基于深度学习的调制识别方法研究

如今,深度学习技术的飞速发展为调制识别提供了新的解决方案。深度网络凭借出色的特征提取能力,可以学习到非结构化数据中的隐藏模式,进而有效完成调制类型的识别任务。本研究设计并实现了残差网络（Residual Network,Res Net）与卷积长短时记忆网络（Convolutional,LongShort-Term Memory, Fully Connected Deep Neural Networks,CLDNN）两种模型,验证了深度学习应用在调制方式识别领域的有效性。通过使用软件无线电设备模拟采集数据,进一步验证了两个模型的泛化性。     

DCGAN信道下的端到端通信系统设计

针对通信系统中长序列建模存在维度诅咒的问题,提出了一种基于深度卷积生成对抗网络(Deep Convolutional Generative Adversarial Networks, DCGAN)信道建模的端到端通信系统改进方案。该方案将卷积神经网络(Convolutional Neural Network, CNN)和条件生成对抗网络(Conditional Generative Adversarial Network, CGAN)结合,利用CNN与全连接层(Fully Connected Layer, FC)的局部连接特性对传输长序列的信道进行建模。通过对参数重新设计及网络结构调整,获得了适应不同调制方式和信道类型的学习网络,将其应用端到端通信系统中,作为收发机之间梯度反向传播的桥梁。仿真实验表明,改进的DCGAN能够以减小的网络规模以及计算量成功地实现长序列建模,并且表现出良好的泛化能力。此外,将建模结果运用到端到端通信系统设计中,可以获得与传统数字调制系统相近的误比特率性能。     

高速移动环境下基于深度学习的信道估计方法

针对高速移动环境下信道快时变、非平稳特性导致下行链路信道估计性能受限的问题,本文提出一种基于深度学习的信道估计网络,即ChanEstNet.ChanEstNet使用卷积神经网络（Convolutional Neural Network,CNN）提取信道响应特征矢量和循环神经网络（Recurrent Neural Network,RNN）进行信道估计.我们利用标准的高速信道数据对学习网络进行离线训练,充分挖掘训练样本中的信道信息,使其学习到高速移动环境下信道快时变和非平稳的特点,更好的跟踪高速环境下信道的变化特征.仿真结果表明,在高速移动环境下,与传统方法相比,所提信道估计方法计算复杂度低,性能提升明显.     

一种面向LTE-V2X的联邦学习信道估计算法

基于深度学习的信道估计方法中,训练网络模型需要大量的数据运算,且所有用户数据都需要集中上传至服务器上,存在隐私泄漏的隐患.针对上述问题,提出了一种基于联邦学习的LTE-V2X(Long Term Evolution-Vehicle to Everything)信道估计算法,采用CNN-LSTM-DNN(Convolutional Neural Network-Long Short Term Memory-Deep Neural Network)模型对时变的信道进行估计,并将学习网络模型所需要的计算分配到车载用户中,在降低道旁基站负载的同时也保护了车载用户数据的隐私.仿真结果表明,基于联邦学习的信道估计算法在车载用户高速移动的场景下,较传统的信道估计算法平均有10 dB以上的归一化均方误差(Normalized Mean Square Error,NMSE)增益以及3 dB以上的误码率(Bit Error Rate,BER)增益,且较集中式学习算法相比,NMSE性能差距在3 dB以内;BER性能差距在1 dB以内,所提算法能够有效追踪时变的信道,且与集中式学习算法相比仅损失了极少的性能.     

基于CNN的毫米波无蜂窝大规模MIMO信道估计

针对小区间干扰导致蜂窝边缘无法满足不断增长的数据速率需求问题,毫米波无蜂窝大规模多输入多输出(Multiple-Input Multiple-Output, MIMO)系统被认为是一种很有前途的解决方案。然而,毫米波的高频率、大带宽以及接入点配置的大量天线给信道估计带来了较大挑战。将毫米波大规模MIMO信道矩阵视为二维图像,结合图像去噪方法提出一种基于改进去噪卷积神经网络(Improved-Denoising Convolutional Neural Network, I-DnCNN)的信道估计算法。通过具有注意力机制的压缩与激励(Squeeze-and-Excitation, SE)模块,自适应调整提取的全局特征以增强对信道噪声特征的学习,根据接收信号估计出噪声等级图且增添为输入,提升对噪声的鲁棒性。最后,采用残差学习的方式获得估计信道矩阵。利用理论信道模型和基于波束追踪的信道数据集进行的仿真实验结果表明,与去噪卷积神经网络(Denoising Convolutional Neural Network, DnCNN)算法相比,所提算法在两个数据集下的信道估计精度可分别平均提升2.27...     

