ZTE Rolls Out a Series of Industry's First TD-SCDMA Handset Products at PT/WIRELESS & NETWORKS COMM CHINA 2007

ZTE Corporation (ZTE), a leading global provider of telecommunications equipment and network solutions, unveiled

Intelligent Reflecting Surface Assisted Transmission Optimization Strategies in Wireless Networks

Wireless Power Transfer(WPT)technology can provide real-time power for many terminal devices in Internet of Things(IoT)through millimeterWave(mmWave)to support applications with large capacity and low latency.Although the intelligent reflecting surface(IRS)can be adopted to create effective virtual links to address the mmWave blockage problem,the conventional solutions only adopt IRS in the downlink from the Base Station(BS)to the users to enhance the received signal strength.In practice,the reflection of IRS is also applicable to the uplink to improve the spectral efficiency.It is a challenging to jointly optimize IRS beamforming and system resource allocation for wireless energy acquisition and information transmission.In this paper,we first design a Low-Energy Adaptive Clustering Hierarchy(LEACH)clustering protocol for clustering and data collection.Then,the problem of maximizing the minimum system spectral efficiency is constructed by jointly optimizing the transmit power of sensor devices,the uplink and downlink transmission times,the active beamforming at the BS,and the IRS dynamic beamforming.To solve this non-convex optimization problem,we propose an alternating optimization(AO)-based joint solution algorithm.Simulation results show that the use of IRS dynamic beamforming can significantly improve the spectral efficiency of the system,and ensure the reliability of equipment communication and the sustainability of energy supply under NLOS link.

Rao Algorithms-Based Structure Optimization for Heterogeneous Wireless Sensor Networks

The structural optimization of wireless sensor networks is a critical issue because it impacts energy consumption and hence the network’s lifetime.Many studies have been conducted for homogeneous networks,but few have been performed for heterogeneouswireless sensor networks.This paper utilizes Rao algorithms to optimize the structure of heterogeneous wireless sensor networks according to node locations and their initial energies.The proposed algorithms lack algorithm-specific parameters and metaphorical connotations.The proposed algorithms examine the search space based on the relations of the population with the best,worst,and randomly assigned solutions.The proposed algorithms can be evaluated using any routing protocol,however,we have chosen the well-known routing protocols in the literature:Low Energy Adaptive Clustering Hierarchy(LEACH),Power-Efficient Gathering in Sensor Information Systems(PEAGSIS),Partitioned-based Energy-efficient LEACH(PE-LEACH),and the Power-Efficient Gathering in Sensor Information Systems Neural Network(PEAGSIS-NN)recent routing protocol.We compare our optimized method with the Jaya,the Particle Swarm Optimization-based Energy Efficient Clustering(PSO-EEC)protocol,and the hybrid Harmony Search Algorithm and PSO(HSA-PSO)algorithms.The efficiencies of our proposed algorithms are evaluated by conducting experiments in terms of the network lifetime(first dead node,half dead nodes,and last dead node),energy consumption,packets to cluster head,and packets to the base station.The experimental results were compared with those obtained using the Jaya optimization algorithm.The proposed algorithms exhibited the best performance.The proposed approach successfully prolongs the network lifetime by 71% for the PEAGSIS protocol,51% for the LEACH protocol,10% for the PE-LEACH protocol,and 73% for the PEGSIS-NN protocol;Moreover,it enhances other criteria such as energy conservation,fitness convergence,packets to cluster head,and packets to the base station.

