MIMO无线通信自适应传输理论方法研究

发布时间：2018-01-11 00:28

本文关键词：MIMO无线通信自适应传输理论方法研究　出处：《东南大学》2016年博士论文　论文类型：学位论文

【摘要】：多天线发送和多天线接收(MIMO, Multiple-Input Multiple-Output)无线传输技术能够提升无线通信的系统容量、频谱效率、功率效率及传输可靠性,在过去的近二十年得到了广泛的研究与应用,成为宽带移动通信系统的核心技术。未来移动通信系统对系统容量、频谱效率、功率效率及传输可靠性都提出了更高的要求,需要采用大规模天线的MIMO无线传输技术。在此背景下,本论文开展MIMO无线通信系统自适应传输理论方法研究,着重研究与迭代接收相适应的自适应MIMO传输理论方法和大规模MIMO系统导频和功率配置的自适应理论方法。首先,研究了MIMO系统迭代接收机的性能建模方法。迭代接收技术是获得逼近信道容量的接收技术,其性能建模是实现迭代接收情况下链路自适应的基础,为此,从等效模型、传递参数、性能提取及传递关系等四个方面着手,提出了MIMO系统迭代接收性能建模方法。该方法以服从高斯分布的对数似然比信息等效模型为基础,以互信息为传递参数并通过仿真获得互信息传递关系图,并利用误比特率或保真度为传递参数的半公式化传递关系及以互信息为传递参数的半公式化传递关系,实现MIMO迭代接收的性能建模。进而,提出了迭代接收机各软输入软输出单元的性能预测方法。仿真结果证实所提方法的有效性。然后,针对MIMO传输链路,研究了迭代接收情况下的高效链路自适应方法。推导了迭代接收后验信干比以及等效信噪比,提出了迭代接收情况下MIMO链路自适应方法。该方法利用经典链路自适应方法确定秩指示和信道质量指示的取值范围,仅在秩指示和信道质量指示的取值范围内确定反馈参数,减少了后验信干比及等效信噪比的计算次数,从而降低了在线吞吐量预测的计算量。仿真结果表明：所提链路自适应方法的吞吐量优于经典链路自适应方法,满足链路服务质量要求,并且获得了3.5dB吞吐量增益。接着,研究了角度域信道模型下大规模MIMO系统上行传输最小均方误差(MMSE)接收机的可达和速率。可达速率分析是实现导频和功率等自适应优化配置的基础,本论文将MMSE检测器输出端后验信干比分解为两个独立随机变量之求和,通过引入卡方变量二次型的分布、随机矩阵的经验特征值分布等理论,得到了这两个独立随机变量的矩统计量及概率分布、以及后验信干比的矩统计量。由两个独立随机变量的概率分布,提出了后验信干比的一种归一化形式,证明了后验信干比服从伽玛分布,并由所得后验信干比矩统计量得到伽玛分布函数的参数。进而,利用后验信干比的分布函数,得到了MMSE接收机后验信干比下界以及可达和速率的近似式。仿真结果证实了理论结果的准确性。最后,研究了大规模MIMO系统上行导频辅助传输方式下导频和功率自适应优化配置方法。在可达和速率分析的基础上,进一步从理论上得到导频辅助传输方式下线性MMSE接收机可达和速率,进而得到其在基站天线单元数量大且用户数目固定的情形下无需迭代数值运算的近似式。针对导频长度及功率联合自适应优化配置,分别证明了固定导频长度下可达和速率是功率的凹函数,固定导频功率下可达和速率是导频长度的凹函数,进而提出针对联合自适应优化配置问题的交替优化算法,计算复杂度低。此外,研究了等功率分配传输情形下导频最优长度。证明了在中等及高信噪比条件下导频长度接近单天线用户数,在低信噪比条件下导频长度接近信道相干时间间隔数的一半。仿真结果证实了可达和速率近似式的准确性及联合优化算法的有效性。
[Abstract]:The multi antenna transmit and multiple receive antennas (MIMO, Multiple-Input, Multiple-Output) wireless transmission technology can improve system capacity of wireless communications, spectrum efficiency, power efficiency and reliability, in the past twenty years has been extensive research and application, become the core technology of broadband mobile communication system. The spectral efficiency of future mobile communication system of system capacity, power, efficiency and reliability are put forward higher requirements to the MIMO wireless transmission technology using large scale antenna. Under this background, the theory research on adaptive transmission method of MIMO wireless communication system in this thesis, the theory focuses on the research and method of adaptive iterative receiver adaptive MIMO transmission theory and method to adapt and large-scale MIMO pilot system and power allocation. Firstly, the performance modeling method of MIMO system is studied. The iterative receiver Iterative Receiver Technology Is to get close to the channel capacity receiving technology, its performance is the basis of link adaptive modeling, realize the iterative receiver case to pass parameters from the equivalent model, the performance of extraction and transfer between the four aspects, proposed the iterative receiver modeling method of MIMO system performance. This method is to obey the Gauss distribution of the log likelihood ratio information the equivalent model based on mutual information and mutual information transmission parameters transfer diagram by simulation, and the bit error rate or fidelity as the half formula transfer parameters transfer relationship and mutual information formula semi transfer parameters transfer relationship, achieve the performance modeling of MIMO iterative receiver. Then, put forward the performance the soft input soft output iterative receiver unit prediction