Cooperative Relay Selection Mechanism in Multi-Hop Networks

In this paper, we consider a three-hop relay system based on interference cancellation technique in Underlay cognitive radio (CR) network. Although underlay CR has been shown as a promising technique to better utilize the source of primary users (PUs), its secondary performance will be severely degraded. On one hand, by adapting the Underlay spectrum sharing pattern, secondary users (SUs) would observe the strict power constraints and be interfered by primary users. On the other hand, limited transmit power results in limited transmission range, which greatly degrade the secondary transmission capacity. To solve the problems above, we propose an interference cancellation protocol for multi-hop wireless communication networks in underlay CR, which could develop the long-distance transmission performance and improve the transmission efficiency significantly. As simulation results shows, proposed scheme significantly reduce the secondary outage probability and increase the secondary diversity than the traditional cases.     

Performance Analysis of Relay Based NOMA Cooperative Transmission under Cognitive Radio Network

This paper proposes a hybrid spectrum accessing mechanism by using NOMA-based cooperative transmission and beam-forming technology. In this mechanism, the secondary user employs spectrum-sensing technology to detect the existence of the primary user. If the primary user does not exist, the secondary source user directly transmits data to the destination user. If the primary user exists, the secondary source user finds the optimal relay according to certain selection principle before transmitting data to the destination user through the chosen relay node. For the signal receiving stage, the secondary user takes use of beam-forming technology to receive the signal from both the secondary source and the secondary relay node. Meanwhile the interference from the primary user is cancelled out in the stage. Furthermore, the outage probability for secondary user in the proposed mechanism is theoretically derived. Finally, the simulation results show that compared with the traditional mechanism, the proposed system model can not only guarantee the continuity of secondary transmission, but also significantly reduce the outage probability of secondary transmission.     

Secrecy Outage Probability Analysis Based on Cognitive Decodeand-Forward Relaying

Wireless communications have to face to several different security issues in practice due to the nature of broadcast. The information theory is well known to provide efficient approaches to address security issues in wireless communications, which attracts much attention in both industry and academia in recent years. In this paper, inspired by information theory, we study the outage probability of the opportunistic relay selection based on cognitive decode-and-forward relaying with the secrecy consideration. Specifically, the closed-form expression of the outage probability is proposed. Moreover, the asymptotic performance evaluation on the basis of the analytical results is investigated. The simulation results show that the relay selection can reduce the outage probability in accordance with our theoretical analysis.     

Outage Capacity Analysis for Cognitive Non-Orthogonal Multiple Access Downlink Transmissions Systems in the Presence of Channel Estimation Error

In this paper, we propose a downlink cognitive non-orthogonal multiple access (NOMA) network, where the secondary users (SUs) operate in underlay mode. In the network, secondary transmitter employs NOMA signaling for downlink transmission, and the primary user (PU) is interfered by the transmission from SU. The expressions for the outage probabilities are derived in closed-form for both primary and secondary users in the presence of channel estimation error. Numerical simulation results show that the channel estimation error and the inter-network interference cause degradation of the downlink outage performance. Also the power allocation and the location have a significant impact on the outage probability. The numerical experiments demonstrate that the analytic expressions of the outage probabilities match with the simulation results.     

基于CST软件的电火工品射频安全性分析

为了研究电火工品在复杂电磁环境下的射频安全性，针对某型电火工品建立了偶极子天线模型。基于CST电磁仿真软件，仿真得到了该天线模型的增益参数，进一步仿真计算得到了在频率为0．75GHz、电场强度为195V／m的电磁环境下，进入到该电火工品的射频功率，并与实际计算结果进行了对比验证。通过多频点仿真计算，得到了该天线模型的增益随频率变化的规律，即在0．5—2．0GHz的频率范围内，天线模型的增益随着频率的增大而增大。     

Pipeline Scheduling Based on Constructive Interference in Strip Wireless Sensor Networks

Strip Wireless Sensor Networks (SWSNs) have drawn much attention in many applications such as monitoring rivers, highways and coal mines. Packet delivery in SWSN usually requires a large number of multi-hop transmissions which leads to long transmission latency in low-duty-cycle SWSNs. Several pipeline scheduling schemes have been proposed to reduce latency. However, when communication links are unreliable, pipeline scheduling is prone to failure. In this paper, we propose a pipeline scheduling transmission protocol based on constructive interference. The protocol first divides the whole network into multiple partitions and uses a pipelined mechanism to allocate active time slots for each partition. The nodes in the same partition wake up at the same time for concurrent transmission. Multiple identical signals interfere constructively at the receiver node, which enhances received signal strength and improves link quality. Simulations show that the proposed scheme can significantly reduce the transmission latency while maintaining low energy consumption compared with other schemes.     

