本文關鍵詞： 正交頻分復用 多輸入多輸出 索引調制 峰均比 帶外輻射　出處：《電子科技大學》2016年碩士論文　論文類型：學位論文

【摘要】：基于索引調制的OFDM(Orthogonal Frequency Division Multiplexing with Index Modulation,OFDM-IM)技術是近年來提出的一種新型多載波方案,它具備頻譜效率高、抗多徑效應強等特性,并且相較于傳統(tǒng)的OFDM,可以在抗載波間干擾方面擁有更突出的優(yōu)勢,因此該技術也成為多載波無線通信的研究方向之一。為了進一步提高系統(tǒng)的頻譜利用率和系統(tǒng)容量,本文考慮將OFDM-IM技術與多輸入多輸出(Multiple Input Multiple Output,MIMO)技術相結合,研究MIMO-OFDM-IM系統(tǒng)的性能。本文主要研究MIMO-OFDM-IM接收機的優(yōu)化與設計,分別從性能最優(yōu)和復雜度最優(yōu)方向提出幾種檢測算法。另外,針對MIMO-OFDM-IM信號的峰均比(Peak-to-Average Power Ratio,PAPR)高和帶外輻射大的缺陷進行優(yōu)化,并提出次優(yōu)接收機設計方案。本文的具體工作安排如下:第一章先介紹了基于索引調制的OFDM技術和MIMO技術的研究現(xiàn)狀,然后將OFDM-IM技術與OFDM比較,闡述了OFDM-IM的優(yōu)缺點。第二章主要從性能最優(yōu)方向提出了針對MIMO-OFDM-IM的三種檢測算法,分別是基于距離的檢測(Distance-Based ordered Detection,DBD)算法、引入門限判決的DBD改進算法和基于排序的檢測算法,并對算法性能進行了仿真。具體地,先總結了MIMO-OFDM-IM的現(xiàn)有的檢測算法,分別是最大似然(Maximum Likelihood,ML)檢測和對數(shù)似然比(Log-likelihood Ratio,LLR)檢測,然后針對ML算法復雜度極高、LLR算法性能較差的不足,提出了三種性能較好的檢測算法。與LLR算法相比,DBD對塊做MMSE均衡,具有更好的BER性能。改進的DBD算法通過引入了一個判決門限,極大程度地降低復雜度。而基于排序的檢測算法對載波組合進行了排序,因此能在實現(xiàn)近ML檢測性能的同時,大幅度降低了算法復雜度。第三章首先從復雜度最優(yōu)的角度提出了三種低復雜度接收機,分別是能量檢測算法、局部搜索算法和迭代Tabu搜索算法,然后進行了算法性能的仿真和復雜度的分析。能量檢測具有最低的復雜度,但檢測性能較差。局部搜索算法先通過能量檢測得到初始解,然后不斷迭代初始解的鄰域空間,直至滿足終止條件,得到最終的輸出。迭代Tabu算法通過修正每一次搜索的鄰域解空間,避免了局部搜索算法存在的陷入局部最優(yōu)解的死循環(huán)問題,因此提高了搜索效率。另外,合理地設置終止條件,可以在算法性能和復雜度之間取得平衡。第四章針對MIMO-OFDM-IM信號存在峰均比高和帶外輻射大的缺陷,對信號進行PAPR抑制和旁瓣能量抑制,并在接收端對信號進行恢復。第五章總結全文,并指出未來的可能研究方向。
[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.
【學位授予單位】：電子科技大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：TN919.3

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