Signal-to-noise ratio of lensless ghost interference with thermal incoherent light

Factors influencing the signal-to-noise ratio （SNR） of lensless ghost interference with thermal incoherent light are investigated. Our result shows that the SNR of lensless ghost interference is related to the transverse length of the object, the position of the object in the imaging system and the transverse size of the light source. Furthermore, the effects of these factors on the SNR are discussed in detail by numerical simulations.

New Technique for Estimating and Suppressing Narrowband Interference in DSSS Systems

A generalized approach for narrowband interference （NBI） suppression in direct sequence spread spectrum （DSSS） communication systems using adaptive infinite impulse response （IIR） filter is presented. The excision filter coefficients depend on both the jammer power and its instantaneous frequency. The dependency of the filter construction on the jammer power is significant as it allows optimal tradeoff between interference removal and signal distortion by maximizing the receiver signal to noise ratio improvement（SNRI）. Instead of traditional adaptive line enhancer （ALE） estimator, a preferable NBI estimator-Fourier interpolation estimator （FIE） is proposed. Closed-form expressions of the SNR improvement and theoretical bit error rate （BER） based on the assumption that the output of the correlator is Gaussian distributed are both derived. Performance results obtained by numerical simulation are also presented and compared with theoretical results.

基于SINR的动态无线网络分布式链路调度

无线信号之间的干扰阻碍了信号的并发传输,降低了无线网络的吞吐量.链路调度是提高无线网络吞吐量、减少信号传输延迟的一种有效方法.因为SINR (signal to interference plus noise ratio)模型准确地描述了无线信号传播的固有特性,能够真实反映无线信号之间的干扰,提出一种在动态无线网络中基于SINR模型的常数近似因子的在线分布式链路调度算法(OLD_LS).在线的意思是指,在算法执行的过程中任意节点可以随时加入网络,也可以随时离开网络.节点任意加入网络或者从网络中离开体现了无线网络的动态变化的特性. OLD_LS算法把网络区域划分为多个正六边形,局部化SINR模型的全局干扰.设计动态网络下的领导者选举算法(LE),只要网络节点的动态变化速率小于1/ε, LE就可以在O(log n+log R)ε≤5(1-21-α/2)/6,α表示路径损耗指数, n是网络节点的规模, R是最长链路的长度.根据文献调研,所提算法是第1个用于动态无线网络的在线分布式链路调度算法.

A BLIND SNR ESTIMATOR FOR DIGITAL BANDPASS SIGNALS

A subspace-based blind Signal-to-Noise Ratio (SNR) estimation algorithm for digital bandpass signals in Additive White Gaussian Noise (AWGN) channel is discussed. The lower bounds of the mean and variance of the estimation are derived, and simulations are performed for the commonly used digital bandpass signals, such as MPSK (M=2, 4, 8), MFSK (M=2, 4) and MQAM (M=16, 64, 128, 256) signals. Theoretical analyses and simulation results indicate that the proposed algorithm is ef- fective even when the SNR is below 0dB. Furthermore, the algorithm can provide a blind estimator in that it needs neither the parameters of the received signals, such as the carrier frequency, symbol rate and modulation scheme, nor the synchronization of the system.

A NOVEL METHOD FOR ESTIMATING THE SNR OF UNKNOWN EMITTER SIGNAL

It is important to estimate the Signal-to-Noise Ratio(SNR) of unknown emitter signal accurately.In order to resolve the disadvantages of present algorithm,a novel method is proposed in this letter.We extract and normalize the information of zero frequency of received signal by the Wigner-Vile Distribution(WVD) transformation and then get the approximate power of original signal by mathematic transformation,at last,we get the estimate value of SNR by the known account formula of SNR.Simulation results show that it is correct and feasible.

