下一代无线通信MIMO检测技术的研究

发布时间：2018-06-08 05:35

本文选题：多输入多输出检测 + 低复杂度检测算法　；参考：《南京林业大学》2016年硕士论文

【摘要】：无线通信的发展趋势代表了人类对通信速率的渴求,从低速的2G网络到如今高速的4G网络,各种技术被提出以在有限的频谱资源下获得高数据传输速率。其中,多输入多输出(MIMO)技术被广泛应用于最新的无线通信标准,并成为无线通信系统的关键技术之一。MIMO为系统提供分集增益和空分复用增益。MIMO技术主要靠增加收发天线的个数而非增加传输的带宽来实现复用,然而,多天线机制导致了信号处理复杂度的提高,因此对于MIMO系统,MIMO符号检测器的超大规模集成电路(VLSI)实现是接收机设计所面临的主要挑战。本文首先对MIMO系统中现有的几种经典的检测算法进行了归纳总结,并针对各自存在的优缺点进行了详细分析。针对MIMO检测算法实现复杂度高的问题,本文提出了一种分层结构低复杂度非线性检测算法并给出了其架构设计。该算法采用分层处理方法,支持并行硬件电路实现,有效提高了检测效率。在建立系统仿真模型的基础上,分析比较了串行干扰消除算法、球形译码和分层低复杂度算法的误码率性能及复杂度,同时实现算法的参数选择,最终对算法的核心算子进行提取以及定量分析。仿真结果表明,提出的低复杂度MIMO检测算法能以较低的运算复杂度,达到逼近最大似然译码算法的误码率性能,在性能和复杂度之间达到平衡。该算法为MIMO无线通信接收机的VLSI实现提供了理论基础,可应用于多标准无线接收机系统。
[Abstract]:The development trend of wireless communication represents the human desire for the communication rate. From the low-speed 2G network to the high-speed 4G network, various technologies have been proposed to obtain high data transmission rate under the limited spectrum resources. Among them, multi-input and multi-output MIMO-technology is widely used in the latest wireless communication standards. MIMO is one of the key technologies of wireless communication system. MIMO provides diversity gain and space-division multiplexing gain. MIMO technology mainly realizes multiplexing by increasing the number of transceiver antennas rather than the bandwidth of transmission. The complexity of signal processing is increased due to the multi-antenna mechanism, so the implementation of VLSI-based VLSIs for MIMO system MIMO symbol detectors is a major challenge in receiver design. In this paper, several classical detection algorithms in MIMO systems are summarized, and their advantages and disadvantages are analyzed in detail. Aiming at the problem of high complexity of MIMO detection algorithm, this paper presents a hierarchical structure low complexity nonlinear detection algorithm and its architecture design. The algorithm uses hierarchical processing method to support the implementation of parallel hardware circuit and effectively improves the detection efficiency. Based on the system simulation model, the BER performance and complexity of serial interference cancellation algorithm, spherical decoding algorithm and layered low complexity algorithm are analyzed and compared, and the parameter selection of the algorithm is realized at the same time. Finally, the core operator of the algorithm is extracted and quantitatively analyzed. Simulation results show that the proposed low complexity MIMO detection algorithm can achieve the BER performance of approximate maximum likelihood decoding algorithm with low computational complexity and achieve a balance between performance and complexity. The algorithm provides a theoretical basis for VLSI implementation of MIMO wireless communication receivers and can be applied to multi-standard wireless receiver systems.
【学位授予单位】：南京林业大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TN919.3

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