基于Markov链的供应链产品市场预测分析

供应链的组建类型取决于市场需求的变化趋势,在对Markov链的基本思想进行分析的基础上,利用其平稳性和无后效性的基本特征,构建了基于Markov链的市场随机需求预测模型,提出了模型的相关步骤,并指出构建转移矩阵时应注意的问题.实例证明基于Markov链的产品市场预测模型能有效地预测产品未来市场变化趋势.     

Data Secure Storage Mechanism of Sensor Networks Based on Blockchain

As the number of sensor network application scenarios continues to grow, the security problems inherent in this approach have become obstacles that hinder its wide application. However, it has attracted increasing attention from industry and academia. The blockchain is based on a distributed network and has the characteristics of nontampering and traceability of block data. It is thus naturally able to solve the security problems of the sensor networks. Accordingly, this paper first analyzes the security risks associated with data storage in the sensor networks, then proposes using blockchain technology to ensure that data storage in the sensor networks is secure. In the traditional blockchain, the data layer uses a Merkle hash tree to store data; however, the Merkle hash tree cannot provide non-member proof, which makes it unable to resist the attacks of malicious nodes in networks. To solve this problem, this paper utilizes a cryptographic accumulator rather than a Merkle hash tree to provide both member proof and nonmember proof. Moreover, the number of elements in the existing accumulator is limited and unable to meet the blockchain’s expansion requirements. This paper therefore proposes a new type of unbounded accumulator and provides its definition and security model. Finally, this paper constructs an unbounded accumulator scheme using bilinear pairs and analyzes its performance.     

多目标模糊动态选拔机制的应用研究

当今经理选拔机制在现代公司制度中的重要性越来越突出。在综合分析经理选拔模糊性的基础上，提出了基于多目标模糊优选的经理选拔模型，并通过该模型对具体的多个模糊决策目标的经理选拔问题进行了应用分析。     

A Safe and Reliable Routing Mechanism of LEO Satellite Based on SDN

Satellite networks have high requirements for security and data processing speed. In order to improve the reliability of the network, software-defined network (SDN) technology is introduced and a central controller is set in the network. Due to the characteristics of global perspective, control data separation, and centralized control of SDN, the idea of SDN is introduced to the design of the satellite network model. As a result, satellite nodes are only responsible for data transmission, while the maintenance of the links and the calculation of routes are implemented by the controller. For the massive LEO satellite network based on SDN, a state evaluation decision routing mechanism is proposed. The designed mechanism monitors the status of the entire network effectively and reduces the on-board load on the satellite network. The best routing decision is made under the comprehensive consideration of the current and historical status of each intersatellite link between Low Earth Orbit (LEO) satellite network nodes. The calculation and storage requirements are controlled within a reasonable range. Based on the curve parameter transmission fuzzy encryption algorithm, a safe and reliable condition assessment decision routing mechanism (CADRM) is designed. It ensures that the personal information of the LEO satellite network can be transmitted safely and effectively. The experimental simulation results show the improvement of network throughput, the reduction of packet loss rate and the enhancing of network reliability.     

A Smart English Text Zero-Watermarking Approach Based on Third-Level Order and Word Mechanism of Markov Model

Text information is principally dependent on the natural languages. Therefore, improving security and reliability of text information exchanged via internet network has become the most difficult challenge that researchers encounter. Content authentication and tampering detection of digital contents have become a major concern in the area of communication and information exchange via the Internet. In this paper, an intelligent text Zero-Watermarking approach SETZWMWMM (Smart English Text Zero-Watermarking Approach Based on Mid-Level Order and Word Mechanism of Markov Model) has been proposed for the content authentication and tampering detection of English text contents. The SETZWMWMM approach embeds and detects the watermark logically without altering the original English text document. Based on Hidden Markov Model (HMM), Third level order of word mechanism is used to analyze the interrelationship between contexts of given English texts. The extracted features are used as a watermark information and integrated with digital zero-watermarking techniques. To detect eventual tampering, SETZWMWMM has been implemented and validated with attacked English text. Experiments were performed on four datasets of varying lengths under multiple random locations of insertion, reorder and deletion attacks. The experimental results show that our method is more sensitive and efficient for all kinds of tampering attacks with high level accuracy of tampering detection than compared methods.     

