社会的发展对无线通信技术提出了越来越高的要求，MIMO技术因具有获得空间复用增益以及分集增益的优势，以及能提高信道容量、通信信道链路可靠性的能力，而日益运用于现今主流无线通信技术标准中。Large MIMO系统由于其收发两端配置了数十甚至上百根的天线，能大幅度提高数据速率和分集增益而逐渐成为研究热点。但是由于天线数的大幅度增加，采用MIMO常规检测技术进行检测时复杂度会大大增加，检测性能也存在退化现象，因此检测技术已经成为了限制Large MIMO系统应用的瓶颈。本文主要研究低复杂度高性能且适用于Large MIMO Systems检测的检测算法。

本文首先从整个系统的角度给出了MIMO系统的数学建模，然后分析了不同场景的MIMO系统信道容量，说明了MIMO技术的优越性。接着分析了MIMO系统中的一些常用常规检测方法，包括最大似然检测ML，匹配滤波器MF，迫零ZF检测，最小均方误差MMSE检测等线性检测方法，ZF-SIC和MMSE-SIC等非线性检测方法以及这些算法的排序改进，另外，简单介绍了LR-Aided线性检测方法和球形解码。之后本文分析了Large MIMO Systems中基于禁忌搜索的低复杂度检测方法，包括禁忌搜索算法RTS，分层禁忌搜索算法LTS，以及排序分层禁忌搜索算法ZF-OLTS。最后，针对ZF-OLTS算法进行了两点改进，改进算法MMSE-OLTS采用MMSE解向量代替ZF解向量作为检测算法的初始解向量，以及采用具有更低复杂度的排序方法，在不损失算法的检测性能前提下，降低了算法整体复杂度。

通过对MMSE-OLTS，ZF-OLTS，MMSE-OSIC，ZF-OSIC，MMSE，ZF这几种算法进行仿真，可以看出，在相同的仿真条件下，MMSE-OLTS算法在大幅度降低复杂度的情况下，依然具有较高的检测性能，性能优于ZF-OLTS以及其他算法。另外，仿真证明了MMSE-OLTS算法的检测性能随着天线数增加而有所提高，显示出了其具有适用于大规模天线系统检测的特点，而且该算法在高阶调制时也比常规检测方法更具有优势。

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