【作者】 孙垂强；

【导师】 葛建华；

【作者基本信息】 西安电子科技大学 ， 通信与信息系统， 2014， 博士

【摘要】 随着越来越多的互联网和多媒体应用融入无线网络，人们对高速宽带无线通信业务的需求不断增长，要求下一代移动通信系统具备为用户提供更高的数据传输速率和更好的服务质量的能力。多输入多输出（Multiple Input Multiple Output，MIMO）技术的发展使得这种需求成为可能。MIMO系统通过在发送端和接收端分别配置多个天线发送和接收信号，获得空间分集和复用增益，从而能够增加系统容量、提高链路传输质量和频谱利用率。目前，点对点的单用户MIMO系统的研究已经日趋成熟，点对多点的多用户MIMO系统成为了近年来无线通信领域中的研究热点之一。多用户MIMO系统具有更多优势：多天线分集增益能够提高误比特率性能，多天线的复用增益可以提高系统的吞吐量，多天线带来的方向性增益可以从空间上区分不同用户，从而消除用户间干扰。本文针对多用户MIMO系统下行链路中的预编码技术、用户调度技术以及天线选择技术开展研究，论文主要研究成果如下：1.针对多用户MIMO系统下行链路预编码设计问题，I）在详细分析现有多用户MIMO预编码算法的基础上，提出了一种基于匹配加权信号泄漏噪声比（Matching weighted Signal-to-Leakage-and-Noise Ratio，MSLNR）的多用户MIMO预编码迭代优化算法。该算法把各个用户的有效信道增益作为匹配加权系数，先对不同用户接收到的泄漏信号功率进行匹配加权，然后通过最大化MSLNR准则求出预编码矢量的闭式解，并在所提出的匹配加权算法的基础上，引入迭代优化方案，进一步提高系统性能。该方案不受系统天线配置数目的严格限制，仿真结果验证了该方案在提高系统和容量方面的有效性。II）针对认知（Cognitive Radio，CR）多用户MIMO系统，将块对角化（BlockDiagonalization，BD）算法和匹配加权信号泄漏噪声比算法联合，提出了一种两级联合的CR-BD-MSLNR预编码方案。该方案根据主用户和认知用户不同的频谱使用优先权，采用两级预编码方案：第一级预编码为了保证主用户的通信质量，通过块对角化算法，使主用户的预编码矩阵置于主用户干扰信道矩阵的零空间内，从而完全消除认知用户对其带来的干扰；第二级预编码在多个认知用户共享信道资源的前提下，采用匹配加权信号泄漏噪声比的迭代优化算法，提高认知用户的和容量。仿真结果表明，该方案能够完全消除认知用户对主用户的干扰，并且能够显著提高认知用户的和容量。2.针对多用户MIMO系统下行链路中的用户调度问题，I）在块对角化算法的基础上，提出了一种低复杂度、次优的用户调度方案。该方案选取一种更紧的和容量上界作为调度准则，利用贪婪算法得到初选用户集，并且通过逐一替换操作来更改已选取的初始用户集，能在一定程度上缓解局部最优解问题。仿真结果表明，该方案既保持了基于和容量上界调度算法的低复杂度特性，又获得了优于基于和容量用户调度算法的和容量性能。II）通过建立多用户MIMO系统用户调度的能量效率模型，提出了基于能量效率的用户调度方案。该方案利用贪婪算法以最大化联合信道矩阵的体积为目标，在用户选择阶段，每一步均选取与已选用户集中用户的联合信道矩阵体积最大的用户，之后通过功率优化来最大化系统能量效率。此外，通过对该方案进行改进，提出了比例公平调度算法，在最大化系统能量效率的同时，兼顾系统内用户的公平性。3.针对大规模MIMO系统下的天线选择技术，提出了基于能量效率的天线选择策略。首先推导了天线选择时的和容量表达式，然后建立了大规模MIMO系统中天线选择时的能量效率模型，详细分析了能量效率与选择天线数目之间的关系，得到了最优天线数目的表达式，在此基础上提出了基于信道矩阵范数的天线选择策略，最后通过计算机仿真验证了所提方案的性能。更多还原