LTE-Advanced中eNodeB解调性能研究

提出基站解调性能要求的目标是估计实际网络如何运行,验证基站不同的损害因素,这些损害因素会对网络性能产生影响。这些影响因素包括RF和基带损害因素、接收机EVM(误差矢量幅度)时域和频域跟踪、频率估计等。对物理上行链路共享信道(PUSCH)、物理上行链路控制信道(PUCCH)和物理随机接入信道(PRACH)的基站解调性能要求进行了描述,给出了各类信道的基站测试集。     

基于深度学习的高维信号信道估计算法

针对大部分基于深度学习（Deep Learning,DL）的信道估计算法估计高维信号时出现的训练开销过大、泛化能力差等问题,提出了一种不需要训练的基于深度学习的高维信号信道估计算法,即UTCENet（Untrained Channel Estimation Network）。在UTCENet中,信道信息上的复杂分布转换为模型参数上的简单分布,即通过神经网络参数化来获得隐式先验知识并将其应用于信道估计。虽然该算法不需要任何训练,但保证了估计的性能,其原因在于专门设计的网络模型可以有效利用时频网格中元素的相关性。仿真结果表明,与传统方法以及现有的深度学习方法相比,所提出的算法在归一化均方误差和误码率方面性能提升明显。     

应用深度学习的信号解调

针对噪声干扰信道下的信号解调问题,提出了应用深度学习的信号识别方法,通过识别信号完成信号解调.深层置信网络使用受限波尔兹曼机为基本单元,设计针对通信信号识别的多层深层置信网络.通信信号首先变换为特定表征序列,并以此构建完备的训练集合对深度置信网络进行逐层的无监督学习和全局有监督的微调反馈学习,在深层置信网络的权重参数优化过程中实现对通信信号的特征提取与识别.仿真实验表明,与传统调制信号解调方法相比,应用深度学习的信号解调方法的检测性能有约0.4 dB的提升.     

基于深度神经网络的短波特定信号识别研究

在时变色散信道和低信噪比下,基于时频图利用深度神经网络的短波信号识别的方法对并行多音信号的识别能够取得一定效果,但常用的相位调制的串行单音短波信号识别难以取得较好效果。由于短波信号帧结构中都含有同步帧和发射电平起控帧等特征数据,提出了一种基于同步帧注意力机制的卷积神经网络结构。测试结果表明,使用卷积神经网络（Convolutional Neural Networks,CNN）、双向长短时记忆（Bi-directional Long Short Term Memory,Bi-LSTM）和注意力机制搭建成的深度神经融合网络模型对短波基带信号直接进行检测识别能够取得较好效果。     

基于深度学习的ACO-OFDM自由空间光通信中信号检测

针对自由空间光通信(free-space optical communication, FSO)系统中大气湍流引起的光强起伏闪烁效应对正交幅度调制(quadrature amplitude modulation, QAM)信号影响很大,缺少实时信道信息时的最大似然(maximum likelihood, ML)检测器性能较差问题,本文提出了一种基于深度学习(deep learning, DL)的信号检测器。其网络框架采用了一个具有全连接层的深度学习神经网络(deep-learning neural network, DNN),实现了无导频的ACO-OFDM空间通信系统中信道盲估计、信道均衡和信号解调。仿真结果表明：在中强湍流大气信道下训练的DNN检测器,8QAM、16QAM和64QAM等调制信号解调的误码率分别可以下降到在2×10^-5、5×10^-5和5×10^-4左右,具有优越性能和鲁棒性,能较好抑制大气湍流引起的信道衰落。     

Resolution Enhancement Technology:Integrated Process Solutions using OPC

DUV lithography, using the 248 nm wavelength, is a viable manufacturing option for devices with features at 130 nm and less. Given the low kl value of the lithography, integrated process development is a necessary method for achieving acceptable process latitude. The application of assist features for rule based OPC requires the simultaneous optimization of the mask, illumination optics and the resist.Described in this paper are the details involved in optimizing each of these aspects for line and space imaging.A reference pitch is first chosen to determine how the optics will be set. The ideal sigma setting is determined by a simple geometrically derived expression. The inner and outer machine settings are determined, in turn,with the simulation of a figure of merit. The maximum value of the response surface of this FOM occurs at the optimal sigma settings. Experimental confirmation of this is shown in the paper.Assist features are used to modify the aerial image of the more isolated images on the mask. The effect that the diffraction of the scattering bars (SBs) has on the image intensity distribution is explained. Rules for determining the size and placement of SBs are also given.Resist is optimized for use with off-axis illumination and assist features. A general explanation of the material' s effect is discussed along with the affect on the through-pitch bias. The paper culminates with the showing of the lithographic results from the fully optimized system.     