2.4GHz无线电波的相位干涉测向研究

讨论了利用相位差测量2.4 GHz入射电磁波方位角和仰角的方法.在理想情况下分别对接收天线为三元阵和五元阵时对测向系统进行仿真,针对其测向精度比较二者的优劣性.对于五元阵接收到的信号所具有的“相位模糊”问题,采用“虚拟基线法”解相位模糊,提高测向精度.     

基于改进注意力机制的认知障碍病程分类

阿尔茨海默病(AD)是一种发病进程缓慢、随着时间不断恶化的神经退化性疾病,在老龄化的趋势下,AD患者数量日渐增加。因此,如何对其予以早期精准诊断并进行正向干预是急需解决的问题。为提高计算机辅助诊断的效率,同时促进疾病的病理生理机制研究,提出了改进的基于SE模块二维双路径融合网络的分类方法,在网络中加入缩减系数模块,增加图片有用信息占比;对通道注意模块的权重函数重新设计,增大特征图间差异,联合二维双路径网络,增大网络倚重点,达到更好分类性能的同时,防止模型过拟合。使用ADNI数据集对AD、EMCI、NC进行二分类,实验表明所提出模型准确度相比于VGG和二维双路径融合模型分别提高了5.59%和8.11%,与其它先进方法进行比较验证了所提方法的可行性。     

An Asynchronous Clustering and Mobile Data Gathering Schema Based on Timer Mechanism in Wireless Sensor Networks

Recently, Wireless sensor networks (WSNs) have become very popular research topics which are applied to many applications. They provide pervasive computing services and techniques in various potential applications for the Internet of Things (IoT). An Asynchronous Clustering and Mobile Data Gathering based on Timer Mechanism (ACMDGTM) algorithm is proposed which would mitigate the problem of “hot spots” among sensors to enhance the lifetime of networks. The clustering process takes sensors’ location and residual energy into consideration to elect suitable cluster heads. Furthermore, one mobile sink node is employed to access cluster heads in accordance with the data overflow time and moving time from cluster heads to itself. Related experimental results display that the presented method can avoid long distance communicate between sensor nodes. Furthermore, this algorithm reduces energy consumption effectively and improves package delivery rate.     

Analysis of Wireless Backhaul Networks Based on Aerial Platform Technology for 6G Systems

As next generation communication technologies emerge, new high data rate applications and high-definition large-screen video streaming have become very popular. As a result, network traffic has been increasing so much that existing backhaul networks soon will not be able to support all traffic demands. To support these needs in future 6G mobile systems, the establishment of an additional backhaul wireless network is considered essential. As one of the solutions, a wireless backhaul network based on an aerial platform has been proposed. In order to explore the potential of aerial platforms as wireless backhaul networks, in this paper, the categories for wireless backhaul networks based on aerial platforms are investigated. This paper includes a survey of the definitions and characteristics of low altitude platforms (LAPs) and high altitude platforms (HAPs), as well as channel models according to the atmosphere. For wireless backhaul network designs based on aerial platforms, altitude and platform selection options, deployment options, energy issues, and security based on target location and performance were considered in the analysis and investigation.     

