Efficient Scheduling Algorithms for Multiantenna CDMA Systems

In multiple-input-multiple-output (MIMO) multiuser systems, simultaneously serving multiple users achieves high data rates. However, high-performance transmit beamforming requires an adequately designed user-selection scheme. Optimal scheduling can be only obtained through a high computationally complex exhaustive search, and hence, low-complexity heuristic algorithms are required. In addition, employing a multiple-access scheme such as code division (CDMA) largely increases the complexity of optimal scheduling, and it becomes unemployable even for a moderate number of users and antennas. In this context, this paper proposes three heuristic scheduling algorithms for MIMO CDMA systems using zero-forcing beamforming (ZFBF). We use a graph-theoretical approach to model the system as a weighted undirected graph. The problem of user selection is then formulated as a graph coloring problem, namely, the maximum weight N-colorable subgraph problem. Then, we design two heuristics to solve this graph problem. The first algorithm is a low-complexity greedy algorithm. The second algorithm is based on a tabu search approach to resolve efficiently the complexity/performance tradeoff. Numerical and simulation results show the sub-optimal performances and robustness of the proposed low-complexity algorithms.