Outage Probability Analysis for D2D-Enabled Heterogeneous Cellular Networks with Exclusion Zone:A Stochastic Geometry Approach

Interference management is one of the most important issues in the device-to-device(D2D)-enabled heterogeneous cellular networks(HetCNets)due to the coexistence of massive cellular and D2D devices in which D2D devices reuse the cellular spectrum.To alleviate the interference,an efficient interference management way is to set exclusion zones around the cellular receivers.In this paper,we adopt a stochastic geometry approach to analyze the outage probabilities of cellular and D2D users in the D2D-enabled HetCNets.The main difficulties contain three aspects:1)how to model the location randomness of base stations,cellular and D2D users in practical networks;2)how to capture the randomness and interrelation of cellular and D2D transmissions due to the existence of random exclusion zones;3)how to characterize the different types of interference and their impacts on the outage probabilities of cellular and D2D users.We then run extensive Monte-Carlo simulations which manifest that our theoretical model is very accurate.

Analysis on D2D Heterogeneous Networks with State-Dependent Priority Traffic

In this work,we consider the performance analysis of state dependent priority traffic and scheduling in device to device(D2D)heterogeneous networks.There are two priority transmission types of data in wireless communication,such as video or telephone,which always meet the requirements of high priority(HP)data transmission first.If there is a large amount of low priority(LP)data,there will be a large amount of LP data that cannot be sent.This situation will cause excessive delay of LP data and packet dropping probability.In order to solve this problem,the data transmission process of high priority queue and low priority queue is studied.Considering the priority jump strategy to the priority queuing model,the queuing process with two priority data is modeled as a two-dimensionalMarkov chain.A state dependent priority jump queuing strategy is proposed,which can improve the discarding performance of low priority data.The quasi birth and death process method(QBD)and fixed point iterationmethod are used to solve the causality,and the steady-state probability distribution is further obtained.Then,performance parameters such as average queue length,average throughput,average delay and packet dropping probability for both high and low priority data can be expressed.The simulation results verify the correctness of the theoretical derivation.Meanwhile,the proposed priority jump queuing strategy can significantly improve the drop performance of low-priority data.

Synthesis and 2D H-bonded Cd(Ⅱ) Network Structure of [Cd(C_(10)H_(15)N_3)Cl_2]

The title complex [CdLCl2] 1 (C10H15CdCl2N3, Mr = 360.55) has been synthesized by the reaction of CdCl22.5H2O with the tridentate Schiff base L, N,N-dimethyl-N-pyridin-2-yl- methylene-1,2-diaminoethane, which is derived from the condensation reaction of pyridine-2- carboxaldehyde and N,N-dimethylethylenediamine. It crystallizes in the monoclinic system, space group C2/c with a = 25.054(13), b = 7.532(4), c = 16.119(8) ? b = 116.238(8)? V = 2728(2) ?, Z = 8, Dc = 1.756 g/cm3, m(MoKa) = 1.970 mm-1, F(000) = 1424, R = 0.0297 and wR = 0.0625. Crystal analyses reveal that the cadmium atom is coordinated by two chlorine atoms and three N atoms from the tridentate ligand in a distorted tetragonal pyramidal environment. Each complex molecule is connected with four surrounding ones to form 2D network by hydrogen bonds along the bc plane. The chlorine atoms act as acceptors and the carbon atoms of the tridentate Schiff base as donors with the CH…Cl distances in the range of 3.518～3.752 ?

A Caching Strategy Based on Many-to-Many Matching Game in D2D Networks

Wireless edge caching has been proposed to reduce data traffic congestion in backhaul links, and it is being envisioned as one of the key components of next-generation wireless networks. This paper focuses on the influences of different caching strategies in Device-to-Device(D2D) networks. We model the D2D User Equipments(DUEs) as the Gauss determinantal point process considering the repulsion between DUEs, as well as the caching replacement process as a many-to-many matching game. By analyzing existing caching placement strategies, a new caching strategy is proposed, which represents the preference list of DUEs as the ratio of content popularity to cached probability. There are two distinct features in the proposed caching strategy.(1) It can cache other contents besides high popularity contents.(2) It can improve the cache hit ratio and reduce the latency compared with three caching placement strategies: Least Recently Used(LRU), Equal Probability Random Cache(EPRC), and the Most Popular Content Cache(MPC). Meanwhile, we analyze the effect of caching on the system performance in terms of different content popularity factors and cache capacity. Simulation results show that our proposed caching strategy is superior to the three other comparison strategies and can significantly improve the cache hit ratio and reduce the latency.

