Abstract
Due to the growing demands of high-dimension multiple-input multiple-output (MIMO) systems, the preprocessing of sorted-QR decomposition becomes one of the computational bottlenecks in the QR-based MIMO detection, and the power consumption and computation complexity of the MIMO detector are growing dramatically. This thesis proposes an 8 × 8 MIMO detector which can be divided into two parts. First, the proposed Givens-Rotation-based algorithm aims to improve the throughput and the hardware utilization efficiency by stopping the sorting operations earlier or relaxing the sorting condition for the parallel sorted-QR decomposition. The detection performance degradation is negligible and better hardware efficiency can be obtained for the larger number of the MIMO antennas. Then, we propose an 8 × 8 mixed K-best/QR-SIC detector with the proposed modified sorted-QR decomposition as the preprocessing. The modified sorted-QR decomposition is used to relax the sorting condition to improve the latency and the hardware utilization rate. Compared to the K-best detector, the proposed mixed K-best/QR-SIC detector can achieve lower computation complexity with almost no performance loss in the high-dimension MIMO detection.