Graph-based resource allocation algorithms for multiuser downlink MIMO-OFDMA networks

Abstract

Multiuser multiple-input multiple-output orthogonal frequency division multiple access MIMO-OFDMA is considered as the practical method to attain the capacity promised by multiple antennas in the downlink direction. However, the joint calculation of precoding/beamforming and resource allocation required by the optimal algorithms is computationally prohibitive. This paper proposes computationally efficient resource allocation algorithms that can be invoked after the precoding and beamforming operations. To support stringent and diverse quality of service requirements, previous works have shown that the resource allocation algorithm must be able to guarantee a specific data rate to each user. The constraint matrix defined by the resource allocation problem with these data rate constraints provides a special structure that lends to efficient solution of the problem. On the basis of the standard graph theory and the Lagrangian relaxation, we develop an optimal resource allocation algorithm that exploits this structure to reduce the required execution time. Moreover, a lower-complexity suboptimal algorithm is introduced. Extensive simulations are conducted to evaluate the computational and system-level performance. It is shown that the proposed resource allocation algorithms attain the optimal solution at a much lower computational overhead compared with general-purpose optimization algorithms used by previous MIMO-OFDMA resource allocation approaches. Copyright © 2012 John Wiley & Sons, Ltd.