无线电波传播中的随机射线及其应用

对建模无线电波传播的随机射线进行了详细的阐述,从随机网格信道引出随机射线的概念,介绍了随机射线的产生背景和分类,并给出一种产生随机射线的数学模型随机桥过程。使用最大熵原理得到发生后次反射随机射线的概率分布。最后介绍使用随机射线建模超宽带室内信道的多径传播轨,在此基础上可以得到信道特性建模的基本随机变量,以及无线电波传播的概率模型等应用。     

随机射线的概率分布及其应用

在使用随机射线方法建模无线传播信道时,需要求解以反射次数为指标的无线电波经过若干次反射以后达到特定位置的概率分布。该文使用信息论中的最大熵原理,首先计算在Manhattan距离度量下二维和三维空间连续情形和离散情形下随机射线的概率密度函数。然后计算在Euclid距离度量下二维和三维空间连续情形下随机射线的概率密度函数,以及作随机游动的随机射线在二维空间的概率密度函数。使用城市密集传播地区的测量数据验证随机射线理论模型结果的可靠性。所得结果对于无线随机传播信道建模具有理论指导意义。     

随机射线方法研究无线电波多径传播特性

把无线电波的物理传播环境建模为随机网格信道,使用最大熵原理得到发生k次反射随机射线在二维传播空间的概率分布.使用随机桥过程产生基本随机变量,以自由布朗桥过程和自由Langevin桥过程为例研究其统计特性,发现基本随机变量服从Rayleigh分布或者x分布随机变量之和的分布.由基本随机变量得到描述无线信道特征参量(包括多径分量的到达时延,幅度增益绝对值和相位等)的表达式.对一个障碍物完全随机分布的二维传播环境的信道特性使用随机射线方法进行仿真分析,得到无线信道的一些特征参量的统计规律,结果与经典的信道特性一致,验证了随机射线方法的有效性.     

随机波束研究超宽带室内多径信道特性

从随机桥过程出发引入随机波束概念,使用随机波束研究超宽带（UWB）室内多径信道的传播特性.将UWB信号多径传播轨迹视作随机过程的样本,得到建模多径信道传播特性的随机波束.使用随机波束构建UWB信道的多径传播模型,并给出使用随机波束方法分析UWB室内多径信道特性的算法.使用该信道模型对实际传播环境进行仿真分析,并与其它建模UWB多径信道的方法进行了比较.仿真得到的UWB信道的功率延迟分布特性与实验测量的结果非常一致,证明此方法的有效性.     

非波动方法建模5.3GHz移动通信系统的路径损耗

根据电磁波传播的随机射线理论和渗流网格理论,得到Euclid距离和Manhattan距离度量下的二维随机网格信道中的路径损耗模型,式中参数具有明确的物理意义.使用此模型分析了视距和非视距情况下5.3GHz移动通信系统的功率分布特征.与实测数据进行比较,结果发现使用Euclid距离度量和Manhattan距离度量进行建模,所得的数值解与实际测量结果的均方误差在可以接受的范围内,证明了此模型的准确性和有效性.     

一种有多反射特性的超宽带信道建模方法

在几何单反射椭圆信道模型和几何随机信道模型基础上,针对电磁波传播过程中出现的多反射特性,提出一种多反射特性的无线信道建模方法。把该方法应用于超宽带信道研究,可以得到UWB信道的几何随机多反射模型(GSMB)。使用该方法对两个UWB信号传播环境进行仿真分析,仿真得到的UWB信道功率延迟分布与实验结果基本一致,同时也验证了其他研究者关于UWB信道中的成簇现象具有确定性的结论。     

28 GHz室内毫米波信道路径损耗模型研究

毫米波信道建模是第五代（the 5th Generation,5G）移动通信系统的关键技术,而路径损耗是表征毫米波信道传播大尺度衰落影响的重要参数.为了更好地理解毫米波信道的传播特性,应进行广泛的信道测量与建模.因此,对28 GHz室内环境进行了信道测量,并给出了相应的毫米波信道路径损耗模型,同时基于入射及反弹射线法/镜像法仿真分析了路径损耗传播特性.研究结果表明:实测结果与仿真结果一致性吻合良好,从而验证了入射及反弹射线法/镜像法的正确性;自由空间邻近（Close-In,CI）参考距离路径损耗模型表达式更简洁,鲁棒性更强.最后,本文给出了一种普遍适用的用来表征室内视距（Line-of-Sight,LOS）与非视距（Non-Line-of-Sight,NLOS）环境28 GHz与60 GHz毫米波信道的路径损耗模型.     

随机桥过程分析街道拐角的无线传播特性

使用随机桥过程研究街道拐角的小尺度衰落和大尺度传播的特性.首先介绍模型,随机桥过程的理论基础,从随机桥过程引入随机射线的概念,利用随机射线建立无线信道分析街道拐角的多径传播特性和大尺度传播特性.然后给出信道的时延分布、多径分量的幅度特性、功率延迟分布,接收机接收波的到达角分布等多径特性参数,并给出路径损耗.仿真结果与参考文献中无线信道测量结果吻合较好,表明使用随机桥过程可以有效地分析街道拐角的无线传播特性.     

