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A novel low complexity maximum likelihood detection algorithm for MIMO WLAN system

机译:一种用于MIMO WLAN系统的新型低复杂度最大似然检测算法

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In this paper, we propose a low complexity algorithm for the maximum likelihood detection (MLD) of MIMO systems. Our algorithm separates the In-phase and Quadrature-phase components of a complex signal into two independent real numbers before calculating the Euclidean distance. Whereby, it is able to determine the closest constellation points directly without: 1) searching all of the candidates and 2) sorting all the results as the well-known K-Best sphere decoding (KSD) does. Consequently, its complexity becomes insignificantly affected by the size of the constellation. We simulate the IEEE 802.11 ac system by using the proposed algorithm and other MIMO decoder types such as Linear MMSE, BLAST-MMSE, LRA-MMSE, and KSD. The Bit Error Rate (BER) performance and complexity are exposed and compared. The paper shows that the proposed algorithm significantly reduces the complexity with an insignificant degradation of BER performance as compare to the KSD.
机译:在本文中,我们提出了一种用于MIMO系统的最大似然检测(MLD)的低复杂度算法。在计算欧几里德距离之前,我们的算法将复信号的同相和正交分量分成两个独立的实数。从而,它能够直接确定最接近的星座点,而无需:1)搜索所有候选者,以及2)像众所周知的K-最佳球形解码(KSD)那样对所有结果进行排序。因此,其复杂度不受星座图大小的影响很小。我们使用提出的算法和其他MIMO解码器类型(例如,线性MMSE,BLAST-MMSE,LRA-MMSE和KSD)对IEEE 802.11 ac系统进行仿真。公开并比较了误码率(BER)的性能和复杂性。本文表明,与KSD相比,所提出的算法显着降低了复杂性,并且BER性能无明显降低。

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