Interference Mitigation Techniques Using Receiver Processing and Resource Allocation

Heterogeneous network consists of the pico cells overlaid over the macro cell coverage area in a wireless cellular network. The pico cells are deployed to increase the capacity of the homogeneous network by reusing the spectrum further. However, more users will tend to be associated to the macro cell due to the fact that the transmit power of the pico cell is low. In order to increase the number of users associated to the pico cell, range extension techniques like biased association are used. This will cause severe interference to cell edge users of the pico cell from the macro cell causing degradation in throughput performance in the cell range extension area. In this paper, interference mitigation using receiver processing along with different scheduling techniques is proposed to improve the throughput, average delay, and the packet delivery ratio performance of the system. The performance comparison of the round robin, proportional fair and modified largest weighted delay first (MLWDF) algorithm for resource allocation using interference suppressing receiver is done, and analyzed. It is shown that the MLWDF algorithm achieves the highest throughput with minimum average delay of packets with the best delivery ratio.

Simultaneous optical signal to noise ratio and symbol rate estimation with blind chromatic dispersion compensation for auxiliary amplitude modulation optical signals

Based on the peak to valley ratio（PTVR） of the average magnitude difference function（AMDF）, we present a novel optical signal to noise ratio（OSNR） and symbol rate（SR） estimation method for commonly used auxiliary amplitude modulations（AAMs）. Moreover, it is demonstrated that the influence of chromatic dispersion（CD）on the method can be mitigated by maximizing the PTVR of the AMDF with additional tunable dispersion compensators. The results of simulations show that the OSNR estimation error can be kept within 0.8 dB in the wide OSNR range of（12, 32） dB, while the SR estimation error is below 0.079% for four widely used10 Gsymbol/s AAM signals.

Channel Estimation and Compensation for Underwater Acoustic Pipeline Communication

An estimation and compensation algorithm for underwater acoustic pipeline channel is investigated.A joint time-frequency adaptive signal-to-noise ratio（SNR）estimation based on the maximum likelihood method is introduced firstly,and the Cramer-Rao lower bound（CRLB）is proposed so as to evaluate the performance of the SNR estimation algorithm.For frequency-selective fading channel part,estimation and compensation are made to improve the robustness of the system on the basis of the LMS algorithm.Furthermore,real-time update iteration algorithm in the frequency domain is investigated to realize synchronous receiving and estimation.For verification,simulations and actual data tests were made,and the results show that the algorithm possesses great robustness,efficiency and accuracy inrealization of SNR estimation,signal detection and frequency impulse compensation for the channel.

Parametric SNR Estimation Based on Auto-Regressive Model in AWGN Channels

Signal-to-noise ratio（SNR）estimation for signal which can be modeled by Auto-regressive（AR）process is studied in this paper.First,the conventional frequency domain method is introduced to estimate the SNR for the received signal in additive white Gauss noise（AWGN）channel.Then a parametric SNR estimation algorithm is proposed by taking advantage of the AR model information of the received signal.The simulation results show that the proposed parametric method has better performance than the conventional frequency doma in method in case of AWGN channel.

An Effective Method of SNR Estimation for LDPC-CPM

The technique of SNR estimation is one of the key technologies in adaptive frequency hopping system. The methods of channel quality estimation for non-linear continuous phase modulation (CPM) signals have some limitations. Therefore, the algorithm of channel quality estimation for CPM signals is worthy of further study. Some similar phase characteristics between sampling CPM and MPSK motivate us to propose a channel estimation algorithm with applications to nonlinear CPM using linear modulation signal processing. A comprehensive analysis of LDPC-CPM schemes using proposed algorithm is presented, and simulation results indicate that the proposed method can not only estimate channel quality well but also make the normalized MSE (NMSE) of SNR estimate close to/less than 0.1 dB at SNR of 4 dB using short block codes. It shows that the algorithm in this paper is effective enough to estimate the signal to noise ratio (SNR). Meanwhile, the algorithm in this paper reduces the complexity of computation compared with other traditional algorithms.

