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Efficient SOR Based Massive MIMO Detection Using Chebyshev Acceleration

机译:使用Chebyshev加速的高效基于SOR的大规模MIMO检测

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Massive multiple-input multiple-output (MIMO) is considered as one of the key techniques in today's 5G wireless communication systems. Though massive MIMO can achieve higher data rate and spectral efficiency compared with small-scale MIMO, its high complexity becomes a problem when hundreds of antennas are equipped. For uplink massive MIMO detection, conventional schemes like zero forcing (ZF) and minimum mean square error (MMSE) are prohibitive due to the unaffordable complexity. To this end, successive over relaxation (SOR) detection is proposed, which iteratively approaches the performance of MMSE with much lower complexity. However, the performance of SOR is often unsatisfactory enough especially in some ill channel conditions. For a better compromise between performance and complexity, Chebyshev-SOR detection is proposed in this paper. Using Chebyshev acceleration, the proposed method can achieve faster convergence and better performance than conventional SOR, especially in ill channel conditions. Numerical results with different channel conditions are given in detail, which show that Chebyshev-SOR method achieves 5dB gain with little complexity overhead. Computational complexity comparison is also given in this paper.
机译:大规模多输入多输出(MIMO)被认为是当今5G无线通信系统中的关键技术之一。尽管与小规模MIMO相比,大规模MIMO可以实现更高的数据速率和频谱效率,但是当配备数百个天线时,其高复杂度成为一个问题。对于上行链路大规模MIMO检测,由于难以承受的复杂性,像零强制(ZF)和最小均方误差(MMSE)这样的常规方案是禁止的。为此,提出了连续过度松弛(SOR)检测,该检测以较低的复杂度迭代地接近MMSE的性能。但是,SOR的性能通常不能令人满意,特别是在某些不良信道条件下。为了更好地兼顾性能和复杂性,本文提出了Chebyshev-SOR检测。使用Chebyshev加速,与传统的SOR相比,所提出的方法可以实现更快的收敛和更好的性能,尤其是在不良信道条件下。详细给出了不同信道条件下的数值结果,结果表明,Chebyshev-SOR方法实现了5dB的增益,且开销很小。本文还给出了计算复杂度的比较。

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