Optimal Resource Allocation for Multiuser MIMO-OFDM Systems With User Rate Constraints

With the proliferation of wireless services, personal connectivity is quickly becoming ubiquitous. As the user population demands greater multimedia interactivity, data rate requirements are set to soar. Future wireless systems, e.g., multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM), need to cater to not only a burgeoning subscriber pool but also to a higher throughput per user. Furthermore, resource allocation for multiuser MIMO-OFDM systems is vital for the optimization of the subcarrier and power allocations to improve overall system performance. Using convex optimization techniques, this paper proposes an efficient solution to minimize the total transmit power subject to each user's data rate requirement. Using a Lagrangian dual decomposition, the complexity is reduced from one that is exponential in the number of subcarriers; M to one that is only linear in M. To keep the complexity low, linear beamforming is incorporated at both the transmitter and the receiver. Although frequency-flat fading has been known to plague OFDM resource allocation systems, a modification, i.e., dual proportional fairness, seamlessly handles flat or partially frequency-selective fading. Due to the nonconvexity of the optimization problem, the proposed solution is not guaranteed to be optimal. However, for a realistic number of subcarriers, the duality gap is practically zero, and optimal resource allocation can be evaluated efficiently. Simulation results show large performance gains over a fixed subcarrier allocation.