【Abstract】 In recent years, with the growing of internet and multimedia applications inwireless networks, the booming demand for wideband high data rates communicationservices is growing quikly. The next generation of mobile communications shouldprovide users with higher data transfer rates and better quality of service. Multiple inputmultiple output (MIMO) techniques make such requirements possible. MIMO systemuses multiple antennas at the transmitter and receiver to obtain spatial diversity andmultiplexing gains. MIMO technology can increase the system capacity, enhance thetransmission link reliability, and improve the spectrum efficiency. Currently, the point topoint single-user MIMO system research has matured, and multiuser MIMO system hasbeen one of the most widely explored topics in wireless communications over the pastfew years. Multiuser MIMO system has many advantages: the multi-antenna diversitygain can improve bit error rate performance, the multi-antenna multiplexing gain canincrease the system throughput, and the multi-directional antenna gain can distinguishdifferent located users, thereby eliminating interference between users.Therefore, thisthesis investigates the precoding design, user scheduling and antenna selection formultiuser MIMO downlink systems. Specifically, the main contributions of this thesisare summarized as follows:1. In the research of the precoding design for multiuser MIMO downlink systems,I) According to the analysis of the typical precoding methods for multiuser MIMOdownlink systems, a multiuser iterative precoding algorithm is proposed, whichis based on matching weighted signal-to-leakage-and-noise ratio (MSLNR)criterion. In the proposed algorithm, the effective channel gain of each user isselected as the matching weighted factor, and the leakage power received byeach user is weighted by the factor. An exact closed form solution for theprecoding vector is obtained by maximizing the WSLNR, and then optimized byusing an iterative optimization approach. The proposed precoding design schemedoes not impose a restriction on the available system antennas configuration,and simulation results show that the proposed scheme can improve the sumcapacity of the system.II) For cognitive radio (CR) multiuser MIMO downlink systems, according to thejoint block diagonalization (BD) algorithm and the MSLNR based algorithm, theCR-BD-MSLNR precoding scheme is proposed. The CR-BD-MSLNRprecoding scheme uses a two-level precoding scheme on the basis of the different priorities when the primary user (PU) and cognitive users (CU) occupyauthorized spectrum. In the first level precoding, for guaranting the PU’scommunication quality, the BD algorithm is adopted to force PU’s precodingmatrix to lie in the null space of interference channel matrix. Thus theco-channel interference from the cognitive user base station (CBS) to the PUcould be removed completely. In the second level precoding, the MSLNR basedalgorithm is adopted to mitigate interference between CUs and improve capacityfor CUs. Simulation results show that the proposed scheme can eliminate theco-channel interference from the CBS to the PU completely and achieve highsum capacity for CUs.2. In the research of the user scheduling for multiuser MIMO downlink systems,I) We propose a low complexity and suboptimal user scheduling algorithm basedon block diagonalization scheme. The proposed user scheduling algorithm uses astrong tight upper bound of sum capacity as selection metric, and thepreliminary selected user set is obtained according to greedy search method.Then a one-for-one substitution operation is employed to modify the preliminaryselected user set, which can mitigate the effect of the local optimum problem toa certain extent. Computer simulations show that the proposed algorithm bothmaintains the low-complexity feature of the capacity upper bound basedalgorithm and obtains higher sum capacity than the capacity based algorithm.That is to say, the proposed algorithm achieves a good trade-off between sumcapacity performance and computational complexity.II) By building the energy-efficient user scheduling model for multiuser MIMOdownlink systems, an low complexity energy-efficient user scheduling scheme isproposed. The proposed user scheduling scheme aims to maximize the largestaggregate channel matrix volume on the basis of greedy search method. In eachuser selection step, the scheme chooses the user that provides the the largestaggregate channel matrix volume with the already selected users. Then theenergy efficiency is maximized by optimizing the transmit power. Furthermore,by taking into account the problem of maintaining fairness among users, asimplified proportional fair scheduling algorithm is also proposed.3. In the research of the antenna selection for massive MIMO systems, an energyefficient antenna selection scheme is proposed. We first derive a goodapproximation of the expression for the sum capacity in the antenna selectionsystem. By building the energy-efficient antenna selection model for massive MIMO systems, we analyze the relationship between energy efficiency andselected antenna number in detail, and determine the optimum antenna number.Then the antenna selection strategy is presented. All the analytical results areverified through computer simulations.更多还原