Throughput Analysis of HARQ Scheme Based on Full-Duplex Two-Way AF SWIPT Relay

The simultaneous wireless information and power transfer (SWIPT) relay system is one of the emerging technologies. Xiaomi Corporation and Motorola Inc. recently launched indoor wireless power transfer equipment is one of the most promising applications. To tap the potential of the system, hybrid automatic repeat request (HARQ) is introduced into the SWIPT relay system. Firstly, the time slot structure of HARQ scheme based on full duplex two-way amplify and forward (AF) SWIPT relay is given, and its retransmission status is analyzed. Secondly, the equivalent signal-to-noise ratio and outage probability of various states are calculated by approximate simplification. Thirdly, the energy harvesting power in each state is calculated. Finally, the energy harvested-throughput sum function is constructed to characterize the performance of energy harvesting and data transmission. Simulation results show that the proposed HARQ scheme has better energy harvested-throughput sum function than the traditional HARQ scheme. When P₂ = 22 dB, the maximum sum function is 54.86% (the proposed HARQ scheme) and 52.307% (the traditional HARQ scheme), respectively.     

Investigation on the Chinese Text Sentiment Analysis Based on Convolutional Neural Networks in Deep Learning

Nowadays, the amount of wed data is increasing at a rapid speed, which presents a serious challenge to the web monitoring. Text sentiment analysis, an important research topic in the area of natural language processing, is a crucial task in the web monitoring area. The accuracy of traditional text sentiment analysis methods might be degraded in dealing with mass data. Deep learning is a hot research topic of the artificial intelligence in the recent years. By now, several research groups have studied the sentiment analysis of English texts using deep learning methods. In contrary, relatively few works have so far considered the Chinese text sentiment analysis toward this direction. In this paper, a method for analyzing the Chinese text sentiment is proposed based on the convolutional neural network (CNN) in deep learning in order to improve the analysis accuracy. The feature values of the CNN after the training process are nonuniformly distributed. In order to overcome this problem, a method for normalizing the feature values is proposed. Moreover, the dimensions of the text features are optimized through simulations. Finally, a method for updating the learning rate in the training process of the CNN is presented in order to achieve better performances. Experiment results on the typical datasets indicate that the accuracy of the proposed method can be improved compared with that of the traditional supervised machine learning methods, e.g., the support vector machine method.     

含有闭环的并联贴标机构运动学分析

目的为了提高贴标机构的通用性,解决流水线上不同倾斜面上的贴标问题,提出一种含有闭环的并联贴标机构,并进行运动学分析,研究其自由度和工作空间,验证其作为贴签机构的可行性。方法建立并联机构三维模型,利用螺旋理论分析机构的自由度,使用闭环矢量法求出机构的运动学逆解方程。利用Matlab的计算功能,采用空间极限搜索法求解机构的工作空间,绘制机构的工作空间,并分析机构在不同点的最大旋转角度。结果该并联机构拥有2个移动,1个旋转自由度;工作空间紧凑无空洞,形状规则;垂直方向大部分工作空间最大转角可达90°。结论该并联机构结构简单,垂直方向转角大,动平台旋转中心易调;结合并联机构固有的刚度大、结构稳定、惯性小的优点,可以高效地完成流水线上不规则产品贴标工序的贴标任务。     

Identification of Weather Phenomena Based on Lightweight Convolutional Neural Networks

Weather phenomenon recognition plays an important role in the field of meteorology. Nowadays, weather radars and weathers sensor have been widely used for weather recognition. However, given the high cost in deploying and maintaining the devices, it is difficult to apply them to intensive weather phenomenon recognition. Moreover, advanced machine learning models such as Convolutional Neural Networks (CNNs) have shown a lot of promise in meteorology, but these models also require intensive computation and large memory, which make it difficult to use them in reality. In practice, lightweight models are often used to solve such problems. However, lightweight models often result in significant performance losses. To this end, after taking a deep dive into a large number of lightweight models and summarizing their shortcomings, we propose a novel lightweight CNNs model which is constructed based on new building blocks. The experimental results show that the model proposed in this paper has comparable performance with the mainstream non-lightweight model while also saving 25 times of memory consumption. Such memory reduction is even better than that of existing lightweight models.     

基于随机集理论的多目标跟踪研究进展

基于随机有限集理论的多目标跟踪方法,能够避免数据关联步骤的困扰,能够较好地解决复杂环境中目标数目未知且随时间变化的多目标跟踪问题.本文分析基于数据关联和基于随机集理论的多目标跟踪方法,阐明基于随机集理论的多目标跟踪方法的特点和优点,对目标状态提取、航迹关联、更准确的滤波算法,以及复杂条件下的PHDF算法等关键问题进行总结和评述,并指出该领域今后的研究热点.