Iterative Genetic and Greedy-Based Algorithms for Multi-Carrier Multi-User Scheduling in MIMO Systems with Successive Zero Forcing

This paper considers low-complexity multi-user scheduling algorithms for multi-carrier multiple-input multiple-output systems. With large number of active users and transmit antennas, the optimal scheduler is computationally too demanding, therefore more efficient sub-optimal schedulers are of interest. We propose genetic and greedy-based iterative algorithms with successive zero forcing for the multi-user multi-carrier scheduling problem, where at each iteration, the proposed algorithms schedule one additional user on every resource unit. In system-level simulations, we analyze their performance and complexity requirements, and demonstrate that the genetic-based iterative scheduler performs well when the network is dense with many users, whereas the greedy-based iterative scheduler can be preferable when there are less users in the network.