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多用户MIMO系统中的预编码技术研究

Research on Precoding Technologies for Multiuser MIMO System

【作者】 周良

【导师】 李晓辉;

【作者基本信息】 西安电子科技大学 , 通信与信息系统, 2011, 硕士

【摘要】 MIMO系统是指收发端各自拥有多根天线的系统。在不增加带宽和发送功率的情况下,MIMO可以成倍地提高无线信道容量,改善系统性能,因此成为无线通信领域的关键技术之一。多用户MIMO预编码技术是MIMO系统中的一项重要技术,它通过在发射端对信号进行预处理以消除多用户干扰、降低误码率或提高系统容量。本文从线性预编码、非线性预编码以及二者的结合三个方面对多用户MIMO系统中的预编码技术进行研究:首先,建立了适合各种预编码方案的系统模型,并在此基础上研究了多种经典的预编码算法。然后,基于信漏噪比(SLNR)思想,提出了适用于任意用户和天线配置的迭代SLNR算法。重点研究了使用施密特信道正交化(CO)代替传统矩阵分解的方法,提出了低复杂度的CO算法和考虑噪声影响的CON算法。为了进一步消除CO算法中的剩余干扰,本文还提出了结合CO和THP的CO-THP算法。最后,通过性能仿真将所提算法与其他算法进行了分析比较,验证了所提算法的有效性。

【Abstract】 Multi-input multi-output (MIMO) system, a system implemented with multiple transmit antennas and multiple receive antennas, which can exponentially increase wireless channel capacity without extra frequency band and transmit power, is proved to be a key technique in wireless communication system. Multiuser MIMO precoding is an important technique in MIMO system, which is developed to eliminate the multiuser interference (MUI), decrease the bit error rate (BER) or increase the capacity through processing at the transmitter.This dissertation researches on the precoding technologies for multiuser MIMO system through three aspects of linear precoding, nonlinear precoding and the combination of them. Firstly, the linear, nonlinear and the combining system model are constructed, on which some classical precoding schemes are studied. Secondly, based on the concept of SLNR (signal-to-leakage-and-noise ratio), an iterative SLNR algorithm suitable for any antenna configuration is proposed. With the conventional matrix decomposition replaced by Schmidt Orthogonalization method, a CO (channel orthogonalization) algorithm and its improved algorithm CON (CO with Noise) are proposed latter. Then, to eliminate the residual interference in CO, the combination of CO and THP (CO-THP) is proposed. Finally, simulation results are given to compare the proposed algorithms with the other algorithms in the literature to verify their effectiveness.

【关键词】 多输入多输出预编码多用户干扰信道正交化
【Key words】 MIMOPrecodingMUICO
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