正交幅度调制误码率仿真及程序效率比较

通信工程论文编号:TX303  论文字数:10368,页数:32

目录
摘要 I
ABSTRACT II
第1章 引言 1
 1.1 背景 1
 1.2 研究内容 1
第2章 正交幅度调制(Quadrature Amplitude Modulation) 3
 2.1 什么是QAM 3
 2.2 QAM调制 3
 2.3 QAM的解调与检测 4
 2.4 QAM的误码率性能 5
 2.5 正交幅度调整的优点与缺点 6
第3章 MATLAB下如何对QAM仿真进行效率优化 7
 3.1 对仿真程序进行效率优化的必要性 7
 3.1.1 M文件简介 7
 3.1.2 循环向量化编程 7
 3.2 如何优化仿真效率及其步骤 10
 3.2.1 分析代码的运行状况 10
 3.2.2 循环矩阵化 10
 3.2.3 预先定义变量 11
 3.2.4 内存的管理 12
 3.2.5 其他方法介绍 12
 3.3 难以采用矩阵算法的类型 13
第4章 利用MATLAB进行16QAM误码率仿真 14
 4.1 矩形16QAM的误码率和误比特率仿真程序改造 14
 4.2 程序效率比较 16
 4.3 程序效率比较结果 17
 4.4 MATLAB 图形用户界面编程 18
第5章 结束语 19
致谢 20
参考文献 21
附录 源代码 22

摘要

 常用数字调制方式有振幅键控、相移键控、差分相移键控、频移键控和正交幅度调制（QAM）。每一种调制技术在特定的工作环境中都有各自的优势和缺点。 由于QAM的高带宽效率而被广泛应用于有线和无线通讯中。当QAM误码性能的理论分析特别困难的时候，我们可以对其进行蒙特卡洛仿真。蒙特卡洛仿真需要产生大量的随机数据和高斯白噪声，按照一般的编程习惯，例如C或Fortran语言的编程，仿真编程通常都使用循环进行运算。然而，MATLAB是一种基于矩阵运算的编程语言，它的矩阵运算效率要远高于循环。因此，传统的编程方式并不能完全的发挥出MATLAB的效率。用矩阵运算替代循环能大大提高仿真效率。
 本文第一章介绍了研究课题的背景和主要内容。第2章介绍了QAM及其误码性能的分析。在第3章中，我们研究对MATLAB编程的改善以减少执行时间的一些技巧。在第4章中，我们对16QAM误码性能的仿真程序进行修改和完善。由对比表示出，仿真的时间大大减少。我们还利用MATLAB进行便于执行和比较的一个实用的用户图形用户界面（GUI）编程。第5章则为结论。

关键词：误码率，仿真效率，16QAM，MATLAB

ABSTRACT
 Commonly digital modulation schemes are amplitude shift keying, phase shift keying, differential phase shift keying, frequency shift keying and quadrature amplitude modulation (QAM). Each modulation technique has its advantages and disadvantages in a certain working environment.  QAM is widely used in wired and wireless communication due to its high bandwidth efficiency. In general, the error performance of QAM is obtained via Monte Carlo simulation, especially when analytical analysis is difficulty. A large number of random data and additive white Gaussian noise (AWGN) samples need to be generated. Iterations are often used as a programming habit of languages like C or Fortran.  MATLAB however, is a matrix based programming language. It is more efficient in matrix computation than iterations. Therefore, the conventional programming using iterations results in long execution time. Simulation efficiency is greatly improved, when iterations are replaced by matrix computation.
 This thesis starts with a general introduction of the research topic in chapter 1. Chapter 2 gives an introduction of QAM and its error performance analysis. In chapter 3, we look into general scenarios where execution time can be reduced by improvement in MATLAB programming. In chapter 4, a conventional 16QAM error performance simulation program is modified and improved. Comparisons show that the simulation time is greatly reduced. We also programmed a user-friendly Graphic User Interface (GUI) in MATLAB for easy execution and comparison. Conclusions are made in chapter 5.
Keywords: BER, Simulation efficiency, 16QAM, MATLAB