CQI algorithm design in MIMO systems with maximum likelihood detectors

In this paper, we investigate throughput optimization in 2×22×2 multi-input multi-output (MIMO) systems using channel quality indicator (CQI) based scheduling. Existing MIMO CQI algorithms are mostly designed for sub-optimal linear symbol detectors such as minimum mean square error (MMSE). We consider in this paper how to select CQIs for both streams in order to maximize the total throughput when the non-linear optimal symbol detection technique, maximum likelihood (ML) detector, is employed. Specifically, we formulate a simple yet accurate mathematical model for throughput maximization in a 2×22×2 MIMO channel using an ML detector. We make use of constellation constrained capacity to characterize the feasible rate region of such MIMO systems. Based on the information-theoretic analysis, a novel CQI algorithm for 2×22×2 MIMO transmission is proposed. Numerical results indicate that the proposed CQI algorithm yields up to 4% throughput improvement over the CQI algorithm optimized for MMSE detectors in High Speed Downlink Packet Access (HSDPA).