极化轨道约束下的最优极化（二）

本文针对相千极化测量过程中，在对接收极化进行圆环轨道约束的条件下，对于任意给定信号和干扰的极化方式，研究了了圆环极化轨道上信号干扰噪声比（ＳＩＮＲ）的局部最优化回题，并对Ｐｏｉｎｃａｒｃ极化球上大圆轨道约束与圆环轨道约束这两种情况下的ＳＩＮＲ最优化问题进行了比较，对于测量过程中信号极化或干扰极化或干扰极化为已知的情况，本文提出了两种全局变极化策略，并研究了这两处策略对ＳＩＮＲ量优化的影响以及二者在     

信号最优极化滤波及性能分析

研究了信号最优极化滤波问题,以信号干扰噪声比(SINR)为目标函数建立了带非线性约束的优化模型,利用变量代换将其转化为无约束的优化问题,利用极值必要条件将优化问题转化为一元二次方程求根问题,导出了最大SINR和最优接收极化的解析表达式。性能分析表明:信号和干扰极化状态差异越大,滤波性能越好,完全极化干扰容易被抑制,而部分极化干扰效果好。     

复杂电磁环境下雷达极化信号的优化接收

利用极化轨道的概念实现了变极化自由度的降维过程,将极化轨道上的极化滤波推广到了多散射源的情况,并在极化轨道约束下研究了信号干扰功率差的优化问题,通过仿真对利用局部最优化改善信号接收的效果及性能进行分析,对我军在复杂电磁环境下的作战和训练有较高的参考价值。     

极化信号的优化接收理论：部分极化情形

本文针对部分极化波情形，利用电磁波的Ｓｔｏｋｅｓ矢量表示法研究了极化信号的优化接收问题；利用Ｌａｇｒａｎｇｅ乘子法，分别推导了以信号干扰功率差（ＰＤＳＩ）和信号干扰噪声比（ＳＩＮＲ）作为优化目标函数时拉收天线的全局最优极化；并通过数值实例验证了中文结论。     

极化信号的优化接收理论:部分极化情形

本文针对部分极化波情形,利用电磁波的Stokes矢量表示法研究了极化信号的优化接收问题;利用Lagrange乘子法,分别推导了以信号干扰功率差(PDSI)和信号干扰噪声比(SINR)作为优化目标函数时接收天线的全局最优极化;并通过数值实例验证了文中结论。     

基于椭圆参数的最优接收极化

从极化的椭圆参数与极化球的Stokes参数的关系出发,直接推导出干扰环境下极化球面上的优化接收信号干扰噪声比参量表示式。该式对极化优化接收和信号增强很有用处。尽管难以得到全局最优解析解,但仍比较详细地给出了小圆和大圆轨道下的局部最优解,并进行了仿真。     

实数加权极化变换法

A.J.Poelman等曾提出一种基于非线性极化变换的滤波方法,能有效提高极化滤波的抗干扰能力,但其算法随非线性程度的增加会变得越来越复杂.为此本文提出一种单通道实数加权极化变换方法,该算法具有结构简单,易于硬件实现的特点.文中给出按输出干扰最小为准则的极化滤波器的固有抗干扰能力只有50%,即只能在极化域内滤除一半的干扰,当采用上述极化变换法后,根据信号极化状态的不同抗干扰能力可以提高到57.7~100%.最后文中还讨论了算法参数的估计问题.     

极化轨道约束下的最优极化（三）

本文研究了极化测量过程中的信号增强问题,提出利用信号干扰功率差（ＰＤＳＩ）作为优化目标函数,以改善恶劣电磁环境中的信号接收质量。文中求解了以ＰＤＳＩ作为目标函数时的全局最优极化以及极化轨道约束下的局部最优极化,并给出最优极化对改善信号接收效果以及极化轨道对于改善信号接收效果有效度的定量描述。     

基于ICA的交叉极化干扰抑制算法

针对极化复用模式中引入的交叉极化干扰问题,利用一种基于独立成分分析（ICA）的盲分离算法,无需信号先验知识和后续解调即可从观测信号中分离出源信号,达到消除极化干扰的目的。该算法基于线性瞬时混合模型,对峭度对比函数进行精确线性搜索优化,选取最佳步长,解决了盲分离信号中的排序问题。文中对不同信噪比和极化隔离度下的分离效果进行了仿真,仿真结果表明,该算法具有较好的分离性能,且在强交叉极化干扰和低信噪比下的性能较为稳定。     

雷达目标互易性的最小变质修正法

针对雷达目标互易性修正问题,从极化测量误差模型出发,提出了基于最小变质准则的散射矩阵修正方法.经过推导,把一个四维带约束非线性最优化问题转化为一个二维无约束非线性最优化问题,并给出了求解过程.最后通过仿真实验比较了最小变质修正法和Cameron修正法的性能,验证了最小变质修正法的可行性和优越性.     

