MIMO systems exploit multi-path propagation in a rich broadcast environment to improve throughput and performance of digital communication systems. The correspondent demappers require additional computational complexity. In this paper, a new detection-decoding approach based on vertical shuffle scheduling is proposed. Space exploration for the maximum likelihood detection is reduced to a dynamic region that surrounds the received symbol. Thus, a dynamic approach is proposed to detect the closest point of the channel observation without calculating all the candidate symbols in a constellation. In addition, a novel method based on EXIT chart study is proposed to find the sufficient number of neighboring points to search around a local minimum and then compute by recursion their Euclidean distances. Compared to the conventional Maximum Likelihood detector, the proposed algorithm allows a reduction in the computational complexity, in terms of number of multiplication, reaching 98 %. The simulation results show that the proposed algorithm outperforms the state-of-the-art algorithms like MMSE, sphere decoding, DBTC and DaVinci codes.

MIMO 系统在丰富的广播环境中利用多径传播来提高数字通信系统的吞吐量和性能。相应的解映射器需要额外的计算复杂度。在本文中，提出了一种新的基于垂直混洗调度的检测-解码方法。最大似然检测的空间探索减少到围绕接收符号的动态区域。因此，提出了一种动态方法来检测信道观察的最近点，而无需计算星座中的所有候选符号。此外，提出了一种基于 EXIT 图研究的新方法，以找到足够数量的相邻点来搜索局部最小值，然后通过递归计算它们的欧几里德距离。与传统的最大似然检测器相比，所提出的算法允许在乘法次数方面降低计算复杂度，达到 98%。仿真结果表明，所提出的算法优于最先进的算法，如 MMSE、球体解码、DBTC 和达芬奇码。