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类型 基础研究 预答辩日期 2018-03-17
开始(开题)日期 2015-12-16 论文结束日期 2018-01-11
地点 健雄院 论文选题来源 国家自然科学基金项目     论文字数 5.63 (万字)
题目 大规模MIMO系统中的高效传输方法研究
主题词 大规模MIMO,信道预测,MMSE接收机,TPE接收机,3D MIMO
摘要 大规模多输入多输出(MIMO)是第五代(5G)蜂窝通信网络的主要技术,具有较高的能效和谱效。当基站天线数很大时,使用简单的线性处理就可以获得满意的性能。但是大规模天线阵列增加了线性处理的复杂度和基站的部署成本。为了降低复杂度和成本,本论文从线性处理和天线技术两个方面,深入研究了“大规模MIMO系统中的高效传输方法研究”这一课题,充分利用统计信道状态信息(CSI),提出了多种高效的传输方法,并进行了性能分析。研究内容涉及基于多项式拟合的大规模MIMO信道预测器、大规模MIMO系统中基于能效的天线数和发射功率联合优化方法、大规模MIMO系统采用截断多项式展开(TPE)接收机的上行功率控制、三维(3D)大规模MIMO系统中低复杂度的双层波束成形和3D大规模MIMO系统利用基站天线下倾角进行无线携能通信的传输方法。具体研究内容和主要贡献现述如下: 1. 针对考虑延迟CSI的大规模MIMO系统,提出了一种低复杂度的基于多项式拟合的信道预测器,减少运算时间和处理延迟。多项式拟合预测器只需要非常少的CSI观测样本,就可以估计现有的CSI。与传统的维纳预测器相比,多项式拟合预测器无需对信道统计信息进行估计,也避免了矩阵求逆运算。首先分析得到了仅与统计CSI有关的近似SINR,仿真验证了该近似值与实际值十分接近。然后比较了完美CSI、维纳预测器和多项式拟合预测器的单用户平均速率的近似差距,还分析了预测器的归一化均方误差(NMSE)。在一个更实际和更一般的离开角(AoD)谱模型下研究性能,该模型具有一个集中方向和一个扩展因子,当AoD谱模型的集中方向的角度和扩展因子较小,且多项式拟合预测器采用一个合适的预测阶数时,可以取得令人满意的性能。 2. 针对大规模MIMO系统中使用最小均方误差(MMSE)接收机的场景,以最大化能效为准则提出了联合优化基站天线数和用户发射功率的迭代算法。首先推导了使用MMSE接收机时的近似可达速率,仿真实验表明该近似值与实际值非常接近。接着以近似可达速率为基础,构建能效最大化的优化问题,约束条件为可达速率目标和发射功率限制。该优化问题是分式规划问题,将其转变为线性规划问题,并提出了联合优化基站天线数和发射功率的迭代算法。该算法只需统计CSI,而无需大维的瞬时信道信息,因此在若干个信道相干时间内都无需重新运行,复杂度较低。为了比较,还研究了迫零(ZF)接收机。仿真实验验证了针对MMSE接收机提出的优化算法在能效方面要优于ZF接收机,并且可以大大减少基站天线数,降低基站部署成本。 3. 针对上行大规模MIMO系统,提出了使用TPE接收机的上行功控算法,交替优化了用户的发射功率和TPE接收机的多项式系数。TPE接收机避免了ZF和MMSE接收机中的矩阵求逆运算,具有较低的复杂度。首先得到了使用TPE接收机的近似SINR。据此构造以最小化所有用户的总发射功率为目标的优化问题,约束条件为单用户的SINR目标和单用户的发射功率限制。然后提出了优化用户的发射功率和TPE接收机的多项式系数的迭代算法,该算法只与统计信道信息有关。为了比较,还研究了ZF和MMSE接收机的上行功控算法。分析了三种接收机的复杂度,在天线数很多时,TPE接收机的复杂度最低。仿真结果表明,在SINR目标较低时,TPE接收机的性能十分接近ZF和MMSE接收机,当SINR目标较高时,通过使用足够多的TPE项数或足够多的基站天线,可以减小TPE接收机与ZF和MMSE接收机之间的性能差距。 4. 针对配置均匀矩形天线阵(URA)的3D大规模MIMO系统,提出了低复杂度的双层波束成形,其中第二层预波束成形是水平和垂直离散傅立叶变换(DFT)预波束成形的Kronecker乘积。首先使用DFT预波束成形将小区进行分割,然后提出了一个基于统计CSI的低复杂度用户分组算法。DFT预波束成形与瞬时信道信息构成了低维的等效信道。基于等效信道,分别对每组用户进行信漏噪比(SLNR)预编码。由于邻组间干扰是组间干扰的主要来源,SLNR预编码旨在抵抗组内和邻组间干扰。为了比较,还研究了考虑所有组间干扰和只考虑单个组内干扰的SLNR预编码。最后使用确定性等价方法分析了所提方案的近似SINR,仿真结果验证了近似SINR很接近实际SINR,同时也证明了本方案在性能和复杂度之间取得了一个较好的平衡。 5. 针对3D大规模MIMO系统,提出了利用基站天线下倾角进行无线携能通信(SWIPT)的传输算法。基站采用匹配滤波(MF)预编码,用户采用功率划分(PS)技术进行信息解码(ID)和能量获取(EH)。为了提高SWIPT效率,开发垂直维度,联合优化基站天线下倾角、功率分配和PS比。以最小化发射功率为目标构建优化问题,约束条件为ID处的SINR目标和EH处的获取功率目标。提出了一个基于统计信道信息的迭代算法求解该问题。仿真展示了所提算法的性能接近穷尽搜索最优解的性能,并且比具有可调下倾角的传统方案要好。
英文题目 Research on High-Efficiency Transmission Schemes for Massive MIMO Systems
英文主题词 massive MIMO,channel prediction,MMSE receiver,TPE receiver,3D MIMO
英文摘要 Massive multiple-input multiple-output (MIMO) is a key ingredient of the fifth-generation (5G) cellular communication networks with high energy and spectral efficiency. When the number of base station (BS) antennas is very large, it can provide satisfying performance with simple linear processing. But massive antenna arrays bring high computational complexity and deployment cost. In order to reduce the complexity and cost, this thesis deeply studies the project named ``Research on High-Efficiency Transmission Schemes for Massive MIMO Systems" from the aspects of linear processing and antenna technology. By making full use of statistical channel state information (CSI), multiple high-efficiency transmission schemes and performance analysis are given. The contents are the channel predictor based on polynomial fitting for massive MIMO systems, joint optimization of number of antennas and transmit power based on maximizing energy efficiency in massive MIMO systems, uplink power control with truncated polynomial expansion (TPE) receiver in massive