基于线性调频连续波的合作式通信辐射源测距

针对加速运动目标参数估计中,离散多项式变换方法无法进行非整数估计的问题,本文提出基于瑞夫算法的离散多项式变换法和基于Chirp-Z变换的离散多项式变换法2种新型离散多项式变换算法,对加速运动目标速度和加速度进行估计,并对2种算法的估计误差和计算量进行了分析比较。结果表明:2种算法在信噪比-20 dB时均方误差开始接近克拉美罗界。基于瑞夫算法的离散多项式变换法与3次迭代基于Chirp-Z变换的离散多项式变换法均可在较低信噪比下可实现任意频率的有效估计且性能接近,二者均可实现低信噪比下速度、加速度的有效估计,但基于瑞夫算法的离散多项式变换法计算量远小于3次迭代基于Chirp-Z变换的离散多项式变换法。

基于活动性检测动态估计噪声的心音降噪算法

针对基于小波分解和最优改进对数幅度谱估计的心音降噪算法存在噪声残留和心音失真的问题,提出一种基于心音活动性检测(HSAD)动态估计噪声的心音降噪算法。通过设计的HSAD判断当前心音帧是否为基础心音帧(FHS),根据判断结果分别采用改进最小值控制递归平均(IMCRA)算法和递归平滑算法对噪声功率进行动态估计与更新,采用非因果先验信噪比,实现心音信号的降噪。实验结果表明,提出算法能更好在提升降噪性能的同时,降低FHS的失真。

一种适用于卫星通信的自适应窄带干扰抑制方法

针对卫星通信系统中的抗干扰问题,提出一种能够根据干扰变化自适应调整策略的干扰抑制方法。该方法通过子带分割、按功率排序、依次陷波等方式进行陷波,然后对比陷波前后信号信噪比的增益,从而确定信噪比增益最大时所对应的子带陷波个数,最终得到信噪比增益最高也即性能最优的陷波方式。该方法不需要预先进行干扰检测,也不需要寻找和设置门限阈值,就可以对多种类型干扰进行自适应陷波,从而达到有效抑制包含单音、窄带、梳状或部分频带等不同干扰的目的,能够显著改善链路的通信性能,提高通信系统的抗干扰能力。

异构无线网络中基于SINR和层次分析法的SAW垂直切换算法研究

B3G或者4G无线网络体系致力于集成各种异构无线接入网络,其中一个主要的设计课题是支持垂直切换的研究。该文将多属性QoS考虑在内,针对各业务特点,提出一种基于SINR(信干噪比)和层次分析法(AHP)的SAW(简单加权法)垂直切换算法(SASAW)。它综合考虑SINR的影响以及要获得同等数据速率情况下,目标网络需要的等效SINR数值、用户通信代价、网络可用带宽等来构造属性矩阵做切换判决。为了评估性能,考虑3GPP定义的4类业务,利用层次分析法中的特征向量法来决定各个QoS属性之间的权重关系,构造比较判决矩阵并检验其一致性;根据判决矩阵,利用特征根法获得权重向量;最后根据属性矩阵和权重向量,利用SAW垂直切换算法进行判决。通过对算法的通过率、丢话率、垂直切换次数、平均用户代价等的性能比较,结果表明该文提出的算法能够根据各业务特点综合考虑各属性间关系,获得优良的系统性能。

基于小波奇异特征约束的期望最大时延估计算法

针对低信噪比条件下非平稳信号时延估计精度低的问题,提出基于小波奇异特征约束的期望最大时延估计算法。设计小波奇异性特征尺度广义互相关矩阵,构建多尺度小波奇异特征约束下的期望最大化模型。推导参数更新公式,利用期望最大化算法并行迭代,求取奇异性特征显著性最大条件下信号的自适应尺度以及该尺度下声源信号的最优时延估计值。仿真和实验结果表明,所提算法在低信噪比条件下,相较于传统广义互相关时延估计算法以及改进算法具有较高的时延估计精度,并且有效提高了误差约束范围内的有效估计成功率。

