Massive MIMO原型系统搭建及信道估计的研究

发布时间：2018-04-08 14:59

本文选题：Massive　切入点：MIMO　出处：《郑州大学》2017年硕士论文

【摘要】：随着移动互联网和大数据时代的到来,下一代通信网络(5G)对传输速率、系统容量、传输时延和系统功耗提出了更加苛刻的要求。面对上千倍数据容量增长、百倍速率提升、百倍用户接入的挑战,5G不仅仅是一次简单的技术的更新,更是一次非常大的跨越性发展、同时也是一次重大变革,这也意味着网络架构必须升级。Massive MIMO技术具有显著提高系统频谱效率、数据传输速率和用户容量以及鲁棒性等优点,被业界公认为5G最有潜力的候选技术之一。原型化在5G发展过程中是一个非常关键的步骤,是推动5G从概念到实现的必备环节。搭建基于软件无线电(SDR,Software Defined Radio)的Massive MIMO原型验证平台是实现5G从理论到应用的重要手段。本文搭建了基于NI软件无线电设备的64天线TDD传输模式的Massive MIMO原型验证平台,并完成了基于USRP-RIO的MIMO-OFDM信道估计的研究,所做的主要工作如下:搭建了Massive MIMO原型验证平台,设计了基站和UE的收发信机软硬件系统。设计搭建Massive MIMO基站软硬件系统,主要编写了基于LabVIEW FPGA的Massive MIMO基站接收端的信道估计(LMMSE、LS)程序和联合调试工作。并对两种信道估计在Massive MIMO平台上的性能做了验证和对比分析;基于LTE10.1协议,搭建了Massive MIMO UE端收发信系统,对UE端系统架构进行了软件设计,主要包括上位机端射频收发模块、基带发送处理模块、基带接收处理模块,以及系统导频结构、帧结构、调制方式等控制信息的设计;最后,联合基站端和UE端对Massive MIMO原型验证平台进行了功能性测试和信道估计算法的验证,最终验证了该平台搭建的正确性和可行性。设计搭建了基于NI USRP-RIO软件无线电平台的2×2 MIMO-OFDM通信系统,并对该系统信道估计进行了研究。重点对该系统的接收模块和发送模块进行了上位机LabVIEW程序的设计,主要包括信道编解码、数字调制与解调、Alamouti编译码、OFDM调制解调、符号同步,信道估计等。然后,搭建了该系统的仿真系统,并对该仿真系统和实际平台下的信道估计算法(LS、DFT-LS)进行了测试和对比分析。测试结果表明,在基于对数距离路径损耗模型的莱斯衰落信道环境下基于DFT的时域LS信道估计要优于频域LS信道估计,这一结果和理论分析相吻合,同时也验证了该系统搭建的正确性。
[Abstract]:With the advent of the era of mobile Internet and big data, the next generation communication network (NGN) has put forward more stringent requirements on transmission rate, system capacity, transmission delay and power consumption.In the face of thousands of times the growth of data capacity, 100 times the speed of 100 times, and the challenge of 100 times user access, 5G is not only a simple technological update, but also a very big leap forward, but also a major change.This means that the network architecture must be upgraded. Massive MIMO technology has the advantages of improving system spectrum efficiency, data transmission rate, user capacity and robustness, and is recognized as one of the most promising candidate technologies for 5G.Prototyping is a very critical step in the development of 5G, which is a necessary step to push 5G from concept to realization.It is an important means to realize 5G from theory to application to build Massive MIMO prototype verification platform based on software radio SDRN software Defined.In this paper, the Massive MIMO prototype verification platform of 64-antenna TDD transmission mode based on NI software radio equipment is built, and the research of MIMO-OFDM channel estimation based on USRP-RIO is completed. The main work is as follows: a Massive MIMO prototype verification platform is built.The hardware and software system of base station and UE transceiver are designed.The hardware and software system of Massive MIMO base station is designed and built. The channel estimation program of Massive MIMO base station receiver based on LabVIEW FPGA and the joint debugging work are mainly written.The performance of the two channel estimators on the Massive MIMO platform is verified and compared. Based on the LTE10.1 protocol, the Massive MIMO UE terminal transceiver system is built, and the UE end system architecture is designed, including the upper computer RF transceiver module.Baseband transmission processing module, baseband receiving processing module, and system pilot structure, frame structure, modulation mode and other control information design; finally,The functional test and channel estimation algorithm of Massive MIMO prototype verification platform are verified by the joint base station and UE terminal. Finally, the correctness and feasibility of the platform are verified.A 2 脳 2 MIMO-OFDM communication system based on NI USRP-RIO software radio platform is designed and built, and the channel estimation of the system is studied.This paper focuses on the design of LabVIEW program for the receiving and transmitting modules of the system, including channel coding and decoding, digital modulation and demodulation, symbol synchronization, channel estimation and so on.Then, the simulation system of the system is built, and the simulation system and the channel estimation algorithm based on the actual platform are tested and compared.The test results show that the time-domain LS channel estimation based on DFT is superior to the frequency-domain LS channel estimation in Rice fading channel environment based on logarithmic distance path loss model, which is consistent with the theoretical analysis.At the same time, the correctness of the system is verified.
【学位授予单位】：郑州大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN919.3

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