(L - 1) nats/symbol when the total number of users K tends to infinity. Allowing L to increase with K, it; may be deduced that transmitting to a properly chosen pair of users is asymptotically optimal, while dramatically reducing the feedback overhead and operational complexity. Next, we tackle the problem of maximizing a weighted sum rate in a scenario with heterogeneous user characteristics.

(cont.) We establish a novel upper bound for the weighted sum capacity, which we then use to show that the maximum expected weighted sum rate can be asymptotically achieved by transmitting to a suitably selected subset of at most MC users, where C denotes the number of distinct user classes. Numerical experiments indicate that the asymptotic results are remarkably accurate and that the proposed schemes operate close to absolute performance bounds, even for a moderate number of users.