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One of major issues in the efficient use of radio resource for multiuser multiple-input/multiple-output (MU-MIMO) systems is the selection of users to achieve the maximum system throughput. The optimal user selection algorithm, which requires exhaustive search, is prohibitive due to its high computational complexity where Block diagonalization (BD) method is applied and known as a suboptimal precoding technique for downlink MU-MIMO systems, which intents to perfectly eliminate inter-user interference. In this paper, we propose efficient, iterative user selection algorithms with low complexity, where the product of eigenvalues of effective channels is utilized as a selection metric by applying the concept of principal angles between subspaces. And, we further examined the applicability of the proposed algorithms to limited feedback systems and proportional fair (PF) scheduling. Through computational complexity analysis, we show that the proposed algorithm has low complexity with a little loss in throughput. Simulation results validate that the proposed algorithm achieves almost the same system throughput by a capacity-based algorithm under high SNR regime with considerable reduction in complexity.