Enhancing Wireless Sensor Network Efficiency through Al-Biruni Earth Radius Optimization

The networks of wireless sensors provide the ground for a range of applications,including environmental moni-toring and industrial operations.Ensuring the networks can overcome obstacles like power and communication reliability and sensor coverage is the crux of network optimization.Network infrastructure planning should be focused on increasing performance,and it should be affected by the detailed data about node distribution.This work recommends the creation of each sensor’s specs and radius of influence based on a particular geographical location,which will contribute to better network planning and design.By using the ARIMA model for time series forecasting and the Al-Biruni Earth Radius algorithm for optimization,our approach bridges the gap between successive terrains while seeking the equilibrium between exploration and exploitation.Through implementing adaptive protocols according to varying environments and sensor constraints,our study aspires to improve overall network operation.We compare the Al-Biruni Earth Radius algorithm along with Gray Wolf Optimization,Particle Swarm Optimization,Genetic Algorithms,and Whale Optimization about performance on real-world problems.Being the most efficient in the optimization process,Biruni displays the lowest error rate at 0.00032.The two other statistical techniques,like ANOVA,are also useful in discovering the factors influencing the nature of sensor data and network-specific problems.Due to the multi-faceted support the comprehensive approach promotes,there is a chance to understand the dynamics that affect the optimization outcomes better so decisions about network design can be made.Through delivering better performance and reliability for various in-situ applications,this research leads to a fusion of time series forecasters and a customized optimizer algorithm.

Single Photon Detection Technology in Underwater Wireless Optical Communication:Modulation Modes and Error Correction Coding Analysis

This study explores the application of single photon detection(SPD)technology in underwater wireless optical communication(UWOC)and analyzes the influence of different modulation modes and error correction coding types on communication performance.The study investigates the impact of on-off keying(OOK)and 2-pulse-position modulation(2-PPM)on the bit error rate(BER)in single-channel intensity and polarization multiplexing.Furthermore,it compares the error correction performance of low-density parity check(LDPC)and Reed-Solomon(RS)codes across different error correction coding types.The effects of unscattered photon ratio and depolarization ratio on BER are also verified.Finally,a UWOC system based on SPD is constructed,achieving 14.58 Mbps with polarization OOK multiplexing modulation and 4.37 Mbps with polarization 2-PPM multiplexing modulation using LDPC code error correction.

Integrated Clustering and Routing Design and Triangle Path Optimization for UAV-Assisted Wireless Sensor Networks

With the development of the Internet of Things(IoT),it requires better performance from wireless sensor networks(WSNs),such as larger coverage,longer lifetime,and lower latency.However,a large amount of data generated from monitoring and long-distance transmission places a heavy burden on sensor nodes with the limited battery power.For this,we investigate an unmanned aerial vehicles assisted mobile wireless sensor network(UAV-assisted WSN)to prolong the network lifetime in this paper.Specifically,we use UAVs to assist the WSN in collecting data.In the current UAV-assisted WSN,the clustering and routing schemes are determined sequentially.However,such a separate consideration might not maximize the lifetime of the whole WSN due to the mutual coupling of clustering and routing.To efficiently prolong the lifetime of the WSN,we propose an integrated clustering and routing scheme that jointly optimizes the clustering and routing together.In the whole network space,it is intractable to efficiently obtain the optimal integrated clustering and routing scheme.Therefore,we propose the Monte-Las search strategy based on Monte Carlo and Las Vegas ideas,which can generate the chain matrix to guide the algorithm to find the solution faster.Unnecessary point-to-point collection leads to long collection paths,so a triangle optimization strategy is then proposed that finds a compromise path to shorten the collection path based on the geometric distribution and energy of sensor nodes.To avoid the coverage hole caused by the death of sensor nodes,the deployment of mobile sensor nodes and the preventive mechanism design are indispensable.An emergency data transmission mechanism is further proposed to reduce the latency of collecting the latency-sensitive data due to the absence of UAVs.Compared with the existing schemes,the proposed scheme can prolong the lifetime of the UAVassisted WSN at least by 360%,and shorten the collection path of UAVs by 56.24%.