Robust uplink power control for co-channel two-tier femtocell networks

This paper is concerned with uplink interference suppression problem in two-tier femtocell networks through power control. Specifically, we consider the Quality-of-Service (QoS) of the macrocell user and femtocell users in terms of their received Signal to Interference-plus-Noise Ratios (SINRs) at macrocell base station (MBS) and femtocell base stations (FBSs), and we also take femtocell users’ power efficiency into consideration by designing an objective function, which is a weighted sum of transmission power and squared SINR difference between femtocell user's maximum SINR and actual SINR. Due to the error of the SINR at MBS caused by distance errors, a robust uplink power control problem is formulated, and it is equivalent to a robust convex optimization problem with femtocell users’ SINR constraints. Then, the robust convex optimization problem is converted into a general convex optimization problem. Moreover, a distributed power control algorithm combined with admission control is presented to obtain femtocell users’ optimal power allocation. Numerical results show the convergence and effectiveness of the proposed uplink power control algorithm.     

Robust Beamforming via Worst-Case SINR Maximization

Minimum variance beamforming, which uses a weight vector that maximizes the signal-to-interference-plus-noise ratio (SINR), is often sensitive to estimation error and uncertainty in the parameters, steering vector and covariance matrix. Robust beamforming attempts to systematically alleviate this sensitivity by explicitly incorporating a data uncertainty model in the optimization problem. In this paper, we consider robust beamforming via worst-case SINR maximization, that is, the problem of finding a weight vector that maximizes the worst-case SINR over the uncertainty model. We show that with a general convex uncertainty model, the worst-case SINR maximization problem can be solved by using convex optimization. In particular, when the uncertainty model can be represented by linear matrix inequalities, the worst-case SINR maximization problem can be solved via semidefinite programming. The convex formulation result allows us to handle more general uncertainty models than prior work using a special form of uncertainty model. We illustrate the method with a numerical example.     

Robust Adaptive Beamformers Based on Worst-Case Optimization and Constraints on Magnitude Response

In this paper, novel robust adaptive beamformers are proposed with constraints on array magnitude response. With the transformation from the array output power and the magnitude response to linear functions of the autocorrelation sequence of the array weight, the optimization of an adaptive beamformer, which is often described as a quadratic optimization problem in conventional beamforming methods, is then reformulated as a linear programming (LP) problem. Unlike conventional robust beamformers, the proposed method is able to flexibly control the robust response region with specified beamwidth and response ripple. In practice, an array has many imperfections besides steering direction error. In order to make the adaptive beamformer robust against all kinds of imperfections, worst-case optimization is exploited to reconstruct the robust beamformer. By minimizing array output power with the existence of the worst-case array imperfections, the robust beamforming can be expressed as a second-order cone programming (SOCP) problem. The resultant beamformer possesses superior robustness against arbitrary array imperfections. With the proposed methods, a large robust response region and a high signal-to-interference-plus-noise ratio (SINR) enhancement can be achieved readily. Simple implementation, flexible performance control, as well as significant SINR enhancement, support the practicability of the proposed methods.     

机间数据链系统的功率分配控制方法

针对想定战场中机间数据链网络通信模型的上行链路功率控制问题,采用了一种基于多目标灰狼算法(Multi-objective Grey Wolf Optimizer,MOGWO)的功率控制方法.将功率控制建模为多目标优化问题,以最小化上行链路中各节点功率、使各节点在接收机处的信干噪比值(Signal-to-In-terference plus Noise Ratio,SINR)接近目标SINR和最小化通信时截获概率为多目标优化问题建立模型,利用MOGWO求解问题模型Pareto前沿,依据系统选解准则求得最佳解.结果表明,MOGWO、多目标粒子群算法、基于分解的多目标进化算法与多目标蚁狮算法所得解对应各节点SINR的平均标准偏差分别为0.0968、0.3544、1.0900和0.3083.在恒定功率方法下最远节点处SINR已不满足正常通信需求,验证了MOGWO功率控制方法有更好的稳定性与寻优能力.     

