单精度量化大规模MIMO系统上行信道估计与导频设计
发布时间：2018-10-15 19:55
【摘要】：随着移动通信的迅猛发展,第五代移动通信系统需要支持更高的数据传输速率。而由于无线资源的日渐紧张,大规模多输入输出(Multiple-Input Multiple-Output,MIMO)技术可以充分利用空间资源,因而可以大幅度提高能量效率和频谱利用率,成为了5G的关键技术之一。同时大规模MIMO系统存在着海量数据处理、系统总消耗功率巨大、硬件成本昂贵等问题。对于解决上述问题一种有效的技术是在基站的接收机中使用低精度的模数转换器(Analog to Digital Converter,ADC),以此来降低大规模MIMO系统部署的成本与功耗。要使系统在低精度量化的基础上进行可靠且高速的通信,则必须获取更加准确的信道状态信息(Channel-State Information,CSI)。由于小区内所有用户同时同频工作,为避免小区内干扰,所以单个小区内的用户需发送相互正交的导频序列。基于以上对CSI和导频的要求,本文将重点研究单精度量化大规模多输入输出(One-Bit Massive MIMO)系统的上行信道估计和导频设计问题。首先,介绍了单用户SIMO系统和大规模多用户MIMO系统模型以及相应的信道模型,并分析了在TDD通信方式下系统上行导频传输及上下行数据传输过程。其次,介绍了单用户SIMO系统的上行信道估计。首先阐述了不同类型CSI对系统信道容量的影响。接着介绍了基于导频的信道估计算法,进而分析了在线性接收下的数据检测。最后在此基础上推导了系统的可达速率。随后,基于单精度量化单用户SIMO系统上行信道估计,研究了单精度量化大规模多用户MIMO系统中的最小二乘(Least Square,LS)估计和最小均方误差(Minimum Mean Square Error,MMSE)估计。但由于上述两种算法均是基于信道输入和量化输出之间的互信息量,因而不能直观地体现量化噪声对信道估计性能及可达速率的影响。接下来通过基于Bussgang分解理论的线性分解来表示单精度量化输入输出之间的关系,进而推导出了线性最小均方误差(Linear Minimum Mean Square Error,LMMSE)估计。最后分析了三种算法的复杂度、均方误差(Mean Square Error,MSE)以及系统的可达速率。仿真结果表明,LS估计的性能最差,但计算复杂度更低,也更适合大规模MIMO系统。最后,本文提出了一种新的基于循环移位Zadoff-Chu(ZC)序列的正交导频生成方案。首先对常用的参考信号基序列的特性进行了分析,进而深入研究了现有文献中正交导频的生成方式,即控制小区内所有用户在不同的时隙段发送各自的导频(时间导频)。然后针对时间导频的数据传输效率较低这一缺陷,本文提出了一种新的正交导频生成方案,即通过ZC序列在时域循环移位生成不同用户的导频(ZC导频),进而以最大化可达速率为目标对导频长度进行优化。仿真结果表明,与现有文献中的导频生成方案相比,采用本文所提方案可以将信道估计的MSE降低约12%,由于对导频长度进行了优化,系统可达速率提高了约10%。
[Abstract]:With the rapid development of mobile communication, the fifth generation mobile communication system needs to support higher data transmission rate. However, due to the increasing shortage of wireless resources, large-scale multi-input output (Multiple-Input Multiple-Output,MIMO) technology can make full use of space resources, so it can greatly improve energy efficiency and spectral efficiency, which has become one of the key technologies of 5G. At the same time, there are some problems in large scale MIMO system, such as massive data processing, huge power consumption and high hardware cost. An effective technique to solve the above problem is to use a low-precision ADC (Analog to Digital Converter,ADC in the receiver of the base station to reduce the cost and power consumption of large-scale MIMO system deployment. In order to achieve reliable and high-speed communication on the basis of low precision quantization, more accurate channel state information (Channel-State Information,CSI) must be obtained. Since all users in the cell work at the same time, in order to avoid interference within the cell, users in a single cell need to transmit orthogonal pilot sequences. Based on the above requirements for CSI and pilot, this paper will focus on the uplink channel estimation and pilot design of single-precision quantized large scale multiple-output (One-Bit Massive MIMO) systems. Firstly, the single-user SIMO system, the large-scale multi-user MIMO system model and the corresponding channel model are introduced, and the uplink pilot transmission and uplink data transmission process of the system under the TDD communication mode are analyzed. Secondly, the uplink channel estimation of single user SIMO system is introduced. Firstly, the influence of different CSI on the channel capacity of the system is discussed. Then the channel estimation algorithm based on pilot is introduced, and the data detection under linear reception is analyzed. Finally, the reachability rate of the system is deduced. Then, based on the uplink channel estimation of single-precision quantized single-user SIMO systems, the least square (Least Square,LS) estimation and the least mean square error (Minimum Mean Square Error,MMSE) estimation of single-precision quantized large-scale multi-user MIMO systems are studied. However, the above two algorithms are based on the mutual information between channel input and quantization output, so the influence of quantization noise on channel estimation performance and reachable rate can not be intuitively reflected. Then the linear decomposition based on Bussgang decomposition theory is used to express the relationship between the input and output of single precision quantization, and then the linear minimum mean square error (Linear Minimum Mean Square Error,LMMSE) estimation is derived. Finally, the complexity of the three algorithms, mean square error (Mean Square Error,MSE) and the reachable rate of the system are analyzed. Simulation results show that the performance of LS estimation is the worst, but the computational complexity is lower, and it is more suitable for large-scale MIMO systems. Finally, a new orthogonal pilot generation scheme based on cyclic shift Zadoff-Chu (ZC) sequences is proposed. Firstly, the characteristics of common reference signal base sequences are analyzed, and then the generation method of orthogonal pilot frequency in the existing literature is deeply studied, that is, all users in the cell are controlled to transmit their own pilot (time pilot) in different time slots. Then a new orthogonal pilot generation scheme is proposed to solve the problem of low data transmission efficiency of time pilot. The pilot frequency (ZC) of different users is generated by cyclic shift of the ZC sequence in time domain, and the pilot length is optimized with the aim of maximizing the reachable rate. The simulation results show that the proposed scheme can reduce the MSE of channel estimation by about 12 points compared with the pilot generation scheme in the existing literature. Because of the optimization of pilot length, the reachable rate of the system can be increased by about 10%.
