基于索引调制的宽带MIMO-OFDM无线传输技术研究

发布时间：2018-01-30 01:34

本文关键词： 正交频分复用多输入多输出索引调制峰均比带外辐射　出处：《电子科技大学》2016年硕士论文　论文类型：学位论文

【摘要】：基于索引调制的OFDM(Orthogonal Frequency Division Multiplexing with Index Modulation,OFDM-IM)技术是近年来提出的一种新型多载波方案,它具备频谱效率高、抗多径效应强等特性,并且相较于传统的OFDM,可以在抗载波间干扰方面拥有更突出的优势,因此该技术也成为多载波无线通信的研究方向之一。为了进一步提高系统的频谱利用率和系统容量,本文考虑将OFDM-IM技术与多输入多输出(Multiple Input Multiple Output,MIMO)技术相结合,研究MIMO-OFDM-IM系统的性能。本文主要研究MIMO-OFDM-IM接收机的优化与设计,分别从性能最优和复杂度最优方向提出几种检测算法。另外,针对MIMO-OFDM-IM信号的峰均比(Peak-to-Average Power Ratio,PAPR)高和带外辐射大的缺陷进行优化,并提出次优接收机设计方案。本文的具体工作安排如下:第一章先介绍了基于索引调制的OFDM技术和MIMO技术的研究现状,然后将OFDM-IM技术与OFDM比较,阐述了OFDM-IM的优缺点。第二章主要从性能最优方向提出了针对MIMO-OFDM-IM的三种检测算法,分别是基于距离的检测(Distance-Based ordered Detection,DBD)算法、引入门限判决的DBD改进算法和基于排序的检测算法,并对算法性能进行了仿真。具体地,先总结了MIMO-OFDM-IM的现有的检测算法,分别是最大似然(Maximum Likelihood,ML)检测和对数似然比(Log-likelihood Ratio,LLR)检测,然后针对ML算法复杂度极高、LLR算法性能较差的不足,提出了三种性能较好的检测算法。与LLR算法相比,DBD对块做MMSE均衡,具有更好的BER性能。改进的DBD算法通过引入了一个判决门限,极大程度地降低复杂度。而基于排序的检测算法对载波组合进行了排序,因此能在实现近ML检测性能的同时,大幅度降低了算法复杂度。第三章首先从复杂度最优的角度提出了三种低复杂度接收机,分别是能量检测算法、局部搜索算法和迭代Tabu搜索算法,然后进行了算法性能的仿真和复杂度的分析。能量检测具有最低的复杂度,但检测性能较差。局部搜索算法先通过能量检测得到初始解,然后不断迭代初始解的邻域空间,直至满足终止条件,得到最终的输出。迭代Tabu算法通过修正每一次搜索的邻域解空间,避免了局部搜索算法存在的陷入局部最优解的死循环问题,因此提高了搜索效率。另外,合理地设置终止条件,可以在算法性能和复杂度之间取得平衡。第四章针对MIMO-OFDM-IM信号存在峰均比高和带外辐射大的缺陷,对信号进行PAPR抑制和旁瓣能量抑制,并在接收端对信号进行恢复。第五章总结全文,并指出未来的可能研究方向。
[Abstract]:OFDM based on Index Modulation. Orthogonal Frequency Division Multiplexing with Index Modulation. OFDM-IMC is a new multi-carrier scheme proposed in recent years. It has the characteristics of high spectral efficiency and strong anti-multipath effect, and compared with the traditional OFDM. This technology has become one of the research directions of multi-carrier wireless communication. In order to further improve the system spectrum efficiency and system capacity. This paper considers the combination of OFDM-IM technology and multiple Input Multiple output Mimo technology. The performance of MIMO-OFDM-IM system is studied. The optimization and design of MIMO-OFDM-IM receiver are studied in this paper. Several detection algorithms are proposed from the direction of optimal performance and optimal complexity, respectively. The peak average of MIMO-OFDM-IM signal is higher than that of Peak-to-average Power Power PAPR, and the outband radiation is higher than that of peak-to-average Power PAPR. The main work of this paper is as follows: chapter 1 introduces the research status of OFDM technology and MIMO technology based on index modulation. Then compare OFDM-IM technology with OFDM. The advantages and disadvantages of OFDM-IM are expounded. In chapter 2, three detection algorithms for MIMO-OFDM-IM are proposed from the aspect of performance optimization. Distance-Based ordered Detection (DBD) algorithm is used to detect distance. The improved threshold decision DBD algorithm and the sorting based detection algorithm are introduced, and the performance of the algorithm is simulated. Specifically, the existing detection algorithms of MIMO-OFDM-IM are summarized. Maximum maximum Likelihoodo (MLL) and Log-likelihood Ratio- LLR (Log-likelihood Ratio- LLR) were detected, respectively. Then aiming at the poor performance of ML algorithm with extremely high complexity, three detection algorithms with good performance are proposed. Compared with LLR algorithm, MMSE equalization of block pairs is done. The improved DBD algorithm greatly reduces the complexity by introducing a decision threshold, while the sorting based detection algorithm sorts the carrier combinations. Therefore, the performance of near-ML detection can be achieved while greatly reducing the complexity of the algorithm. In Chapter 3, three low-complexity receivers are proposed from the point of view of optimal complexity, which are energy detection algorithms. Local search algorithm and iterative Tabu search algorithm, then the algorithm performance simulation and complexity analysis. Energy detection has the lowest complexity. But the detection performance is poor. The local search algorithm first obtains the initial solution by energy detection, and then iterates the neighborhood space of the initial solution until the termination condition is satisfied. By modifying the neighborhood solution space of each search, the iterative Tabu algorithm avoids the dead cycle problem in which the local search algorithm falls into the local optimal solution. Therefore, the search efficiency is improved. In addition, the termination condition is set reasonably. There is a balance between the performance and complexity of the algorithm. Chapter 4th aims at the defects of high peak-to-average ratio (PAPR) and high out-of-band radiation in MIMO-OFDM-IM signals. The signal is suppressed by PAPR and sidelobe energy, and the signal is recovered at the receiving end. Chapter 5th summarizes the full text and points out the possible research direction in the future.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TN919.3

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