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Low complexity MIMO detection algorithm by combining modified OSIC and ML detection

机译:结合改进的OSIC和ML检测的低复杂度MIMO检测算法

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The Ordered Successive Interference Cancellation (OSIC) algorithm has the advantage of high capabilities. Moreover, as compared to Maximum Likelihood Detection it has poor performance but its error rate is expected. The OSIC algorithm complexity is based on matrix inversion. In this paper, an improved OSIC algorithm is proposed, that uses a parallel detection and an accurate detection value of combining programs while maintaining performance with the slight reduced computational complexity. Considering the error propagation of the traditional OSIC algorithm, modified OSIC and ML detection algorithm are merged, the use of exhaustive search ML method is to improve the overall performance. In order to avoid the computational complexity of ML algorithm, “k” symbols are selected to be detected by the modified OSIC. The remaining symbols are detected by ML detection. The simulations are performed in MATLAB and it shows that the performance of the proposed algorithm is better than the conventional OSIC algorithm.
机译:有序连续干扰消除(OSIC)算法具有功能强大的优势。此外,与最大似然检测相比,它的性能较差,但可以预期其错误率。 OSIC算法的复杂性基于矩阵求逆。本文提出了一种改进的OSIC算法,该算法使用并行检测和组合程序的准确检测值,同时在保持性能的同时略微降低了计算复杂度。考虑到传统OSIC算法的错误传播,将改进的OSIC算法和ML检测算法融合在一起,使用穷举搜索ML方法可以提高整体性能。为了避免ML算法的计算复杂性,选择“ k”个符号以由修改后的OSIC检测。其余符号通过ML检测进行检测。在MATLAB中进行了仿真,结果表明该算法的性能优于传统的OSIC算法。

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