Deep Learning Based Physical Layer Security of D2D Underlay Cellular Network

In order to improve the physical layer security of the device-to-device(D2D)cellular network,we propose a collaborative scheme for the transmit antenna selection and the optimal D2D pair establishment based on deep learning.Due to the mobility of users,using the current channel state information to select a transmit antenna or establish a D2D pair for the next time slot cannot ensure secure communication.Therefore,in this paper,we utilize the Echo State Network(ESN)to select the transmit antenna and the Long Short-Term Memory(LSTM)to establish the D2D pair.The simulation results show that the LSTMbased and ESN-based collaboration scheme can effectively improve the security capacity of the cellular network with D2D and increase the life of the base station.

Hetero-bimetallic Complex of a 2D Coordination Network Constructed by Sodium Ion and p-Sulfonatothiacalix[4]arene

A 2D coordination polymer built by sodium ion and water-soluble p-sulfonatothiacalix[4]arene of trivalent yttrium complex [Na（H2O）2Y（H2O）6（DMF） （p-sulfonatothiaca lix[4]arene）]-9H2O is reported. The complex belongs to the monoclinic system, space group P2 1/c, with a = 16.703（3）, b = 17.819（4）, c = 17.357（4）A, β = 106.23（3）°, Z = 4, V = 4960.0（17）A^3, Mr = 1304.08, Dc = 1.746 g/cm^3,μ= 1.624 mm^-1, F（000） = 2688, the final R = 0.0398 and wR = 0.1132 for 7534 observed reflections with I 〉 2σ（I）. One yttrium（Ⅲ） ion is coordinated by the thiacalixarene ligand via the sulfonato group, and also ligated by an oxygen atom of a DMF molecule occupying the cavity of thiacalixarene and six aqua ligands.

An Implicit Coupled 1D/2D Model for Unsteady Subcritical Flow in Channel Networks and Embayment

In this study, 1D and 2D shallow-water models were coupled to simulate unsteady flow in channel networks and embayment. The 1D model solved the 1D shallow-water equations (St. Venant) using the Preissmann box method and targeted long narrow reaches of the river networks, while the 2D model targeted broad channels and embayment and solved the 2D shallow-water equations using a semi-implicit scheme applied to an unstructured grid of triangular cells. The 1D and 2D models were solved simultaneously by building a matrix for the free surface elevation at every 1D junction and 2D cell center. Velocities were then computed explicitly based on the results at the previous time step and the updated water level. The originality of the scheme arose from a novel coupling method. The results showed that the coupled 1D/2D model produced identical results as the full 2D model in classical to benchmark problems with considerable savings in computational effort. Application of the model to the Pearl River Estuary in southern China showed that complex patterns of tidal wave propagation could be efficiently modeled.

基于深度学习的二维人体姿态估计综述

人体姿态估计是近年来计算机视觉问题中的一个热门话题,它在改善人类生活方面具有巨大的益处和潜在的应用。近年来深度神经网络得到快速发展,相较于传统方法而言,采用深度学习的方法更能提取图像表征信息。综合分析近年来人体姿态估计的进展,根据检测人数分为单人和多人人体姿态估计。针对单人姿态估计,介绍了基于直接预测人体坐标点的坐标回归方法及基于预测人体关键点高斯分布的热图检测方法;针对多人姿态估计,采用解决多人到解决单人过程的自顶向下方法和直接处理多人关键点的自底向上方法。总结了各方法网络结构的特点和优缺点,并阐述当前面临的问题及未来发展趋势。

