Research and Implementation of a Hybrid MIMO Detection Algorithm

Multiple-input multiple-output (MIMO) technology plays a crucial role in the field of wireless communications. As one of the key technologies, MIMO signal detection ensures the reliability of communication systems and achieves high throughput transmission. In this paper, to find a high-performance and low-complexity detection algorithm, a hybrid detection algorithm is proposed based on the K-best detection algorithm. The hybrid algorithm employs the minimum mean square error (MMSE) linear detection algorithm combined with sorted QR decomposition (SQRD) for preprocessing, followed by signal detection using the K-best detection algorithm. Compared with the traditional K-best detection algorithm, the proposed method shows significant performance improvement. To address the computational complexity issue caused by the fixed K value in each layer of the hybrid detection algorithm, an adaptive threshold algorithm is introduced to select an appropriate K value for each layer, significantly reducing the algorithm's complexity. On the hardware implementation level, not only is the overall algorithm architecture optimized but a lookup table (LUT) based sorting algorithm is also proposed to address the sorting delay issue in the hybrid detection algorithm. Comprehensive analysis shows that this detector, implemented in a 28-nm process, achieves a throughput of 4.8 Gbps at a clock frequency of 769 MHz, presenting a significant advantage compared with other literature.