【学位授予单位】：广东工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN919.3
本文编号：2273670
[Abstract]:With the rapid development of mobile communication, the fifth generation mobile communication system needs to support higher data transmission rate. However, due to the increasing shortage of wireless resources, large-scale multi-input output (Multiple-Input Multiple-Output,MIMO) technology can make full use of space resources, so it can greatly improve energy efficiency and spectral efficiency, which has become one of the key technologies of 5G. At the same time, there are some problems in large scale MIMO system, such as massive data processing, huge power consumption and high hardware cost. An effective technique to solve the above problem is to use a low-precision ADC (Analog to Digital Converter,ADC in the receiver of the base station to reduce the cost and power consumption of large-scale MIMO system deployment. In order to achieve reliable and high-speed communication on the basis of low precision quantization, more accurate channel state information (Channel-State Information,CSI) must be obtained. Since all users in the cell work at the same time, in order to avoid interference within the cell, users in a single cell need to transmit orthogonal pilot sequences. Based on the above requirements for CSI and pilot, this paper will focus on the uplink channel estimation and pilot design of single-precision quantized large scale multiple-output (One-Bit Massive MIMO) systems. Firstly, the single-user SIMO system, the large-scale multi-user MIMO system model and the corresponding channel model are introduced, and the uplink pilot transmission and uplink data transmission process of the system under the TDD communication mode are analyzed. Secondly, the uplink channel estimation of single user SIMO system is introduced. Firstly, the influence of different CSI on the channel capacity of the system is discussed. Then the channel estimation algorithm based on pilot is introduced, and the data detection under linear reception is analyzed. Finally, the reachability rate of the system is deduced. Then, based on the uplink channel estimation of single-precision quantized single-user SIMO systems, the least square (Least Square,LS) estimation and the least mean square error (Minimum Mean Square Error,MMSE) estimation of single-precision quantized large-scale multi-user MIMO systems are studied. However, the above two algorithms are based on the mutual information between channel input and quantization output, so the influence of quantization noise on channel estimation performance and reachable rate can not be intuitively reflected. Then the linear decomposition based on Bussgang decomposition theory is used to express the relationship between the input and output of single precision quantization, and then the linear minimum mean square error (Linear Minimum Mean Square Error,LMMSE) estimation is derived. Finally, the complexity of the three algorithms, mean square error (Mean Square Error,MSE) and the reachable rate of the system are analyzed. Simulation results show that the performance of LS estimation is the worst, but the computational complexity is lower, and it is more suitable for large-scale MIMO systems. Finally, a new orthogonal pilot generation scheme based on cyclic shift Zadoff-Chu (ZC) sequences is proposed. Firstly, the characteristics of common reference signal base sequences are analyzed, and then the generation method of orthogonal pilot frequency in the existing literature is deeply studied, that is, all users in the cell are controlled to transmit their own pilot (time pilot) in different time slots. Then a new orthogonal pilot generation scheme is proposed to solve the problem of low data transmission efficiency of time pilot. The pilot frequency (ZC) of different users is generated by cyclic shift of the ZC sequence in time domain, and the pilot length is optimized with the aim of maximizing the reachable rate. The simulation results show that the proposed scheme can reduce the MSE of channel estimation by about 12 points compared with the pilot generation scheme in the existing literature. Because of the optimization of pilot length, the reachable rate of the system can be increased by about 10%.
【学位授予单位】：广东工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN919.3
【参考文献】
相关期刊论文 前3条
1 阳析;金石;;大规模MIMO系统传输关键技术研究进展[J];电信科学;2015年05期
2 MA Zheng;ZHANG ZhengQuan;DING ZhiGuo;FAN PingZhi;LI HengChao;;Key techniques for 5G wireless communications:network architecture, physical layer,and MAC layer perspectives[J];Science China(Information Sciences);2015年04期
3 王海荣;俞菲;黄永明;杨绿溪;;大规模MIMO多小区TDD系统中的预编码策略和导频调度[J];信号处理;2013年08期
相关博士学位论文 前1条
1 汪智勇;低精度量化通信系统接收技术研究[D];中国科学技术大学;2014年
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