双向无线中继信道MIMO-PNC信号检测技术研究
发布时间：2018-10-21 20:38
【摘要】：21世纪初网络编码理论取得了突破性进展,物理层网络编码技术利用了无线环境下电磁波的广播特性,将中继节点也纳入编码的范围,使其不仅仅只具有存储转发功能,从而提高了网络吞吐量并可提高系统的鲁棒性,其在安全性和功率消耗方面也有一定的性能提升。MIMO技术通过在收发两端增加天线的数目形成并行的链路提升网络容量并能够通过分集复用等技术提高可靠性。以上两种技术的结合是本文的研究重点。本文对无线通信领域一个典型的应用场景——双向中继信道模型做了系统的研究,并详细介绍了物理层网络编码技术和映射方案。在阐述该模型的基础上,将MIMO和PNC技术结合应用到双向无线中继信道上,相比于单纯的单天线网络,其在吞吐量和可靠性方面都有更好的性能,但同时更多的天线数目和更加复杂的编码技术也会带来一系列问题,在接收端信号的检测是其中的难点,天线数目越多,信号之间的干扰就越严重,检测时如何减少其他信号的干扰和减少错误传播现象是设计检测算法的关键。传统的MIMO-PNC检测算法包括ZF检测、MMSE检测、SIC检测和ML检测等,ZF和MMSE检测是线性检测算法,算法简单但性能一般,而ML检测虽是最优检测但复杂度过高实用性较差,第四章在串行干扰消除的思想基础上提出了一种新的检测算法QR-GSIC算法,实现了在不显著增加复杂度的基础上提升检测性能,并通过Matlab仿真软件进行了性能分析。格基规约辅助检测在进行信号检测时能够减少信道矩阵的条件数从而减小噪声的干扰,将其中的LLL算法与QR-GSIC算法结合,从抑制噪声方面提高检测性能,并通过仿真验证了改进后的QR-GSIC+LLL算法能够进一步提高QR-GSIC的检测性能。本文从MIMO与PNC出发,以双向无线中继信道为平台,重点研究了MIMO-PNC的适用性,并解决MIMO-PNC在信号检测上的难点,对经典的算法做了回顾并提出了一些改进算法和思路,并通过仿真验证了改进后算法的优良性能。
[Abstract]:At the beginning of the 21st century, network coding theory has made a breakthrough. The physical layer network coding technology takes advantage of the broadcast characteristics of electromagnetic waves in wireless environment and brings the relay nodes into the coding scope, so that it not only has the function of storage and forwarding. Thus, the network throughput is improved and the robustness of the system is improved. MIMO technology enhances network capacity by increasing the number of antennas at both ends of the transmitter and receiver to form parallel links to enhance network capacity and improve reliability through diversity multiplexing. The combination of the above two technologies is the focus of this paper. In this paper, the bidirectional relay channel model, a typical application scene in wireless communication field, is systematically studied, and the physical layer network coding technology and mapping scheme are introduced in detail. Based on this model, the combination of MIMO and PNC technology is applied to two-way wireless relay channel. Compared with the single antenna network, it has better performance in throughput and reliability. But at the same time, more antennas and more complex coding technology will also bring a series of problems, in which the detection of signals at the receiving end is difficult. The more the number of antennas, the more serious the interference between the signals. How to reduce the interference of other signals and reduce the error propagation is the key to design the detection algorithm. Traditional MIMO-PNC detection algorithms include ZF detection, MMSE detection, SIC detection and ML detection. ZF and MMSE detection are linear detection algorithms. In chapter 4, based on the idea of serial interference cancellation, a new detection algorithm, QR-GSIC algorithm, is proposed, which improves the detection performance without significantly increasing the complexity, and analyzes the performance through the Matlab simulation software. In order to reduce the noise interference, the LLL algorithm is combined with the QR-GSIC algorithm to improve the detection performance, which can reduce the condition number of the channel matrix and reduce the noise interference when the signal is detected by the lattice-protocol auxiliary detection, and the algorithm is combined with the QR-GSIC algorithm to improve the detection performance. Simulation results show that the improved QR-GSIC LLL algorithm can further improve the detection performance of QR-GSIC. Based on MIMO and PNC, this paper focuses on the applicability of MIMO-PNC and solves the difficulties in signal detection of MIMO-PNC, and gives a review of the classical algorithms and puts forward some improved algorithms and ideas. The excellent performance of the improved algorithm is verified by simulation.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN919.3
本文编号：2286312
[Abstract]:At the beginning of the 21st century, network coding theory has made a breakthrough. The physical layer network coding technology takes advantage of the broadcast characteristics of electromagnetic waves in wireless environment and brings the relay nodes into the coding scope, so that it not only has the function of storage and forwarding. Thus, the network throughput is improved and the robustness of the system is improved. MIMO technology enhances network capacity by increasing the number of antennas at both ends of the transmitter and receiver to form parallel links to enhance network capacity and improve reliability through diversity multiplexing. The combination of the above two technologies is the focus of this paper. In this paper, the bidirectional relay channel model, a typical application scene in wireless communication field, is systematically studied, and the physical layer network coding technology and mapping scheme are introduced in detail. Based on this model, the combination of MIMO and PNC technology is applied to two-way wireless relay channel. Compared with the single antenna network, it has better performance in throughput and reliability. But at the same time, more antennas and more complex coding technology will also bring a series of problems, in which the detection of signals at the receiving end is difficult. The more the number of antennas, the more serious the interference between the signals. How to reduce the interference of other signals and reduce the error propagation is the key to design the detection algorithm. Traditional MIMO-PNC detection algorithms include ZF detection, MMSE detection, SIC detection and ML detection. ZF and MMSE detection are linear detection algorithms. In chapter 4, based on the idea of serial interference cancellation, a new detection algorithm, QR-GSIC algorithm, is proposed, which improves the detection performance without significantly increasing the complexity, and analyzes the performance through the Matlab simulation software. In order to reduce the noise interference, the LLL algorithm is combined with the QR-GSIC algorithm to improve the detection performance, which can reduce the condition number of the channel matrix and reduce the noise interference when the signal is detected by the lattice-protocol auxiliary detection, and the algorithm is combined with the QR-GSIC algorithm to improve the detection performance. Simulation results show that the improved QR-GSIC LLL algorithm can further improve the detection performance of QR-GSIC. Based on MIMO and PNC, this paper focuses on the applicability of MIMO-PNC and solves the difficulties in signal detection of MIMO-PNC, and gives a review of the classical algorithms and puts forward some improved algorithms and ideas. The excellent performance of the improved algorithm is verified by simulation.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN919.3
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