Robust optimization for the correlated MIMO downlink with imperfect channel state information

To reduce the performance deterioration induced by imperfect channel state information (CSI) in cor-related multiple input multiple output(MIMO) downlink, the linear transmit/receive filters should be optimized to be robust to imperfect CSI. A sub-optimization algorithm based on minimizing sum MSE conditional on available imperfect CSI estimates subject to a per-user power constraint is proposed. The algorithm adapts the existing MMSE algorithm from uncorrelated single-user MIMO system with perfect CSI to correlated MIMO downlink with imperfect CSI. Simulation shows that the suboptimal algorithm can effectively mitigate the performance loss induced by imperfect CSI and has a good convergence performance. In addition, the effect of spatial correlation on the performance of the proposed algorithm is also simulated.     

基于STBC的混沌MIMO雷达的信号处理研究

针对MIMO（multiple input multipleoutput）雷达正交信号设计的困难,提出了一种超宽带调制的混沌二相码,并结合STBC（space-time block coding）技术,能够达到发射信号的完全正交和最大空间分集．方法简单易行,具有较好的保密特性．仿真实验给出2×2系统下,信噪比为20dB时的回波信号波形,发现该方法较好地实现对复杂目标的识别．同时推导了该模型在奈曼皮尔逊准则下的目标检测概率,相对于窄带系统,检测概率显著提高．     

Lattice reduction aided MMSE Tomlinson-Harashima precoding based on VBLAST algorithm for MIMO systems

A lattice reduction aided （LRA） minimum mean square error （MMSE） Tomlinson-Harashima precoding （THP） was proposed based on vertical Bell Labs layered space time （VBLAST） algorithm for multiple input multiple output （MIMO） systems. The extended channel was used to provide optimal tradeoff between residual interference and noise amplification. The processing based on lattice reduction method helps achieve maximal diversity order. The VBLAST algorithm was applied to get the optimal processing ordering for successive interference cancellation （SIC） at transmitter. Simulation results show that the proposed algorithm outperforms conventional THP and the LRA zero-forcing （ZF） THP with full diversity order.     

Capacity and QoS based codebook construction for MIMO precoded spatial multiplexing systems with limited feedback

This paper deals with the design and performance analysis of transmit precoder optimization for multiple input multiple output (MIMO) systems with limited feedback of channel state information. A capacity criterion based optimal codebook construction algorithm for MIMO precoded spatial multiplexing systems is pre-sented. The optimal precoder structure combining precoding and power allocation is employed. Simulation results show that the capacity criteria based codebook can achieve higher capacity than that of equally power allocation based codebook of previous research.     

Impact of channel estimation error on channel capacity of multiple input multiple output system

In order to investigate the impact of channel estimation error on channel capacity of multiple input multiple output （MIMO） system, a novel method is proposed to explore the channel capacity in correlated Rayleigh fading environment. A system model is constructed based on the channel estimation error at receiver side. Using the properties of Wishart distribution, the lower bound of the channel capacity is derived when the MIMO channel is of full rank. Then a method is proposed to select the optimum set of transmit antennas based on the lower bound of the mean channel capacity. The novel method can be easily implemented with low computational complexity. The simulation results show that the channel capacity of MIMO system is sensitive to channel estimation error, and is maximized when the signal-to- noise ratio increases to a certain point. Proper selection of transmit antennas can increase the channel capacity of MIMO system by about 1 bit/s in a flat fading environment with deficient rank of channel matrix.     

用B样条神经网络控制非线性系统的混沌运动

采用B样条神经网络，通过选取混沌系统不稳定周期轨道的不动点附近的数据作为参数扰动模型输入样本的学习，把该模型训练成神经网络混沌控制器，从而预测出混沌系统将来时刻的时间序列，获得控制混沌系统的扰动信号。用该扰动信号，将嵌入在混沌吸引子中不稳定周期轨道镇定到稳定的不动点处．通过对Henon映射的数值仿真实验，证明采用B样条神经网络控制非线性混沌运动是有效的．     

Optimal training design and placement for MIMO orthogonal frequency division multiplexing channel estimation

This paper deals with optimal training design and placement over multiple orthogonal frequency division multiplexing(OFDM) symbols for the least squares(LS) channel estimation in multiple-input multipleoutput(MIMO) OFDM systems.First,the optimal pilot sequences over multiple OFDM symbols are derived by co-cyclic Jacket matrices based on the minimum mean square error(MSE) of the LS channel estimation.Then,an enhanced channel estimation method using sliding window is proposed to improve further the performanc...     

