Greedy User Selection Using a Lattice Reduction Updating Method for Multiuser MIMO Systems

User selection plays a crucial role in multiple-access channels (e.g., uplink channels of cellular systems) to exploit the multiuser diversity. Although the achievable rate can be adopted for a performance indicator in user selection, it may not be proper if a suboptimal detector or decoder is employed. In particular, for multiuser multiple-input-multiple-output (MIMO) systems, a low-complexity suboptimal MIMO detector can be used instead of optimal MIMO detectors, which require prohibitively high computational complexity. Under this practical circumstance, it may be desirable to derive user selection criteria based on the error probability for a given low-complexity MIMO detector. In this paper, we propose a low-complexity greedy user selection scheme with an iterative lattice reduction (LR) updating algorithm when an LR-based MIMO detector is used. We also analyze the diversity gain for combinatorial user selection approaches with various MIMO detectors. Based on the simulation results, we can confirm that the proposed greedy user selection approach can provide a comparable performance with the combinatorial approaches with much lower complexity.