Optimal Downlink OFDMA Subcarrier, Rate, and Power Allocation with Linear Complexity to Maximize Ergodic Weighted-Sum Rates

In this paper, we propose a resource allocation algorithm for ergodic weighted-sum rate maximization in downlink OFDMA systems. In contrast to most previous research that focused on maximizing instantaneous rates using deterministic optimization techniques, we focus on maximizing ergodic rates using stochastic optimization techniques, which allow us to exploit the temporal dimension, in addition to the frequency and multiuser dimensions. Furthermore, in contrast to most previous algorithms that used greedy suboptimal heuristics with quadratic complexity, we use a dual optimization approach that resulted in a simple subcarrier, rate, and power allocation algorithm that has complexity O(MK) for an M-user, K-subcarrier OFDMA system. Surprisingly, our method is shown to result in duality gaps less than 10^-4 in scenarios of practical interest, thereby allowing us to claim practical optimality. We present simulation results for a 3GPP-LTE system employing adaptive modulation.