一种多用户MIMO系统干扰对齐优化算法

干扰对齐技术可以获得干扰信道自由度的最佳值,从而有效改善系统的性能。在实际系统中干扰对齐技术通常采用迭代的方法进行预编码矩阵与干扰抑制矩阵的设计,而迭代方法都需要对发送预编码矩阵进行初始化处理。然而,目前大多数已有的研究所采用的初始化处理方法都忽略了干扰的影响。因此,在此基础上提出了一种基于新的初始化方法的优化算法,该方法在初始化预编码矩阵中既考虑了干扰信号也考虑了有用信号。首先,选取均方误差和最小化作为优化目标,然后利用正交三角（QR）分解将信道空间分为有用信号空间与干扰信号空间来进行预编码矩阵的初始化设计,经过反复迭代得到发送预编码矩阵与干扰抑制矩阵的最优解。理论分析和仿真结果表明,所提算法在收敛性、均方误差、和速率等方面都优于其他算法。     

MIMO干扰信道下的协作干扰对齐优化算法

干扰对齐是将来自其他发射机的干扰信号对准到同一信号子空间,从而减少对期望信号的干扰的一种传输技术,近年来得到了广泛的关注.本文为K用户多输入多输出(MIMO)干扰信道系统提出了一种协作干扰对齐优化算法.通过对信道的奇异值分解,基于矩阵弦距离,不仅选出一组最好的特征子信道来传输信号,而且还选取一组有利于有用信号远离干扰信号的预编码矩阵,这样,可以最大化减少干扰对有用信号的影响.另外,本文还根据得出的预编码矩阵来计算和优化干扰抑制矩阵.本文算法在没有用迭代的基础上来计算预编码矩阵和干扰抑制矩阵,这样不仅使整个系统的复杂度大大降低,进一步,仿真结果显示容量和能量效率较其他算法有明显改进,这也正是最近受到广泛瞩目的绿色通信所要求的.     

认知型飞蜂窝网络中的子信道分配与功率控制

为了解决宏蜂窝与飞蜂窝构成的两层异构网络上行干扰与资源分配问题,提出了一种在认知型飞蜂窝的双层异构网中结合子信道分配和功率控制进行资源分配的框架。通过对异构网中跨层干扰问题进行分析与建模,将求解最优子信道分配矩阵和用户发射功率矩阵作为干扰管理问题的解决方法。模型中认知型飞蜂窝网络子信道和飞蜂窝网络用户构成非合作博弈,双方利用效用函数最优值进行匹配,构成初始信道分配矩阵;再由接入控制器根据接入条件从初始信道分配矩阵中筛选用户,并优化接入用户的发射功率矩阵,得到最优子信道分配矩阵和功率矩阵。仿真结果表明,优化框架提高了双层异构网络中飞蜂窝网络用户的吞吐量和接入率,降低了异构网中跨层干扰。     

最大化瑞利熵的干扰对齐优化算法

干扰对齐技术常采用迭代的方法进行预编码矩阵与干扰抑制矩阵的设计,然而目前采用的迭代方法并不能做到完全的干扰对齐。针对这种情况,提出了一种新的干扰对齐优化算法,避开了反转信道的操作。该算法在最大化信干噪比算法的基础上加入完全干扰对齐的约束条件,将系统中各用户的所有干扰对齐约束条件进行奇异值分解,最终通过瑞利熵最大化的求解方法联合迭代求解发送侧的预编码矩阵与接收侧的干扰抑制矩阵。仿真结果表明,所提优化算法在较高信噪比时不同天线数下的和速率、不同迭代次数下的和速率等方面都优于原最大信干噪比算法。     

基于矩阵补全的天波雷达瞬态干扰抑制算法

瞬态干扰持续时间短、强度大,严重影响天波超视距雷达的性能。传统的瞬态干扰抑制方法需要预先抑制海杂波,且只能抑制强瞬态干扰,不能抑制弱瞬态干扰和噪声,该文提出一种基于矩阵补全的瞬态干扰抑制算法,该方法首先利用Teager-Kaiser算子进行瞬态干扰检测,然后将干扰数据剔除,最后利用海杂波和目标回波构成的Hankel矩阵的低秩性,通过改进的低秩矩阵补全算法进行数据恢复。该算法不仅能够抑制强瞬态干扰,而且能同时抑制弱瞬态干扰和噪声,提高了回波信号的信噪比。实测和仿真数据处理结果证明了算法的有效性。     

