基于LR-MMSE的MIMO系统检测算法研究

发布时间：2018-05-09 15:20

  本文选题：最小均方差 + 格约减　； 参考：《南京信息工程大学》2016年硕士论文

【摘要】：多输入多输出(MIMO)技术是无线通信领域的一个重要突破,空间复用和空间分集技术使得空间资源得到充分利用,控制了信道衰减。MIMO技术在保证系统带宽和发射功率的前提下,大大提高了频谱使用效率和信道容量。信号检测技术却对MIMO技术在无线通信中的运用产生了影响,所以本文在一些传统检测算法的基础上,对改进的检测算法进行了深入分析,并在性能和复杂度之间取得了良好的折衷点。主要工作如下：第一,对MIMO模型的概念进行分析,详细概述了MIMO信道的原理和MIMO系统的传统检测算法,对MIMO检测的改进算法进行了深入分析。由于传统检测算法在性能和复杂度之间这种间存在局限,进一步介绍了格约减(LR)技术,主要介绍了对偶格(DLR)算法。在此基础上结合格约减技术与传统检测算法,使得这些次优、低复杂度的传统检测算法性能有明显地改善。第二,串行排序干扰消除(OSIC)算法在信号迭代检测过程中需重复求伪逆,使得计算复杂度会比较高。为了改善这一问题,本文提出了一种改进的算法一噪声投影按序逐次消除((OSNPC)算法,而且DLR辅助的OSNPC算法省去了对偶格约减基的求逆运算,使得复杂度大大降低。由于OSNPC算法每次迭代优先选择信噪比最大的符号来检测,而信号正确性其实应取决于当前的噪声样本,所以又提出了一种改进的Improved-OSNPC算法,与DLR结合时,检测性能有了明显提高,复杂度基本没变化。第三,仿真各种检测算法。首先仿真了MIMO传统检测算法误码率性能曲线,并分析复杂度情况。然后仿真了格约减辅助的检测算法曲线,并与传统检测算法进行比较。最后仿真了两种改进算法的性能曲线,利用仿真实验数据给上节理论推导提供数据支持,并且验证了两种改进方案的合理性和可行性。
[Abstract]:Multi-input-multiple-output (MIMO) technology is an important breakthrough in the field of wireless communication. Spatial multiplexing and spatial diversity technology make full use of space resources and control the channel attenuation. MIMO technology can guarantee the system bandwidth and transmit power. The spectrum efficiency and channel capacity are greatly improved. Signal detection technology has an impact on the application of MIMO technology in wireless communication, so this paper analyzes the improved detection algorithm on the basis of some traditional detection algorithms. A good compromise point between performance and complexity is obtained. The main work is as follows: first, the concept of MIMO model is analyzed, the principle of MIMO channel and the traditional detection algorithm of MIMO system are summarized in detail, and the improved algorithm of MIMO detection is deeply analyzed. Due to the limitation between the performance and complexity of the traditional detection algorithm, the lattice reduction (LR) technique is further introduced, and the dual lattice reduction (DLR) algorithm is mainly introduced. On the basis of this, the performance of these sub-optimal and low-complexity traditional detection algorithms is improved obviously by combining the lattice reduction technique with the traditional detection algorithm. Second, the serial sorting interference cancellation (SSI) algorithm requires repeated pseudo-inversion in the signal iterative detection process, which makes the computational complexity higher. In order to improve this problem, this paper proposes an improved algorithm, noise projection successive elimination (OSNPC) algorithm, and the DLR assisted OSNPC algorithm eliminates the inverse operation of the reduced basis of dual lattice, which greatly reduces the complexity. Because the OSNPC algorithm preferentially selects the symbol with the largest signal-to-noise ratio (SNR) for each iteration, and the accuracy of the signal should depend on the current noise samples, an improved Improved-OSNPC algorithm is proposed. When combined with DLR, the detection performance is obviously improved. The complexity is basically the same. Third, simulation of various detection algorithms. First, the BER performance curve of the traditional MIMO detection algorithm is simulated, and the complexity is analyzed. Then the algorithm curve is simulated and compared with the traditional detection algorithm. Finally, the performance curves of the two improved algorithms are simulated, and the rationality and feasibility of the two improved algorithms are verified by using the simulation experimental data to provide data support for the theoretical derivation of the above section.
【学位授予单位】：南京信息工程大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TN919.3
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本文编号：1866529