Kalman Filtering Based Combining for MIMO Systems With Hybrid ARQ

This paper proposes a Kalman filtering (KF)-based combining scheme for multiple-input multiple-output (MIMO) systems with hybrid automatic repeat request (ARQ). In the state-space model, the change of a transmit signal vector in consecutive transmission time intervals (TTIs) is interpreted as the transition of a state vector. Accordingly, the proposed KF operation performs symbol-level combining (SLC) based on linear minimum mean-square-error (LMMSE) detection using the information aggregated up to the current TTI. The state-space model can represent various configurations for MIMO systems with hybrid ARQ (HARQ) via a simple modification of a transition indicating vector. Therefore, compared to the existing SLC schemes designed for a specific system in a dedicated manner, the proposed scheme can be applied to various MIMO-HARQ systems, similar to bit-level combining (BLC). In addition, by employing a low-complexity correction step for the KF operation, the computational complexity of the proposed scheme is lower than that of existing SLC schemes and is comparable to that of BLC. Simulation results and analyses confirm that the proposed scheme outperforms BLC and achieves near-identical error performance to the LMMSE-based direct SLC scheme with a brute-force aggregation of all related information up to the current TTI for the transmitted packet(s).