MIMO systems, low-complexity two-stage beamforming for three-dimensional (3D) massive MIMO and transmission algorithm of exploiting BS antenna tilt for simultaneous wireless information and power transfer (SWIPT) in 3D massive MIMO systems. The detailed contents and main contributions are listed as follows: 1. In massive MIMO systems with delayed CSI, we propose a low-complexity channel prediction based on polynomial fitting to reduce the computing time and process latency. The predictor based on polynomial fitting needs very few CSI samples to estimate the current one. Compared with conventional Wiener predictor, polynomial predictor does not need to estimate the channel statistics, and avoids matrix inversion. We analyze the approximate SINR which only depends on statistical CSI and is numerically validated tight. We derive the approximate gap of per-user average rate between perfect CSI, Wiener predictor and polynomial predictor. We also analyze the normalised mean square error (NMSE) of prediction. We investigate the performance under a more practical and more general angle of departure (AoD) spectrum model which has a concentration direction and a spreading factor. When the concentration direction and spreading factor are relatively small, the performance is satisfying with a proper prediction order. 2. In the massive MIMO system with minimum mean-square-error (MMSE) receiver, we propose an iterative algorithm to jointly optimize the number of BS antennas and user transmit power for maximizing the energy efficiency. Firstly, we derive the approximate achievable rate with MMSE recevier. This approximation is very tight with the actual value via simulations. Accordingly, the optimization problem is formulated, aiming at maximizing the energy efficiency subject to the target of achievable rate and the constraint of transmit power. We transform the optimization problem, which is a fraction programming problem, into a linear programming problem. We propose an iterative algorithm to jointly optimize the number of BS antennas and user transmit power. The algorithm only requires channel statistics instead of large-dimensional instantaneous channel realizations. So, the algorithm only has to run once in multiple channel coherence periods which has low complexity. For comparison, we investigate the zero-forcing (ZF) scheme. Simulations show that our proposal with MMSE receiver outperforms ZF receiver in terms of energy-efficiency and can significantly reduce the number of BS antennas and BS deployment cost. 3. We propose an uplink power control algorithm for uplink massive MIMO systems with TPE receiver, alternatively optimizing transmit power and polynomial coefficients. TPE receiver can avoid the matrix inversion in ZF and MMSE receivers with low complexity. Firstly, we derive the associated approximate SINR. Accordingly, the optimization problem is formulated aiming at minimizing the total transmit power of all users, subject to per-user SINR target and per-user transmit power constraint. The proposed algorithm depends only on channel statistics. For comparison, we investigate the uplink power control with ZF and MMSE receivers. When the number of BS antennas is large, the complexity of TPE receiver is the lowest. Simulations reveal that when the SINR target is low, the performance of TPE receiver is very close to that of ZF and MMSE receivers, when the SINR target is high, we can add more TPE terms or antennas to reduce the