method. Simulation results confirm the effectiveness of the proposed method. Then, according to the MIMO transmission link, the iterative receiver Efficient link adaptation methods. Deduced the iterative receiver posteriori SNR and equivalent SNR, forward link adaptive method MIMO iterative receiver case. This method uses the classical method to determine the range of link adaptive rank indication and channel quality indication, only to determine the feedback parameters in the range rank indication and channel quality indicator in a letter to calculate ratio and equivalent signal-to-noise ratio of the number of test is reduced, thereby reducing the amount of online computation throughput prediction. The simulation results show that the throughput is better than the classical link adaptive method proposed link adaptive method, link to meet quality of service requirements, and obtained the 3.5dB throughput gain. Then, the research angle domain channel model of large-scale MIMO system uplink transmission minimum mean square error (MMSE) receiver is achievable rate and rate. Analysis is the implementation of pilot and power Adaptive optimization based, the SNR is decomposed into two independent random variables summation test MMSE detector output, by introducing a distribution chi square variable two type, experience the value distribution characteristics of random matrix theory, the moments and the probability distribution of the two independent random variables the signal ratio testing and the moments. By probability distribution of two independent random variables, proposes a posteriori signal-to-noise ratio of the normalized form, it proves that the posterior SNR obeys the gamma distribution, and by the posterior signal obtained parameter of gamma distribution function than the moment statistics. Then, the distribution function of the ratio of signal to interference test using, SNR bounds and approximations and the rate of inspection has been up to MMSE receiver. The simulation results confirm the accuracy of the theoretical results. Finally, the research on the large scale MIMO system uplink pilot aided The frequency allocation method and adaptive power optimization guide transmission mode. Based on the analysis of reachability and rate, further pilot assisted transmission under linear MMSE receiver and rate up to theoretically, and then get the number of base station antenna elements and the number of users under the condition of no fixed approximation requires an iterative numerical calculation. According to the pilot length and power joint adaptive optimization, it is shown that the fixed length of pilot and the rate is a concave function of power, fixed pilot power can reach and rate is a concave function of pilot length, then put forward alternating optimization algorithm which combines adaptive optimization and low computational complexity. In addition, study on the transmission power allocation under the condition of optimal pilot length. It is proved that in the medium and high SNR pilot single antenna length is close to the number of users, in the low SNR. The lower pilot length is close to half of the coherent time interval of the channel. The simulation results confirm the accuracy of the approximation of the reachable and rate and the effectiveness of the combined optimization algorithm.

【学位授予单位】：东南大学
【学位级别】：博士
【学位授予年份】：2016
【分类号】：TN919.3

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