基于最强快拍法的自适应副瓣对消技术

由于实战中,电子干扰变化快、起伏大;该种变化将引起副瓣对消性能的严重下降.根据干扰的能量性质,推导出干扰对自相关矩阵的影响.在存在干扰时,自相关矩阵必然存在若干个显著的特征值,大的特征值是由干扰的强能量所致.因此,对回波信号进行能量开窗积累,即可取出最强能量片段,并据此估算自相关矩阵和互相关向量,进行副瓣对消.该方法已应用于某新型监视雷达中.实践表明,与传统副瓣对消技术相比,该方法可显著提升副瓣对消在实战中的对消能力.     

MIMO干扰信道下低复杂度的分布式干扰对齐算法

干扰对齐技术可以有效地提高干扰信道容量和抑制干扰,其问题归结为求得闭式解。传统的干扰对齐方案根据信道的互易性,采用迭代的方法（分布式）来逼近闭式解,但带来了较大的计算开销。本文在K用户MIMO干扰信道系统中提出一种低复杂度的分布式干扰对齐算法,通过对用户K的干扰协方差矩阵进行基于修正的Gram-Schmidt方法使用排序QR分解,选出酉矩阵Q最后的dk列作为用户近似的干扰抑制滤波矩阵,和传统分布式干扰对齐方案相比,在基本保持系统容量和迭代收敛速度的同时,系统的复杂度明显降低。仿真结果验证了算法的有效性。      

一种基于最大化Rayleigh熵的稳健干扰对齐算法

干扰对齐在消除干扰方面具有独到的优势,但需要完美的信道状态信息(CSI),这在实际中很难实现。该文分析了传统稳健干扰对齐方案的优缺点,在此基础上,提出一种最大化Rayleigh熵的稳健干扰对齐算法,并对收敛性,自由度和频谱效率等进行了分析。不同于MAX-SINR算法,该文通过最大化信号的Rayleigh熵,求得干扰抑制矩阵。在正向通信中,考虑到数据流之间的相关性取干扰抑制矩阵为原始干扰抑制矩阵的酉矩阵形式,并采用注水功率分配实现用户数据流间的最佳功率分配;基于信道的互惠性,在反向通信时,做类似的处理。通过迭代计算,逐渐将干扰压缩。最后,在完美CSI和误差CSI时,仿真表明该算法显著地提高了系统的性能。     

知识辅助的两级自适应抗干扰技术

机载雷达通常工作在强杂波、强干扰的复杂电磁环境中,如何有效消除压制干扰抑制杂波是其中的关键问题。传统的两级空时自适应处理( STAP )算法在静默期采集信号得到干扰子空间,在开机阶段运用空间投影技术抑制干扰并采用降维STAP抑制杂波。虽然该算法在干扰平稳时具有较好的效果,但是在实际应用中,复杂的干扰环境会破坏广义平稳假设。因此,仅采集单个静默期的干扰样本来估计协方差矩阵会出现偏差。为了克服该问题,提出采集多个静默期的干扰信号来估计当前的干扰协方差矩阵,以此来提高估计准确度,可以更好地抑制干扰。仿真结果表明即使在当前静默期采集的干扰信息不完整时,该技术仍然能够利用以前的干扰信息准确估计干扰协方差矩阵。     

Nash bargaining solution based multi-cell and multi-user interference alignment scheme for cellular networks

In wireless cellular networks, the interference alignment （IA） is a promising technique for interference management. A new IA scheme for downlink cellular network with multi-cell and multi-user was proposed, in the proposed scheme, the interference in the networks is divided into inter-cell interference （ICI） among cells and inter-user interference （IUI） in each cell. The ICI is aligned onto a multi-dimensional subspace by multiplying the ICI alignment precoding matrix which is designed by the singular value decomposition （SVD） scheme at the base station （BS） side. The aligned ICI is eliminated by timing the interference suppression matrix which is designed by zero-forcing （ZF） scheme at the user equipment （UE） side. Meanwhile, the IUI is aligned by multiplying the IUI alignment precoding matrix which is designed based on Nash bargaining solution （NBS） in game theory. The NBS is solved by the particle swarm optimization （PSO） method. Simulations show that, compared with the traditional ZF IA scheme, the proposed scheme can obtain higher data rate and guarantee the data rate fairness of UEs with little additional complexity.     