一种新的无线电波传播路径损耗模型

使用渗流网格建模无线电波的随机传播环境,在此基础上使用随机射线方法,从概率论的角度得到若干路径损耗的解析公式.经过与经典路径损耗模型以及其他由非波动方法得到的路径损耗模型的比较之后,从逻辑上推断出一个新的路径损耗模型.对新模型中参数的取值范围进行了讨论和分析,最后使用城市密集传播地区的测量数据验证新的路径损耗模型的精确性.     

一种基于几何统计的卫星移动MIMO信道模型

结合统计模型复杂度低和几何模型精确度高的优点,提出了一种基于几何统计的双极化卫星移动多输入多输出(MIMO)系统的信道建模理论。该模型总体上使用几何模型的建模思路,采用射线追踪方法对信道中传输的射线进行追踪,重点关注各条射线的各种小尺度参数,在实际计算中引入统计学方法对各种小尺度参数进行建模与处理,同时考虑信道环境造成的信号衰减以及信道环境对射线极化的影响,完成了信道模型的建立。根据已完成的建模理论,利用Matlab实现极化卫星移动MIMO信道的建模与仿真。通过与增强型统计模型仿真结果进行比较,得出了此几何统计模型是正确的,并可在一定程度上提高建模准确性的结论。     

基于VIIRS传感器的场地反射率测量精度的验证

反射率基法是目前最常用、最有效的可见光近红外通道在轨辐射定标方法。在该方法中,准确的场地反射率测量是得到高精度定标结果的重要前提之一。利用双光谱仪法进行了野外地物反射率时间序列测量,避免了用传统测量方法可能出现的辐射条件不一致问题。用中心区和高反区场地反射率测量值对VIIRS传感器的表观反射率进行了模拟,并将VIIRS可见光近红外9个通道(I1、I2、M1～M7)的卫星观测表观反射率值与6S辐射传输模型模拟值进行了对比。除M6通道外(水汽吸收),相对偏差均在3%以内,验证了场地反射率测量的准确性。     

Electric-field sensor based on a double quantum dot in a microcavity

A scheme for an optical quantum external-electric-field sensor based on a double quantum dot placed in a high-Q semiconductor microcavity is proposed. A model of the dynamic processes occurring in this system is developed, its spectral characteristics are investigated, and the noise stability of the sensor is examined. It is demonstrated that, owing to design features, the device has a number of advantages, including high sensitivity, the presence of different excitation and measurement channels, and the possibility of accurate determination of the spatial field distribution.     

Capacity of distributed PHY-layer sensor networks

Sensor networks are comprised of nodes with minimal baseband and RF functionalities. In such networks, it is assumed that a source sensor communicates with a target sensor over a number of relaying sensors by utilizing distributed low-complexity space-time encoding techniques, hence the resulting communication scenario is a generalized form of orthogonalized multiple-input multiple-output (MIMO) channels. The contributions of this paper are the derivation of the Shannon capacity in terms of natural units per second per Hertz for such space-time encoded distributed communication scenarios. Closed-form capacity expressions are derived for ergodic flat-fading Rayleigh and Nakagami channels, as well as the communication-rate outage probabilities for aforementioned channels. It is shown that the distributed Alamouti scheme yields the best performance over ergodic channels. In the case of nonergodic channels, the 3/4-rate sporadic space-time block code (STBC) is shown to give optimum performance. Finally, Monte Carlo simulations are used to assess the performance of distributed multistage sensor networks. It is shown that notable power savings can be achieved, compared to the traditional single-link sensor networks.     

Adaptive quantized target tracking in wireless sensor networks

This paper addresses target tracking in wireless sensor networks (WSN) where the observed system is assumed to evolve according to a probabilistic state space model. We propose to improve the use of the variational filtering (VF) by optimally quantizing the data collected by the sensors. Recently, VF has been proved to be suitable to the communication constraints of WSN. Its efficiency relies on the fact that the online update of the filtering distribution and its compression are executed simultaneously. However, this problem has been used only for binary sensor networks neglecting the transmission energy consumption in a WSN and the information relevance of sensor measurements. Our proposed method is intended to jointly estimate the target position and optimize the quantization level under fixed and variable transmitting power. At each sampling instant, the adaptive method provides not only the estimate of the target position by using the VF but gives also the optimal number of quantization bits per observation. The adaptive quantization is achieved by minimizing the predicted Cramér–Rao bound if the transmitting power is constant for all sensors, and optimizing the power scheduling under distortion constraint if this power is variable. The computation of the predicted Cramér–Rao bound is based on the target position predictive distribution provided by the VF algorithm. The proposed adaptive quantization scheme suggests that the sensors with bad channels or poor observation qualities should decrease their quantization resolutions or simply become inactive in order to save energy.     