最小均方盲反卷积法在机械设备振动分析中的应用

将多通道盲反卷积应用于机械设备振动信号的分析,分析了机械振动信号的多通道盲反卷积模型,采用最小均方盲反卷积算法从测量信号中分离振源信号,并进行实验论证.实验内容包括:提取滚动轴承故障源信号,斜齿轮故障源信号以及柴油机活塞-缸套撞击信号.     

时变MIMO系统的联合符号检测与信道估计

针对MIMO系统时变多径信道,结舍分集舍并,提出一种带判决反馈的修正混和型MLSE（DF-MHMLSE）为基础的低复杂度联合符号检测与信道估计的递推算法．发送端仅需少量导频符号用于信道估计初始化,在此基础上,针对系统中各MISO子系统,分别采用修正混和型MLSE算法（MHMLSE）,形成临时判决符号矢量集合及对应的临时信道矢量集合,最终根据分集合并确定最佳判决符号矢量,同时实现信道矢量的自适应更新,该算法减小了传统MIMOMLSE的计算复杂度,实现了逐符号检测,并取得了较低的误比特率．     

非平稳信号自适应最大信噪比盲源分离方法

为了提高时变非平稳信号的盲源分离效果,提出了自适应最大信噪比盲源分离新方法.该方法以信噪比函数作为代价函数,并基于改进的多项式系数自回归模型,进行最优滑窗长度的自适应估计.仿真计算表明,FastICA算法需要预设源信号的概率密度函数,以选择适宜的非线性函数近似估计源信号的非高斯性,当假设的概率密度函数与实际不符时无法正确分离源信号;累积量算法在信源的峰度相同时无法正确分离源信号.新方法与经典的FastICA算法和基于累积量的盲源分离算法比较结果表明,对于经典的FastICA算法、累积量算法无法正确分离的时变非平稳信号,新方法能够有效地进行盲源分离,分离结果不受源信号的概率分布、信源的峰度等统计因素影响.      

MIMO双向中继网络的预编码设计与功控策略

为加强MIMO双向中继系统的空间复用增益,研究一种低复杂度的发送和接收预编码矩阵.利用子空间对齐方法,将双向MIMO信道分解为多路单入单出（SISO）的子信道形式,使得两个源用户能够使用网络编码获取更好的空间复用增益.同时通过矩阵计算和转化,给出了一种优化的功率分配方案.在确定优化矩阵后,该方案能够为每个子信道独立地进行优化功率分配,并且能够得到各节点间优化功率分配的闭合表达式,从而将算法复杂度从O（n3）降低为O（n）.仿真结果表明,在典型场景下,所提方案在具有更低复杂度的优势下,系统性能接近优化的梯度下降迭代方案,优于传统单纯前向放大转发方式（AF） ,有2.99 bit/（sHz）的性能增益.      

基于改进遗传算法的递归神经网络非线性系统辨识

将递归内时延神经网络应用于非线性动力学系统辨识中，描述了其动力学方程，并引入改进遗传算法作为其学习算法，通过非线性动力学SISO和MIMO系统的辨识仿真研究，验证了内时延递归网络结构和改进遗传算法的有效性。     

多分量相移键控信号码速率盲估计

为解决单通道接收机同时截获到同一频带范围内的多分量相移键控信号的参数估计问题,提出了一种不经信号分离直接提取各独立信号分量码速率的盲估计算法.从理论上推导了多分量相移键控信号的二阶共轭循环自相关具有线性特性,因此可以不受干扰地提取各信号分量的码速率;进而提出了简单而有效的谱峰增强方法,与基于二阶共轭循环自相关获得的谱峰相比,用此法获得的谱峰更为清晰.仿真实验表明:用提出的算法,当双分量信号功率比为1:1且信噪比为-5 dB时,码速率估计的正确率可达98％;尤其是在单分量环境下,该算法比现有算法的性能提高4 dB以上.     

