大规模MIMO系统中低复杂度检测算法的研究及优化

发布时间：2018-04-21 02:31

本文选题：大规模MIMO + 线性检测算法　；参考：《南京邮电大学》2017年硕士论文

【摘要】：随着移动互联网的蓬勃发展,移动数据量和接入设备数剧增,3G/4G所提供的服务已渐渐不能满足人们的需求,关于5G技术的研究正在如火如荼地展开。大规模MIMO技术作为未来5G移动通信的关键技术,通过增加基站天线数,大幅度提高了系统频谱效率和能量效率。然而随着基站天线数的不断增加,接收端信号检测的复杂度也不断增大,成为大规模MIMO进一步应用于实际的瓶颈问题。为此,本文对大规模MIMO系统中上行链路的检测算法进行了研究,包括线性检测算法和低复杂度的非线性检测算法,并重点分析了一种适用于高阶调制大规模MIMO系统的EP检测算法。本文首先利用大规模MIMO系统模型,对线性检测算法MRC、ZF以及MMSE进行了分析和比较。研究表明,当基站接收天线数目远远大于发送天线数目并且不断增加至无穷时,信道会出现两两正交特性,此时,最简单的线性处理技术就可以达到最优检测性能。但是,这种方法收敛较慢,且在实际应用中发送天线数目和接收天线数目往往相差不大。所以针对适用于大规模MIMO系统的低复杂度非线性检测算法的研究依然很有必要的。其次,本文简化单用户系统模型,假设m(28)n,重点研究了一种基于期望传播(EP)的适用于高阶调制大规模MIMO系统的低复杂度、高精度的信号检测算法,该算法通过构造高斯树逼近后验概率p(7)u y(8)来检测信号。本文对EP算法原理和计算复杂度进行了深入研究,并将EP算法与MMSE-SIC、GTA-SIC检测算法进行了比较。研究表明,EP算法具有健壮性和快速性,不管系统的基站天线数或者调制阶数是多少,EP算法总能在性能上远远优于GTA-SIC和MMSE-SIC,而在计算复杂度方面仅仅提高了几倍。
[Abstract]:With the rapid development of mobile Internet, the service provided by 3G / 4G has been unable to meet the needs of people. The research on 5G technology is being carried out in full swing. As the key technology of 5G mobile communication in the future, the large-scale MIMO technology can greatly improve the spectral efficiency and energy efficiency of the system by increasing the number of base station antennas. However, with the increase of the number of base station antennas, the complexity of signal detection at the receiving end is also increasing, which becomes the bottleneck of large-scale MIMO application in practice. Therefore, this paper studies the uplink detection algorithms in large-scale MIMO systems, including linear detection algorithms and low complexity nonlinear detection algorithms. An EP detection algorithm for high order modulation large scale MIMO systems is analyzed. In this paper, a large scale MIMO system model is used to analyze and compare the linear detection algorithms MRCZF and MMSE. The results show that when the number of receiving antennas is much larger than the number of transmitting antennas and increasing to infinity, the channel will have the characteristic of being orthogonal to each other. In this case, the most simple linear processing technique can achieve the optimal detection performance. However, the convergence of this method is slow, and the number of transmitting antennas and receiving antennas is not always different in practical applications. Therefore, it is necessary to study the low complexity nonlinear detection algorithm for large scale MIMO systems. Secondly, this paper simplifies the single-user system model, assumes that map28n, and focuses on a low-complexity and high-precision signal detection algorithm for high-order modulation large-scale MIMO systems, which is based on the expected Propagation Episode (EPV). The algorithm detects signals by constructing a posterior probability of Gao Si tree approximation. In this paper, the principle and computational complexity of EP algorithm are deeply studied, and the comparison between EP algorithm and MMSE-SIC-GTA-SIC detection algorithm is made. The results show that the algorithm is robust and fast. No matter what the number of base station antennas or modulation orders of the system is, the performance of the EP algorithm is far better than that of GTA-SIC and MMSE-SICs, but the computational complexity is improved only a few times.
【学位授予单位】：南京邮电大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN919.3

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