Tree‐based channel assignment schemes for multi‐channel wireless sensor networks

Many sensor node platforms used for establishing wireless sensor networks (WSNs) can support multiple radio channels for wireless communication. Therefore, rather than using a single radio channel for whole network, multiple channels can be utilized in a sensor network simultaneously to decrease overall network interference, which may help increase the aggregate network throughput and decrease packet collisions and delays. This method, however, requires appropriate schemes to be used for assigning channels to nodes for multi‐channel communication in the network. Because data generated by sensor nodes are usually delivered to the sink node using routing trees, a tree‐based channel assignment scheme is a natural approach for assigning channels in a WSN. We present two fast tree‐based channel assignment schemes (called bottom up channel assignment and neighbor count‐based channel assignment) for multi‐channel WSNs. We also propose a new interference metric that is used by our algorithms in making decisions. We validated and evaluated our proposed schemes via extensive simulation experiments. Our simulation results show that our algorithms can decrease interference in a network, thereby increasing performance, and that our algorithms are good alternatives for static channel assignment in WSNs. Copyright © 2015 John Wiley & Sons, Ltd.     

微波谐振腔湿度测量同轴环耦合设计与实现

基于微波谐振腔汽轮机内流动湿蒸汽湿度的测量原理,分析了微波谐振腔及同轴线小环耦合的场结构分布,设计出两端带栅网结构的湿度传感器.采用HFSS型微波软件对湿度传感器进行了建模仿真,由此得到场分布及S参数曲线图,以此设计出湿度传感器的结构尺寸.仿真结果表明,该微波谐振腔传感器工作在TE011模式下,谐振频率为9.58 GHz,其Q=1 198,适合作为测试流动湿蒸气的传感器.与采用矩形波导和谐振腔的孔耦合相比,这种新型同轴线耦合装置体积小,对汽轮机设备的开口也小,实用性也强.     

Collaborative beamforming for wireless sensor networks with Gaussian distributed sensor nodes

Collaborative beamforming has been recently introduced in the context of wireless sensor networks (WSNs) to increase the transmission range of individual sensor nodes. The challenge in using collaborative beamforming in WSNs is the uncertainty regarding the sensor node locations. However, the actual sensor node spatial distribution can be modeled by a properly selected probability density function (pdf). In this paper, we model the spatial distribution of sensor nodes in a cluster of WSN using Gaussian pdf. Gaussian pdf is more suitable in many WSN applications than, for example, uniform pdf which is commonly used for flat ad hoc networks. The average beampattern and its characteristics, the distribution of the beampattern level in the sidelobe region, and the distribution of the maximum sidelobe peak are derived using the theory of random arrays. We show that both the uniform and Gaussian sensor node deployments behave qualitatively in a similar way with respect to the beamwidths and sidelobe levels, while the Gaussian deployment gives wider mainlobe and has lower chance of large sidelobes.     

阵列式振动传感器环境干扰消除方法研究

为了克服复杂环境下单振动传感器误报率高的问题,采用了传感器阵列的定位(定区域)技术消除环境干扰的方法。首先首次提出了传感器阵列的最佳分布模型和传感器阵列消除环境干扰的算法模型,然后给出了目标定位(定区域)的具体算法,最后将传感器阵列定位(定区域)方法与单传感器方法进行实验对比。实验结果表明:本方法消除环境干扰效果好,目标定位(定区域)的精度高、检测率高。     

8/4-4分载式并联六维力传感器建模与分析

为增大传感器量程,适应大负载要求,基于8/4-4并联压电六维力传感器,提出了一种8/4-4分载式并联结构的六维力传感器。基于大力分载原理,在8/4-4并联压电六维力传感器的基础上,各个支链采用压电陶瓷作为敏感元件,增加中心承载梁,使其分载传感器的大部分外负载广义六维力。建立8/4-4分载式并联六维力传感器的数学模型,并推导其解耦算法。通过ADAMS算例仿真与理论模型进行对比,六维力传感器的数学模型及解耦算法的误差不超过0.14%,验证了其准确性。     

Color reproduction from noisy CFA data of single sensor digital cameras.

Single sensor digital color still/video cameras capture images using a color filter array (CFA) and require color interpolation (demosaicking) to reconstruct full color images. The color reproduction has to combat sensor noises which are channel dependent. If untreated in demosaicking, sensor noises can cause color artifacts that are hard to remove later by a separate denoising process, because the demosaicking process complicates the noise characteristics by blending noises of different color channels. This paper presents a joint demosaicking-denoising approach to overcome this difficulty. The color image is restored from noisy mosaic data in two steps. First, the difference signals of color channels are estimated by linear minimum mean square-error estimation. This process exploits both spectral and spatial correlations to simultaneously suppress sensor noise and interpolation error. With the estimated difference signals, the full resolution green channel is recovered. The second step involves in a wavelet-based denoising process to remove the CFA channel-dependent noises from the reconstructed green channel. The red and blue channels are subsequently recovered. Simulated and real CFA mosaic data are used to evaluate the performance of the proposed joint demosaicking-denoising scheme and compare it with many recently developed sophisticated demosaicking and denoising schemes.