LTE上行通信链路中WiFi同频干扰的一种抑制方法

考虑多接收天线的第三代移动通信长期演进(LTE,long term evolution)上行通信链路,针对该链路中的Wi-Fi同频干扰,提出了一种新的多天线合并方法:干扰重建抑制合并(IRRC,interference reconstruction rejectioncombining)。首先估计接收信号的协方差矩阵,并将其作为干扰信号协方差矩阵的近似值;再应用干扰抑制合并(IRC,interference rejection combining)恢复期望信号;然后从接收信号中剔除期望信号,得到重建的干扰信号;最后,再次估计干扰信号的协方差矩阵,并进行干扰抑制合并。多径衰落信道中的仿真结果表明:考虑一发两收、正交相移键控(QPSK,quadrature phase shift keying)调制、0dB干信比的LTE上行信号,与传统的IRC方法相比,最小均方误差准则下应用IRRC方法约有2dB的发射功率改善。     

任意平面阵列的干扰抑制

本文提出一种任意平面阵列抑制干扰的方法.对任意平面阵列的接收信号进行多次正交变换,然后对变换后信号的自相关矩阵求平均值,所得矩阵应用最大信号与干扰加噪声功率比准则求得抑制干扰的权值.计算机模拟实验表明,该方法能有效抑制干扰且对干扰信号之间的相关特性没有要求.     

Eigenstructure based partially adaptive array design

A procedure is presented for designing partially adaptive arrays having nearly fully adaptive performance under steady-state conditions. Theory predicts that the required adaptive dimension is less than or equal to the rank of the spatially/temporally correlated portion of the interference correlation matrix for arbitrary linearly constrained minimum-variance beamformers. Knowledge of the eigenstructure of the interference correlation matrix is required to implement a beamformer with this adaptive dimension. To avoid adaptive estimation of the eigenstructure, the eigenstructure of an averaged correlation matrix (which spans the interference scenarios of interest) is utilized, and the adaptive dimension is given by the rank of the averaged correlation matrix. Construction of a transformation for reducing adaptive dimension is addressed. Simulations illustrating the utility of the eigenstructure approach are provided     

一种相干信号自适应波束形成零陷展宽算法

针对传统自适应波束形成器在相干干扰位置出现快速变化时,输出性能下降,甚至干扰抑制失效的问题,提出了一种相干信号自适应波束形成零陷展宽算法。首先,对接收数据协方差矩阵进行解相干处理得到Toeplitz矩阵;其次,对协方差矩阵进行重构和优化;最后,进行零陷展宽和对角加载处理。仿真结果表明：该算法不仅能对相干干扰自适应形成宽零陷,而且可以灵活地控制零陷的深度和宽度;与Mailloux算法相比,在输入信噪比较高的情况下,该算法能得到更低的波束旁瓣电平和更高的输出信干噪比     

Fast converging adaptive detection of Doppler-shifted,range-distributed targets

A generalized likelihood ratio test (GLRT) for the adaptive detection of a target or targets that are Doppler-shifted and distributed in range is derived. The unknown parameters associated with the hypothesis test are the complex amplitudes in range of the desired target and the unknown covariance matrix of the additive interference, which is assumed to be characterized as complex zero-mean correlated Gaussian random variables. The target's or targets' complex amplitudes are assumed to be distributed across the entire input data block (sensor × range). The unknown covariance matrix is constrained to have the reasonable form of the identity matrix (the internal noise contribution) plus an unknown positive semidefinite (psdh) matrix (the external interference contribution). It is shown via simulation for a variety of interference scenarios that the new detector has the characteristic of having a bounded constant false alarm rate (CFAR), i.e., for our problem, the probability of false alarm P_F for a given detection threshold is bounded by the P_F that results when no external interference is present. It is also shown via simulation that the new detector converges relatively fast with respect to the number of sample vectors K necessary in order to achieve a given probability of detection P_D     