基于SINR最优的VoLTE异频切换优化

随着低频段重耕,城区LTE网络实现了1.8 G/2.1 G/800 MHz重叠覆盖,优化异频切换以利用不同频段覆盖的互补性提升VoLTE用户感知是网络优化的重要课题。通过分析路径损耗、SINR、切换对MOS的影响,SINR是其中决定性的因素,根据测试获取的RSRP和SINR之间的映射关系,提出了基于SINR最优的800 MHz和1.8 G/2.1 G异频切换优化方法。经应用验证,优化后可获得更好的的网络性能。     

A Novel Adaptive Beamformer Based on Semidefinite Programming (SDP) With Magnitude Response Constraints

A novel robust adaptive beamformer, formulated as a semidefinite programming (SDP) problem, is proposed in this paper. With new constraints on the magnitude response, the beamwidth and response ripple of the robust response region can be well controlled. Moreover, only a small part of these inequality constraints on the magnitude response are active during optimization so that few degrees of freedom (DOFs) of the adaptive beamformer are consumed. Consequently, the resultant beamformer has significant improvement on signal-to-interference-plus-noise ratio (SINR). An important problem in the proposed beamformer is how to generate the array weight vector from the optimal semidefinite matrix. In this paper, a method utilizing the extended spectral factorization method is proposed to solve this problem. Simple implementation, flexible performance control as well as significant SINR enhancement support the practicability of the proposed method.     

极化轨道约束下的最优极化（一）

本文针对极化测量过程中干扰和噪声对接收效果的影响，提出一种极化轨道约束下的变极化接收方法，以改卷接收系统的SINR（信号干扰噪声比）。在极化轨道约束下的SINR最大化问题是一个寻求局部最优的问题，本文在任意的信号与干扰极化条件下，解决了任意给定的极化轨道上SINR的最大化问题，并对极化轨迈上最优极化与其他两种最优极化得到的SINR进行了比较。     

Ant-Colony-Optimization-Based Scheduling Algorithm for Uplink CDMA Nonreal-Time Data

Scheduling plays an important role in determining the overall performance of code-division multiple-access (CDMA) systems. This paper is focused on the uplink scheduling of CDMA nonreal-time data. In practical CDMA systems, data can only be transmitted with a few fixed transmission rates. Moreover, to guarantee receiving accuracy, the actual received signal-power-to-interference-plus-noise-power ratio (SINR) is expected to be no less than the target SINR value. Using Heaviside unit step functions, the relationship between the actual SINR value and the actual available maximum transmission rate is described in the proposed system model. Based on the proposed system model, an integer optimization problem is formulated to simultaneously maximize the throughput and the scheduling efficiency. Particularly, an ant-colony-optimization (ACO)-based scheduling algorithm is proposed to solve the proposed optimization problem. The computational complexity analysis indicates that the proposed ACO-based scheduling algorithm is computationally efficient in terms of both running time and storage space. In addition, the numerical results show that the proposed optimization problem is more efficient at guiding the development of scheduling algorithms for uplink CDMA nonreal-time data. Moreover, the proposed ACO-based scheduling algorithm performs quite well in terms of quality, running time, and stability.     

杂波环境下共享频谱恒模波形设计

针对射频频谱环境愈发拥挤问题,深入研究了通过波形设计的手段实现频谱共享的问题。为紧密贴近工程实践,提出了一种新的方法设计恒定幅度信号的问题。该算法首先针对雷达发射端,提出雷达波形满足特定的时域与频谱要求,施加约束,然后考虑雷达接收滤波器接收杂波,以优化最大信干噪比建立优化问题模型,得到了一个非凸的分式规划问题模型。最后,利用分步优化方法分解为两个优化问题,并且将非凸问题松弛为可解的凸问题再利用高斯随机化方法得到优化信号,多次循环优化。仿真结果验证了该算法的有效性,该方法设计得到的探测信号能够实现频谱共存,而且信干噪比性能能够得到保证。      

Waveform optimization for MIMO-STAP to improve the detection performance

In this letter, we address the problem of waveform optimization for multi-input multi-output (MIMO) space-time adaptive processing (STAP) in the presence of colored Gaussian disturbance. A novel diagonal loading (DL) based method is proposed to optimize the waveform covariance matrix (WCM) for maximizing the output signal-interference-noise ratio (SINR) of MIMO-STAP such that the detection performance can be maximized. The resultant nonlinear optimization problem is reformulated as a semidefinite programming (SDP) one, which can be solved very efficiently. Simulation results show that the output SINR of MIMO-STAP can be improved considerably by the proposed method, as compared to that of uncorrelated waveforms.