2D雷达组网几何定位融合算法

研究了两部2D雷达组网中的目标定位估计和定位精度问题。为考虑地球曲率对目标定位精度的影响,提出了两雷达站组网中基于实际地球椭球模型的几何交叉定位与数据融合相结合的方法,建立了两部雷达观测定位几何模型,推导了定位方程和精度估计公式并进行了误差分析。仿真分析表明,在选择更为实际的观测模型的前提下,利用几何定位与数据融合方法不但改善了两雷达的定位性能,而且根据定位几何精度因子(geometricaldilution of precision,GDOP)图的特点,选择相应的定位雷达,提高了雷达站组合的几何定位精度。

高效的多跳频信号2D-DOA估计算法

为了利用跳频信号的空域特征参数辅助多跳频信号的网台分选,在空时频分析的基础上,提出一种基于多重信号分类(multiple signal classification,MUSIC)对称压缩谱(MUSIC symmetrical compressed spectrum,MSCS)的多跳频信号二维波达方向(two dimensional direction of arrival,2D-DOA)高效估计算法。首先根据跳频信号的时频域特征,构建每一跳的空时频矩阵(spatial time-frequency distribution,STFD),获取时频域的协方差矩阵;然后将共轭子空间的思想引入到MUSIC算法中,通过对噪声子空间及其共轭的交集进行奇异值分解,实现噪声子空间的降维;最终通过半谱搜索实现2D-DOA的高效估计。同时为了提高低信噪比条件下算法的性能,在时频图处理过程中采用形态学滤波进行去噪,并在修正的时频图上完成了跳频信号每一跳的提取。通过理论论证和实验仿真表明,本文算法相比于MUSIC算法,在保证均方根误差相当和估计成功率有所提高的情况下,计算复杂度降低了一半。

基于概率模型的E-2D Mesh网络容错性分析

研究了太比特路由器核心交换网络拓扑的一种新结构-E-2D Mesh.提出一种计算E-2D Mesh网络连通率的新方法.证明了当网络结点失效率控制在0.66%以下时,具有四万多个结点的E-2D Mesh网络可保持不低于99%的连通率,且在同等规模条件下,E-2D Mesh网络结点容错率至少是Mesh网络的11.09倍.研究结果表明,该方法在计算E-2D Mesh网络连通率时显示出较强的生命力且能够用于研究其它层次的网络和其它网络通信问题.

2D排水模型在排水工程中的应用探讨

利用水力模型软件Info Works ICM建立广州市FY路2D排水模型,分析评估现状管道水力运行状况,找出内涝的原因,制定有针对性的解决方案,并利用水力模型对设计方案进行校核,保证方案的合理性和可行性。现通过实例介绍2D排水模型在城市排水工程中的应用方法和具体流程,可为其他地区模型应用提供参考。

基于深度学习的2D/3D医学图像配准研究

2D/3D配准在临床诊断和手术导航规划中有着广泛的应用,可解决医学图像领域中不同维度图像存在信息缺失的问题,能辅助医生在术中精准定位患者的病灶。常规的2D/3D配准方法主要依赖于图像的灰度进行配准,但非常耗时,不利于临床实时性的需求,并且配准过程中容易陷入局部最优值。提出用深度学习的方法来解决2D/3D医学图像配准问题。采用一个基于深度学习的卷积神经网络,通过网络对数字影像重建技术(DRR)进行训练并自动学习图像特征,预测X光图像所对应的参数,从而实现配准。以人体骨盆的模型骨为实验对象,根据骨盆的CT数据生成36000张DRR图像作为训练集,同时通过C臂采集模型骨的50张X光图像作为验证。结果显示,深度学习算法在相关系数、归一化互信息、欧式距离3个精度评价指标上的测试值分别为0.82±0.07、0.32±0.03、61.56±10.91,而常规2D/3D算法对应的测试值分别为0.79±0.07、0.29±0.03、37.92±7.24,说明深度学习算法的配准精度优于常规2D/3D算法的配准精度,且不存在陷入局部最优值的问题。同时,深度学习的配准时间约为0.03 s,远低于常规2D/3D配准的时间,可满足临床对于实时配准的需求,未来将进一步开展临床数据的2D/3D配准研究。