A Novel Approach to Energy Optimization:Efficient Path Selection in Wireless Sensor Networks with Hybrid ANN

In pursuit of enhancing the Wireless Sensor Networks(WSNs)energy efficiency and operational lifespan,this paper delves into the domain of energy-efficient routing protocols.InWSNs,the limited energy resources of Sensor Nodes(SNs)are a big challenge for ensuring their efficient and reliable operation.WSN data gathering involves the utilization of a mobile sink(MS)to mitigate the energy consumption problem through periodic network traversal.The mobile sink(MS)strategy minimizes energy consumption and latency by visiting the fewest nodes or predetermined locations called rendezvous points(RPs)instead of all cluster heads(CHs).CHs subsequently transmit packets to neighboring RPs.The unique determination of this study is the shortest path to reach RPs.As the mobile sink(MS)concept has emerged as a promising solution to the energy consumption problem in WSNs,caused by multi-hop data collection with static sinks.In this study,we proposed two novel hybrid algorithms,namely“ Reduced k-means based on Artificial Neural Network”(RkM-ANN)and“Delay Bound Reduced kmeans with ANN”(DBRkM-ANN)for designing a fast,efficient,and most proficient MS path depending upon rendezvous points(RPs).The first algorithm optimizes the MS’s latency,while the second considers the designing of delay-bound paths,also defined as the number of paths with delay over bound for the MS.Both methods use a weight function and k-means clustering to choose RPs in a way that maximizes efficiency and guarantees network-wide coverage.In addition,a method of using MS scheduling for efficient data collection is provided.Extensive simulations and comparisons to several existing algorithms have shown the effectiveness of the suggested methodologies over a wide range of performance indicators.

四川盆地PT1井区海相地层工程地质特征研究

PT1井区超深海相地层钻井过程中气侵和井漏频发,严重制约该区块的安全高效开发。文章基于有效应力法,利用最优化方法开展了海相地层孔隙压力评价;结合断层和裂缝发育程度探讨了PT1井区气侵和井漏纵横向分布特征。结果表明,受异常高压和裂缝发育程度的双重影响,气侵主要发生在龙潭组,占比达40%;井漏主要发生在筇竹寺组和灯影组,占总漏失量的80%以上。气侵与异常压力、裂缝发育程度、断裂情况等因素有关,异常高压是气侵内在的原因,而断裂带和发育的构造裂缝为气侵提供了必要条件。井漏层位和漏失量主要受一、二级大型断裂带控制,不同断裂带的影响具有显著的叠加效应,断裂带附近发育的构造裂缝为漏失提供了通道,距离F I7断裂越近越易出现漏失,且漏失量越大。研究成果为PT1井区钻井过程井下复杂预防和处理提供了科学支撑。

PT对称光晶格势中的涡旋光孤子传输特性的研究

本研究提出了一种实现具有宇称时间(PT)对称性的光学贝塞尔势的方案。通过从冷原子气体中光的衍射、非局域非线性和PT对称势约束之间的相互作用入手,研究了如何存在、传播和操纵二维涡旋光孤子。结果显示,该系统支持稳定的二维涡旋光孤子,其拓扑电荷最大值为|m|=6。此外,可通过控制PT对称晶格势的虚部来保证这种孤子的稳定性。由于里德堡-电磁感应透明(Rydberg-EIT)效应增强了局域和非局域非线性,因此这些二维涡旋光孤子只需要很低的功率就可以激发出来。研究结果不仅对PT对称势以及操纵二维涡旋光孤子有重要意义,还在光信息处理和传输方面具有很好的应用前景。

尖端Pt负载纳米Au棒的制备及其催化还原4-硝基苯酚

采用种子生长法制备了长径比约为4的金纳米棒(AuNRs),并将铂负载其两端制备出尖端Pt负载的纳米Au棒(Pt-AuNRs)。采用紫外-可见分光光度计、透射电子显微镜和X射线光电子能谱等一系列常规表征手段对AuNRs和Pt-AuNRs的物化性质进行表征及分析。研究AuNRs和Pt-AuNRs作为催化剂在NaBH4存在下催化还原4-硝基苯酚(4-NP)的性能。首次提出Pt-AuNRs催化还原4-NP机制。结果表明:500-Pt-AuNRs催化剂表现出最好的催化性能,速率常数Kapp=0.383 6 min^(-1),是AuNRs催化剂的4.7倍;Pt-AuNRs特殊的异质结构以及高表面活性和稳定性,有助于BH-4在其表面的高效吸附和电子转移。