利用双通道激光雷达验证低信噪比反演算法

针对相干测风激光雷达(LiDAR)在低信噪比(SNR)下反演算法的可靠性和精度难以验证的问题,搭建了一种双通道的脉冲相干测风LiDAR系统,可以同时获取高、低SNR的2组数据,并使用高SNR通道的结果作为真值,比较利用不同的算法在低SNR通道进行矢量风速估计的结果。该系统避免了使用其他观测设备作为真值时难以配准或观测目标不统一的问题。本文研究利用雷达获取的观测结果验证了各个算法的有效性,并在各个算法间进行了横向对比。最终,依据各个算法的性能表现和计算复杂度,指明了各个算法具有优势的使用场景。该结果对于充分利用现有系统、使用新算法提高低SNR下的数据获取效率,或在指定探测指标的前提下降低激光能量等硬件要求、实现系统小型化有一定意义。

DFT扩频广义多载波系统的SINR性能分析

针对离散傅立叶变换扩频的广义多载波系统(DFT-S-GMC),提出一种信干噪比(SINR)的性能分析方法。该方法基于DFT-S-GMC收发机频域等效的简化实现结构,利用信道频率响应和噪声方差,接收端采用最小均方误差(MMSE)均衡,分析得到了SINR的闭合表达式,并考虑了信道均衡后时域复用的数据块(IFBT符号)之间的残余干扰,而且,本方法很容易扩展到一发多收的情况。仿真表明,多径信道下基于该等效SINR的误块率(BLER)性能曲线能很好地匹配系统在高斯白噪声信道下的性能曲线。

基于MF预编码的大规模MIMO网络SINR概率密度分析

大规模MIMO系统中,相对于其他基于信道矩阵分解的波束成形算法,如迫零、最小均方误差算法等,匹配滤波(Matched filter,MF)具有复杂度极低的优点,从而成为一种极具实用潜力的波束成形算法。鉴于此,本文推导了基站采用MF波束成形算法时,用户端信干噪比(Signal-to-interferenceand-noise ratio,SINR)的近似概率密度函数(Probability density function,PDF)。该函数对于推导与分析系统性能,如和速率、中断概率等至关重要。仿真表明:当基站天线数趋于大规模时,SINR公式的PDF曲线趋近于通过纯仿真得到的PDF曲线。

幅相误差对体积阵MVDR波束形成的影响

体积阵是一种由多个水听器组成的立体阵列,能够增大潜标接收基阵的孔径,获得较大的空间增益,工程中多将其制作成具有收合、展开功能的阵列应用于低频吊放声呐。由于各水听器通道内器件参数和幅度增益不一致,体积阵的每个阵元接收到的信号之间存在幅相误差。文中通过建立存在幅相误差时的双圆环体积阵模型,从统计学角度分析了幅相误差对其协方差矩阵、最小方差无畸变(MVDR)波束形成器的输出信噪比(SNR)、阵增益以及方位估计精度的影响。计算机仿真结果表明,阵列幅相误差的存在会导致MVDR波束形成器的输出SNR和阵增益降低;对于相位误差而言,当输入SNR在-5 dB以上时,这种影响随输入SNR的增大越来越明显;对于幅度误差而言,当输入SNR在-10 dB以上时,幅度误差对MVDR波束形成器的输出SNR和阵增益的影响会更显著;并且,相比于幅度误差,MVDR波束形成的方位估计精度对相位误差更加敏感。

基于分式二次规划的互模糊函数赋形方法

在开展认知雷达波形设计时,由于发射波形与接收滤波器的非匹配体制,互模糊函数赋形相比传统模糊函数赋形优化自由度更高。该文针对强杂波条件下微弱运动目标检测问题,以最大化信干噪比为优化准则,提出了一种联合发射相位编码序列与接收滤波器设计的互模糊函数赋形方法。在恒模约束下,优化问题被建模为二次分式规划形式;然后通过引入辅助变量,并利用共轭梯度法求解Stiefel流形空间上的最小化问题,非凸优化据此转化为恒模约束二次优化问题;通过交替循环和类幂迭代算法求得最优解。此外考虑到发射波形受硬件限制而难以实现严格恒模,该文构建了一种低峰均比约束二次优化问题模型,并利用最近邻向量法求得最优解。最后,不同参数下的仿真与实测数据实验表明,该文赋形方法相较于传统方法具有较高的信干噪比增益和收敛速度。