performance gap. 4. We propose low-complexity two-stage beamforming for 3D massive MIMO systems with a uniform rectangular array (URA), where the second-stage prebeamforming is the Kronecker product of horizontal and vertical discrete Fourier transform (DFT) prebeamforming. DFT prebeamforming splits the cell. We propose a low-complexity user grouping algorithm based on statistical CSI. DFT prebeamforming and instantaneous CSI form the low-dimensional effective channel. With the low-dimensional effective channels, signal-to-leakage-and-noise-ratio (SLNR) precoding is adopted for each group. Because inter-group interferences mainly come from adjacent groups, SLNR precoding is used to combat the intra-group and adjacent-group interferences. For comparison, we study the SLNR precoding considering all-group and intra-group interferences. The approximate SINR of our proposal is derived using deterministic equivalent method. Simulations validate that the approximations are tight, and our proposal achieves a good balance between performance and complexity. 5. For 3D massive MIMO systems, we propose a transmission algorithm which exploits BS antenna tilt for SWIPT. The BS applies matched filtering (MF) precoding and users adopt power splitting (PS) technique for information decoding (ID) and energy harvesting (EH). In order to improve the SWIPT efficiency, we exploit the vertical domain and jointly optimize the BS antenna tilt, allocated power and PS ratios. The optimization problem aims at minimizing the transmit power subject to SINR and harvested power targets. We propose an iterative algorithm which only requires statistical CSI. Simulations show that the performance of the proposal is close to that of brute-force search, and outperforms the conventional systems with an adjustable tilt.
学术讨论
主办单位时间地点报告人报告主题
东南大学 2014年10月9日 南京无线谷 范立行 Power Control and Low-Complexity Receiver for Uplink Massive MIMO Systems
东南大学 2017年11月17日 南京无线谷 范立行 Performance Analysis of Downlink and Uplink Decoupling in Heterogeneous Networks
东南大学 2014年2月13日 南京无线谷 范立行 A Low-Complexity 3D Massive MIMO System Jointly Using Statistical and Instantaneous CSIT
东南大学 2017年4月10日 南京无线谷 范立行 SWIPT in 3D Massive MIMO Systems with Tilt Optimization
东南大学 2017年6月12日 南京无线谷 华梦 Unmanned Aerial Vehicles-Based Internet of Things Services
东南大学 2017年9月18日 南京无线谷 华梦 The Key Technologies Research of Unmanned Aerial Vehicles Used in Internet of Thing
东南大学 2014年10月13日 南京无线谷 黄伟 Compressive CSIT Estimation in FDD Multi-user Massive MIMO System
     
学术会议
会议名称时间地点本人报告本人报告题目
美国特拉华大学会议 2014年11月3日 美国特拉华大学 A Low-Complexity Linear Receiver Based on Uplink Power Control for Massive MIMO Systems
International Conference on Wireless Communications and Signal Processing (WCSP) 2017年10月13日 南京 Optimal Design of 3D MIMO SWIPT Systems with Tilt Adaptation
2014 IEEE/CIC International Conference on Communications in China (ICCC) 2014年10月15日 上海 Power Control and Low-Complexity Receiver for Uplink Massive MIMO Systems
     
代表作
论文名称
Power Control and Low-Complexity Receiver for Uplink Massive MIMO Systems
Performance analysis of low-complexity channel prediction for uplink massive MIMO
A low-complexity 3D massive MIMO scheme jointly using statistical and instantaneous CSIT
Exploiting BS Antenna Tilt for SWIPT in 3-D Massive MIMO Systems
 
答辩委员会组成信息
姓名职称导师类别工作单位是否主席备注
蔡跃明 正高 教授 博导 中国人民解放军理工大学
王保云 正高 教授 博导 南京邮电大学
仰枫帆 正高 教授 博导 南京航空航天大学
黄永明 正高 教授 博导 东南大学
李春国 正高 教授 博导 东南大学
      
答辩秘书信息
姓名职称工作单位备注
何世文 副高 副研究员 东南大学