低复杂度大规模MIMO检测算法的研究

发布时间：2018-06-07 18:44

本文选题：大规模MIMO + 检测算法　；参考：《西安电子科技大学》2014年硕士论文

【摘要】：在发送端和接收端都有多根天线的MIMO系统由于其在发射分集和数据速率等方面的优势,变得越来越受欢迎,从而发展到今天已经相当成熟了。而为了进一步提高频谱效率和信道容量,提出了以大型阵列天线代替原来的几根天线的大规模MIMO系统。目前对大规模MIMO系统的研究尚处于起步阶段,而接收端的检测技术作为MIMO系统的一个重要组成部分,对其检测算法的研究将会极大地推动对大规模MIMO研究的发展。传统MIMO系统的检测算法包括ZF、MF、MMSE和ZF-SIC等算法。其中球形检测算法在以高复杂度为代价的基础上可以获得近似ML检测的性能。而本文研究的大规模MIMO系统的发射天线和接收天线数量可以达到数十乃至数百根,若采用传统的MIMO检测算法,其检测复杂度将会变得难以忍受,因此寻找适用于大规模MIMO系统的低复杂度的检测算法成为关键。本文首先介绍了大规模MIMO技术的研究背景和研究现状,指明了全文的研究方向。接着对大规模MIMO系统进行了简单的介绍。主要简单地分析了大规模MIMO系统的总速率上界问题,探讨了大规模MIMO系统的关键技术,主要包括信道估计技术、下行预编码和上行检测技术,从技术特点和研究现状两个方面进行了介绍。同时还讨论了大规模MIMO系统未来有待进一步研究的难点和热点问题。本文重点对低复杂度的大规模MIMO的检测算法进行了研究。详细介绍了基于本地邻域搜索的似然上升搜索(LAS)检测算法的基本原理和实现过程。接着从三个方面分析了LAS算法的复杂度,并在不同SNR或者不同天线数的条件下对LAS算法的检测性能进行了仿真验证。然后介绍了一种基于LAS的MOS-LAS算法,该算法通过生成多个不同的局部最小点并从中找出最优值的方式达到了改善的目的。根据生成局部最小点的方式不同又细分为MIV-LAS算法和MSCS-LAS算法。本文对MIV-LAS算法和MSCS-LAS算法的思想进行了详细地介绍,并通过仿真验证了算法的有效性。最后还介绍了另外用一种低复杂度的主动禁忌搜索(RTS)检测算法。本文详细阐述了RTS算法的算法原理和实现过程,并从算法原理和复杂度等方面将RTS算法和LAS算法进行了全面地比较,并通过仿真验证了RTS算法的检测性能,得出了RTS算法的检测性能优于LAS算法的结论。
[Abstract]:The MIMO system, which has multiple antennas at both the transmitter and receiver, is becoming more and more popular because of its advantages in transmitting diversity and data rate, and it has become quite mature today. In order to further improve the efficiency of the spectrum and the capacity of the channel, a large array antenna is proposed to replace the original antennas. At present, the research on large-scale MIMO system is still in the beginning stage, and the detection technology of the receiver is an important part of the MIMO system. The research on its detection algorithm will greatly promote the development of large-scale MIMO research. The detection algorithms of the traditional MIMO system include the algorithms of ZF, MF, MMSE and ZF-SIC. Among them, the sphere of detection of the MIMO system includes the algorithms of the MF, MMSE and ZF-SIC. Shape detection algorithm can obtain approximate ML detection performance on the basis of high complexity, and the number of transmitting antenna and receiving antenna of large-scale MIMO system can reach tens or hundreds of roots. If the traditional MIMO detection algorithm is used, the detection complexity will become unbearable, so the search is suitable for large scale. The key to the low complexity detection algorithm of scale MIMO system is the key. This paper first introduces the research background and research status of large-scale MIMO technology, points out the research direction of the full text, and then briefly introduces the large-scale MIMO system. It mainly analyzes the total rate upper bound problem of large-scale MIMO system, and discusses the big rules. The key technologies of the modular MIMO system, including channel estimation, downlink precoding and uplink detection, are introduced from two aspects of technical characteristics and research status. At the same time, the difficulties and hot issues to be further studied in the future of large-scale MIMO systems are also discussed. This paper focuses on the detection of large scale MIMO with low complexity. The basic principle and implementation process of the likelihood ascending search (LAS) detection algorithm based on local neighborhood search are introduced in detail. Then the complexity of the LAS algorithm is analyzed from three aspects, and the detection performance of the LAS algorithm is verified under the conditions of different SNR or different antenna numbers. Then a kind of method is introduced. Based on the MOS-LAS algorithm of LAS, the algorithm achieves the goal of improving by generating a number of different local minimum points and finding the optimal value from it. According to the different ways of generating the local minimum points, the algorithm is subdivided into MIV-LAS and MSCS-LAS algorithms. This paper introduces the ideas of MIV-LAS and MSCS-LAS algorithms in detail. The effectiveness of the algorithm is verified by over simulation. Finally, a low complexity active tabu search (RTS) detection algorithm is also introduced. This paper expounds the algorithm principle and implementation process of the RTS algorithm in detail, and compares the RTS algorithm with the LAS algorithm in the aspects of the principle and complexity of the algorithm, and verifies the RTS through simulation. The detection performance of the algorithm shows that the detection performance of the RTS algorithm is better than that of the LAS algorithm.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN919.3

【相似文献】