Blind successive interference cancellation for DS-CDMA systems

We propose a blind successive interference cancellation receiver for asynchronous direct-sequence code-division multiple-access (DS-CDMA) systems using a maximum mean energy (MME) optimization criterion. The covariance matrix of the received vector is used in conjunction with the MME criterion to realize a blind successive interference canceler that is referred to as the BIC-MME receiver. The receiver executes interference cancellation in a successive manner, starting with the most dominant interference component and successively cancelling the weaker ones. The receiver is compared against various centralized and decentralized receivers, and it is shown to perform well in the presence of estimation errors of the covariance matrix, making it suitable for application in time-varying channels. We also analyze properties of the covariance matrix estimates which are relevant to the performance of the BIC-MME receiver. Further, the BIC-MME receiver is particularly efficient in the presence of a few strong interferers as may be the case in the downlink of DS-CDMA systems where intracell user transmissions are orthogonal. An iterative implementation that results in reduced complexity is also studied     

An adaptive array utilizing an adaptive spatial averaging technique for multipath environments

When the interference is coherent with the desired signal, the conventional adaptive arrays working under the guiding principle of output power minimization tend to cancel the desired signal by using the coherent interference. A technique is described which enables the adaptive array to function even under such an environment. The array is divided into subarrays, whose input correlation matrices are adaptively averaged so as to produce a Toeplitz matrix which would be obtained when the interference did not correlate with the desired signal. The averaged matrix is now free from correlation terms between the desired signal and interference, and therefore may be used to derive the optimum weight for the array element just as in the ordinary radio environment of incoherent interference. Numerical examples show that the new adaptive array is highly capable to suppress the coherent interferences as well as incoherent ones.     

Stiefel流形上的单边干扰对齐预编码

干扰对齐通过在接收端重叠干扰能有效的提升干扰信道的容量。单边干扰对齐是指仅仅只有发射端参与的干扰对齐技术,它不需要接收端的参与,与双边干扰对齐技术相比可以大大的减小反馈量。本文在干扰子空间弦距离最小化的改进单边干扰对齐预编码算法方案的基础上,提出将预编码矩阵建模于Stiefel流形上,能够将有约束的最优化问题转化为无约束的最优化问题进行求解。仿真结果表明,将预编码矩阵在Stiefel流形上建模后求解与普通的最优化算法相比有更快的收敛速度和更高的和速率。      

稀疏信号结构性噪声干扰下的感知矩阵优化

针对具有结构性噪声干扰的稀疏信号处理问题,该文提出一种基于贝叶斯理论的感知矩阵优化设计方法。结合具有加性干扰的稀疏信号模型,通过对感知矩阵进行能量约束,最小化信号的后验协方差矩阵的迹,实现感知矩阵的优化设计。仿真不同信号稀疏度和重构算法时,感知矩阵优化对信号重构误差和重构时间的影响;分析信号先验信息存在偏差时,感知矩阵优化对重构效果的影响。仿真结果表明,优化后的感知矩阵能够更好地获取稀疏信号中的重要信息,信号重构精度的均方误差减小约15～25 dB,重构时间减少约40%。     

A novel adaptive beamformer for MEG source reconstruction effective when large background brain activities exist

This paper proposes a novel prewhitening eigenspace beamformer suitable for magnetoencephalogram (MEG) source reconstruction when large background brain activities exist. The prerequisite for the method is that control-state measurements, which contain only the contributions from the background interference, be available, and that the covariance matrix of the background interference can be obtained from such control-state measurements. The proposed method then uses this interference covariance matrix to remove the influence of the interference in the reconstruction obtained from the target measurements. A numerical example, as well as applications to two types of MEG data, demonstrates the effectiveness of the proposed method.