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为了提升高信噪比情况下次优检测算法的检测性能,在一层遍历搜索的排序串行干扰消除算法(ML-OSIC)的基础上引入格规约技术,提出一种新的格规约辅助检测算法(ML-LLL-OSIC).该算法首先对噪声干扰最小的子信道信号进行遍历检测,然后利用格规约技术处理剩余子信道矩阵以改善信道矩阵的正交性,最后利用改进的信道矩阵进行排序串行干扰抵消检测.上述算法既减少了遍历检测搜索次数,又改善了信道矩阵的正交性,可更加有效地避免层间干扰和误码扩散.仿真结果表明,在多用户多入多出系统(MU-MIMO)中,QPSK调制方式下信噪比大于10d B时,或16QAM调制方式下信噪比大于14d B时,本算法可以获得接近ML算法的检测性能.
In order to improve the detection performance of next-best detection algorithm with high signal-to-noise ratio (SNR), a lattice-approximation technique is introduced based on the ML-OSIC algorithm of a layer of traversal search. Algorithm (ML-LLL-OSIC). This algorithm firstly traverses the sub-channel signal with the least noise interference and then uses the lattice approximation technique to process the remaining sub-channel matrix to improve the orthogonality of the channel matrix. Finally, the improved channel matrix Order serial interference cancellation detection.The algorithm not only reduces the number of traversal detection and search, but also improves the orthogonality of the channel matrix, which can effectively avoid inter-layer interference and bit error diffusion.The simulation results show that in multi-user multi-access In the MU-MIMO, the SNR of QPSK modulation is more than 10d B, or the signal-to-noise ratio of 16QAM is greater than 14d B, this algorithm can get the detection performance close to ML algorithm.