Joint user and antenna selection for multiuser MIMO downlink with block diagonalization

User selection is necessary for multiuser multiple-input multiple-output (MIMO) downlink systems with block diagonalization (BD) due to the limited free spatial transmit dimensions. The pure user selection algorithms can be improved by performing receive antenna selection (RAS) to increase sum rate. In this paper, a joint user and antenna selection algorithm, which performs user selection for sum rate maximization in the first stage and then performs antenna selection in the second stage, is proposed. The antenna selection process alternately drops one antenna with the poorest channel quality based on maximum determinant ranking (MDR) from the users selected during the first stage and activates one antenna with the maximum norm of projected channel from the remaining users. Simulation results show that the proposed algorithm significantly outperforms the algorithm only performing user selection as well as the algorithm combining user selection with MDR receive antenna selection in terms of sum rate.     

神经Chebyshev正交多项式均衡器及自适应算法

提出一种全新结构的非线性均衡器———神经Chebyshev正交多项式自适应均衡器.该均衡器由1个非线性神经自适应滤波器和1个Chebyshev正交多项式滤波器级联而成.基于最陡下降方法,推导出了相应的自适应算法.仿真结果表明,在线性信道中,该均衡器的均方误差(MSE)比神经自适应均衡器和二阶Volterra均衡器小;在非线性信道中,以更为简单的结构达到了和BP算法训练的三层神经网络相似的性能.     

Switching between antenna subset selection and quasi-orthogonal space-time block code in presence of correlation

We address the problem of adaptive modulation and coding scheme (AMCS) for a multi-input multioutput (MIMO) system in presence of time-varying transmitting correlation. Antenna subset selection and quasiorthogonal space-time block code (QOSTBC) have different error performances with different signal-to-noise ratios (SNRs) and in different spatial correlation scenarios. The error performance can be improved by selecting an appropriate transmission scheme to adapt to various channel conditions. The maximum distance criterion is the simplest and very effective algorithm for the antenna subset selection without needs of complex calculation and channel state information at transmitter (CSIT). The minimum error performance criteria and the simplified linear decision strategy are developed for constant transmission rate traffic to select the optimal transmission scheme. It can dramatically decrease algorithm complexity for obtaining error probability according to the known quantities comparing with using instant CSIT. Simulation results show that, remarkable performances including low SNR and weak spatial correlation at the expense of simple calculation and almost no bandwidth loss by adopting AMCS can be achieved. The proposed AMCS improves robustness of slowly varying spatial correlated channels.     

天线分集的MIMO系统的容量分析

结合空间分集和极化分集，对MIMO—OFDM系统中的容量进行研究。在IEEE 802．16d室内多径环境下，对使用2根发射天线和2根接收天线的MIMO—OFDM系统进行了深入研究。在发射端和接收端，空间分集和极化分集技术同时应用在MIMO—OFDM系统中。为了比较，对仅使用空间分集的通信系统容量也进行了讨论。     

基于ICA的MIMO系统空时盲均衡算法

多输入多输出系统的MMSE均衡中,由于接收端采样大小的限制,对观测信号协方差矩阵的估计和信道的盲辨识误差会严重影响均衡性能,采用独立分量分析作为一种辅助手段改进传统的均衡器,并选择最佳均衡时延优化算法。仿真结果表明,该算法提高了传统算法的鲁棒性,在大大降低计算复杂度的同时改善了均衡性能。     

Joint dirty paper coding and linear receiver design for multiuser MIMO broadcast channels

A multiuser multiple input multiple output （MIMO） broadcast scheme was proposed through applying dirty paper coding （DPC） at the transmitter and linear equalization at the receiver. Assuming single data stream communication for each user, joint transmitter and linear receiver design were done to enhance the system performance. Furthermore, a multiuser scheduling algorithm was presented to exploit multiuser diversity when the number of the users is larger than that of transmit antennas. The proposed system achieves the sum rate close to the Sato bound and is superior to some of the existing schemes.     

基于ICA的MIMO系统空时盲均衡算法

多输入多输出系统的MMSE均衡中,由于接收端采样大小的限制,对观测信号协方差矩阵的估计和信道的盲辨识误差会严重影响均衡性能,采用独立分量分析作为一种辅助手段改进传统的均衡器,并选择最佳均衡时延优化算法。仿真结果表明,该算法提高了传统算法的鲁棒性,在大大降低计算复杂度的同时改善了均衡性能。