A near-optimal randomized algorithm for uplink resource allocation in OFDMA systems

OFDMA has been selected as the multiple access scheme for emerging broadband wireless communication systems. However, designing efficient resource allocation algorithms for OFDMA systems is a challenging task, especially in the uplink, due to the combinatorial nature of subcarrier assignment and the distributed power budget for different users. Inspired by Glauber dynamics, in this paper, we propose a randomized iteration-based uplink OFDMA resource allocation algorithm. We show that our algorithm is near-optimal in the sense that by increasing the number of iterations (which scales up the complexity), with arbitrarily large probability, the algorithm can converge to the subcarrier/power allocation pattern with the maximum sum-utility. We also show that this algorithm can be generalized to solve a joint uplink-downlink allocation problem in full-duplex OFDMA systems. Simulations are conducted to compare the performance of our algorithm with existing ones.