Cost-effective test solutions for smart card and other integrated flash applications

From its emergence in the late 1980s as a lower cost alternative to early EEPROM technologies, flash memory has evolved to higher densities and speedsand rapidly growing acceptance in mobile applications.In the process, flash memory devices have placed increased test requirements on manufacturers. Today, as flash device test grows in importance in China, manufacturers face growing pressure for reduced cost-oftest, increased throughput and greater return on investment for test equipment. At the same time, the move to integrated flash packages for contactless smart card applications adds a significant further challenge to manufacturers seeking rapid, low-cost test.     

Theoretical analysis of the relationship between the Brillouin gain coefficient and the strain in the optical-fiber sensors

The relation between the power of the Brillouin signal and the strain is one of the bases of the distributed fiber sensors of temperature and strain. The coefficient of the Bfillouin gain can be changed by the temperature and the strain that will affect the power of the Brillouin scattering. The relation between the change of the Brillouin gain coefficient and the strain is thought to be linear by many researchers. However, it is not always linear based on the theoretical analysis and numerical simulation. Therefore, errors will be caused if the relation between the change of the Brillouin gain coefficient and the strain is regarded as to be linear approximately for measuring the temperature and the strain. For this reason, the influence of the parameters on the Brillouin gain coefficient is proposed through theoretical analysis and numerical simulation.     

An improved parallel thinning algorithm with two subiterations

The parallel thinning algorithm with two subiterations is improved in this paper. By analyzing the notions of connected components and passes, a conclusion is drawn that the number of passes and the number of eight-connected components are equal. Then the expression of the number of eight-connected components is obtained which replaces the old one in the algorithm. And a reserving condition is proposed by experiments, which alleviates the excess deletion where a diagonal line and a beeline intersect. The experimental results demonstrate that the thinned curve is almost located in the middle of the original curve connectivelv with single pixel width and the processing speed is high.     

Novel fiber-optical interferometer with miniaturized probe for in-hole measurements

Today, micro-system technology and the development of new MEMS （Micro-Electro-Mechanical Systems） are emerging rapidly. In order for this development to become a success in the long run, measurement systems have to ensure product quality. Most often, MEMS have to be tested by means of functionality or destructive tests. One reason for this is that there are no suitable systems or sensing probes available which can be used for the measurement of quasi inaccessible features like small holes or cavities. We present a measurement system that could be used for these kinds of measurements. The system combines a fiber optical, miniaturized sensing probe with low-coherence interferometry, so that absolute distance measurements with nanometer accuracy are possible.     

Study of waveguide coupling efficiency in hybrid silicon lasers

This paper presents a new method to increase the waveguide coupling efficiency in hybrid silicon lasers. We find that the propagation constant of the InGaAsP emitting layer can be equal to that of the Si resonant layer through improving the design size of the InP waveguide. The coupling power achieves 42% of the total power in the hybrid lasers when the thickness of the bonding layer is 100 nm. Our result is very close to 50% of the total power reported by Intel when the thickness of the thin bonding layer is less than 5 nm. Therefore, our invariable coupling power technique is simpler than Intel＇s.     

Teleportation of an arbitrary unknown N-qubit entangled state under the controlling of M controllers

A new quantum protocol to teleport an arbitrary unknown N-qubit entangled state from a sender to a fixed receiver under M controllers(M < N) is proposed. The quantum resources required are M non-maximally entangled Greenberger-Home-Zeilinger (GHZ) state and N-M non-maximally entangled Einstein-Podolsky-Rosen (EPR) pairs. The sender performs N generalized Bell-state measurements on the 2N particles. Controllers take M single-particle measurement along x-axis, and the receiver needs to introduce one auxiliary two-level particle to extract quantum information probabilistically with the fidelity unit if controllers cooperate with it.     

A rigorous proof of MIMO channel capacity’s increase with antenna number

It is well known that adding more antennas at the transmitter or at the receiver may offer larger channel capacity in the multiple-input multiple-output（MIMO） communication systems. In this letter, a simple proof is presented for the fact that the channel capacity increases with an increase in the number of receiving antennas. The proof is based on the famous capacity formula of Foschini and Gans with matrix theory.     

Diode-end-pumped Nd:YVO4/LBO lasers with 4.2W continuous-wave output at 457 nm

A continuous-wave (CW) 457 nm blue laser operating at the power of 4.2 W is demonstrated by using a fiber coupled laser diode module pumped Nd: YVO4 and using LBO as the intra-cavity SHG crystal With the optimization of laser cavity and crystal parameters, the laser operates at a very high efficiency. When the pumping power is about 31 W, the output at 457nm reaches 4.2 W, and the optical to optical conversion efficiency is about 13.5% accordingly. The stability of the out putpower is better than 1.2% for 8 h continuously working.     

Call for Papers

正Wireless Body-area Networks The last decade has witnessed the convergence of three giant worlds:electronics,computer science and telecommunications.The next decade should follow this convergence in most of our activities with the generalization of sensor networks.In particular with the progress in medicine,people live longer and the aging of population will push the development of wireless personal networks