2D雷达组网空中目标高度估计方法综述

概述了2D雷达组网如何利用多部2D雷达探测的距离和方位数据估计空中目标高度的基本思想,阐述并分析了运用几何计算法、最小二乘法、极大似然法及状态滤波法及其改进方法对空中目标高度进行估计的适用范围及其优缺点。仿真试验表明,雷达探测精度、雷达站址空间布局及空中目标高度等因素均对目标高度估计精度影响较大。最后,给出了未来2D雷达组网空中目标高度估计研究方向。

具有2D氢键网络结构的锰化合物[Mn(BBP-H)_2]的水热合成(英文)

利用水热合成方法,得到了一个新型的锰配合物[Mn(BBP-H)2](BBP为2,6-双(2-苯并咪唑甲基)吡啶),并通过X-射线衍射得到其晶体结构,空间群为P-4n2,晶胞参数a=1.01470(17)nm,b=1.01470(17)nm,c=1.5885(5)nm,V=1.6355(7)nm3,Z=2.每个锰离子与两个带电荷的三齿配体BBP配位,形成畸变的八面体构型,相邻的分子之间通过氢键形成2D平面结构.

基于测向平面的2D雷达目标高度估计方法

针对2D雷达组网中的高度估计问题,提出了一种基于测向平面的2D雷达目标高度估计方法。该方法通过2D雷达对目标的测向方位在空间中形成测向平面,并利用2个相交的测向平面及雷达对目标的测量距离,估计出目标的地心地固(ECEF)坐标。再利用ECEF坐标到大地坐标的转换得到目标的高度估计,最后进行了蒙特卡罗仿真试验。结果表明,该方法简单有效,具有工程应用价值。

基于多模块关系网络的2D足迹分类

由于足迹数据的样本量有限,类间差小、类内距大,一般方法难以获取有效的足迹特征表示,导致足迹分类准确度不高。针对双模态2D足迹分类问题,文中提出一种基于小样本学习的多模块网络算法(MulRN),该算法在嵌入单元与关系单元使用了多个模块来提高网络的特征提取能力与特征度量能力,使用具有多分支结构的Inception模块与MRFB模块提升网络的特征提取能力,采用空间注意力模块与通道注意力模块提取出区分度更高的足迹特征,从而更好地实现足迹分类;并在miniImageNet、Omniglot等小样本数据集与双模态2D足迹数据集上进行了实验。实验结果表明,该方法在小样本数据集上具有较好的表现,同时在双模态2D足迹数据集上也达到了不错的效果,特别在右脚双模态数据集上的5-way 5-shot实验中达到了95.41%的分类准确率。

基于FPGA的2D-Torus片上网络无死锁路由算法

片上网络的拓扑结构和路由算法直接影响片上网络的传输延迟和传输效率.基于2D-Torus拓扑结构,提出了一种新的片上网络无死锁路由算法.通过改变数据包在片上网络路由过程中受限制转弯的位置,保证片上网络的自适应路由条件,从而有效降低片上网络的延迟.在FPGA硬件平台上,设计并实现了基于该路由算法的2D-Torus片上网络,并对其进行测试.实验结果表明,基于该路由算法的片上网络,可以满足片上网络多方向数据通信及多路数据并行通信等性能要求.

2D Mesh片上网络中交换机服务性能影响的研究及其拓扑改进

本文研究了交换机服务性能对2D Mesh片上网络的缓冲区资源和端到端延时的影响,发现在较低的丢包率的情况下,即使交换机能够提供很高的服务性能,却难以节省其所使用的缓冲区资源的现象.针对该现象,提出了一种基于星型子网的网状拓扑结构SSBM(Star-Subnet-Based-Mesh),在同样的网络规模以及丢包率的情况下,该种结构与2D Mesh结构相比具有更少的端到端通信延时,并且能够以较少的交换机服务性能为代价来节省较多的缓冲区资源,在较大程度上优化了2D Mesh片上网络的面积.

具有失效结点2D-Torus网络可靠性研究

结合2D-Torus网络的特点,以3×3Torus为例采用markov过程建立结点失效独立和结点失效相关条件下的网络可靠性模型.通过建立markov状态空间图并进行求解得出可靠性模型的数学表达式,计算出网络的可靠度.通过对模型的仿真表明:网络规模越大,可靠性越低;结点失效相关时的网络可靠性要比结点失效独立时的网络可靠性低.