空间调制中信道估计与信号检测算法

发布时间：2018-04-23 18:56

本文选题：空间调制技术 + 信道估计　；参考：《哈尔滨工业大学》2017年硕士论文

【摘要】：近些年来,随着基于多天线的无线通信技术快速的发展,我们的生活已然进入了全新的网络时代,如何利用有限的频谱资源来满足日益增长的用户数量和用户需求已成为当代无线通信发展的难题。在这种环境下,空间调制技术应运而生,它在提高频谱利用率的同时避免了很多普通MIMO中的弊病,该系统的发射天线之间不要求进行同步,而且不会存在信道间的相互干扰问题,因此对于硬件的实现要求比较低,因此空间调制成为一种独特的MIMO传输方式。本文主要研究空间调制下的信道估计与低复杂度信号检测相结合的联合算法,具体研究内容包括:分析传统空间调制与广义空间调制的基本原理,对普通MIMO、传统空间调制、广义空间调制三者的性能进行仿真对比;通过仿真分析传统空间调制下信道估计和信号检测联合算法的性能,分析各种因素对联合算法信道估计性能的影响;考虑到广义空间调制信息序列与训练序列不同,将联合算法进行改进应用于广义空间调制中,使其估计性能得到改善;对传统空间调制下的经典信号检测算法进行仿真,分析各种因素对信号检测性能产生的影响;研究几种低复杂度信号检测算法,对其检测性能进行仿真,并在相同条件下与ML算法进行对比;针对低复杂度检测算法性能不佳的问题,将近似ML算法减小搜索范围的思想与ML算法的搜索方式相结合,既降低了算法复杂度,又提高了检测性能。
[Abstract]:In recent years, with the rapid development of wireless communication technology based on multi-antenna, our life has entered a new network era. How to use the limited spectrum resources to meet the increasing number of users and user needs has become a difficult problem in the development of modern wireless communications. In this environment, spatial modulation technology emerges as the times require. It not only improves the spectrum efficiency, but also avoids the disadvantages of common MIMO. The system does not need synchronization between transmit antennas. Moreover, there is no interference between channels, so the requirement for hardware implementation is relatively low, so spatial modulation becomes a unique MIMO transmission mode. This paper mainly studies the joint algorithm of channel estimation and low complexity signal detection under spatial modulation. The specific research contents include: analyzing the basic principles of traditional spatial modulation and generalized spatial modulation, for ordinary MIMOs, traditional spatial modulation, The performance of generalized spatial modulation is simulated and compared, and the performance of joint channel estimation and signal detection algorithm under traditional spatial modulation is analyzed by simulation, and the influence of various factors on channel estimation performance of joint algorithm is analyzed. Considering that the generalized spatial modulation information sequence is different from the training sequence, the joint algorithm is applied to improve the estimation performance of the generalized spatial modulation, and the classical signal detection algorithm under the traditional spatial modulation is simulated. This paper analyzes the influence of various factors on signal detection performance, studies several low-complexity signal detection algorithms, simulates their detection performance, and compares them with ML algorithm under the same conditions. Aiming at the problem of poor performance of low complexity detection algorithm, combining the idea of approximate ML algorithm to reduce the search range and the search method of ML algorithm, the complexity of the algorithm is reduced and the detection performance is improved.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN919.3

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