模具设计与制造专业班会内容与PTS人生技能课程相融合的研究

模具设计与制造专业学生的班会内容与专业拓展课《PTS人生技能》的内容相融合,先分析模具设计与制造专业的培养目标,阐述拓展课的8个模块,并以“理解和管理情绪模块”为例进行了主题班会的实施过程的介绍。班会内容与PTS人生技能课的融合是一种有益的尝试,班会中应用了课程的“演、思、说、用”4个环节。以学生为中心的理念,经验学习圈理论。让学生在班会中学习和应用人生技能,提升了个人综合素质,为学生的全面发展提供有力支持。

Al_(2)O_(3)负载Pt基催化剂表面动态变化的谱学研究

明确多相催化剂表面在反应过程的动态变化对催化剂的优化、设计有重要意义.我们通过控制Pt的不同负载量制备了一系列Al_(2)O_(3)负载的Pt/Al_(2)O_(3)催化剂,利用X-射线衍射、X-光电子能谱、球差扫描电镜、CO-探针的红外光谱、低能离子散射谱、程序升温氧化和拉曼光谱等研究Pt/Al_(2)O_(3)的表面结构和反应过程中的变化,以丙烷直接脱氢(PDH)反应为探针,考察反应过程存在“诱导”期的表面动态变化,特别是表面积碳、表面形貌、活性位点等的演化.进而与其催化反应性能关联,发现Pt纳米粒子(NP)和团簇上丙烷易深度脱氢或断裂C-C键生成CH_(4)的同时形成积碳、随后失去活性;而孤立的Pt单原子位点(SAC)上不易生成积碳、是丙烯生成的关键活性位.

双耦合SP-S补偿紧凑型抗偏移WPT系统

在无线电能传输(wireless power transfer,WPT)系统中,偏移是不可避免的,偏移会引起系统参数的变化从而影响系统的传输性能。基于S-S和P-S补偿拓扑,提出一种具有抗偏移特性的双耦合SP-S补偿的紧凑型WPT系统。该系统采用两个同轴布置、相互解耦的圆角方形线圈作为能量的发射线圈,其与单一方形接收线圈均有耦合,提升了X方向和Y方向的抗偏移容忍度。通过谐振参数配置使接收线圈在偏移的过程中,一个线圈回路的输出增加,另一个线圈回路输出减少,从而使系统输出随接收线圈位置偏移波动平缓。提出方形解耦线圈结构参数的设计方法,并分析发射端并联补偿电容对输出抗偏移性能的影响。最后,搭建实验平台验证该方法的有效性与系统的抗偏移能力。

孤独症谱系障碍RUBI-PT方案的改编及适应性调查

目的·探究“行为干预研究单位孤独症网络家长培训”[the Research Units in Behavioral Intervention(RUBI)Autism Network Parent Training,RUBI-PT]方案的中国本土化改编并对其适应性进行调查。方法·按照文化改编的4个步骤对RUBI-PT方案进行改编,包括信息收集、初步改编设计、初步改编测试、进一步调整。信息收集阶段邀请了6位儿科专家和2位心理治疗师进行6次焦点小组访谈,并根据专家意见从语言、治疗形式、治疗设置等方面对RUBI-PT方案进行初步改编;初步改编测试阶段招募了16位孤独症谱系障碍(autism spectrum disorder,ASD)患儿的家长,分2批参加线上RUBI-PT,结束后收集项目反馈问卷并行适应性调查分析,最后根据测试结果进行方案的进一步调整。结果·RUBI-PT的初步改编方案由个体培训调整为团体培训,包含8次核心技能课程,采用线上会议形式实施。初步测试结果显示,家长对于上课进度、上课过程、课后作业完成情况、作业点评情况的满意度分别为90%、80%、100%和100%;课程难度方面,第7次课(功能性沟通训练)和第8次课(教授技能)的难度最大。依据上述调查结果和专家小组意见完成进一步调整,最终形成本土化RUBI-PT的改编方案。结论·经过改编和适应性调查,形成了适用于中国ASD儿童家庭的家长行为训练策略即RUBI-PT。

基于磁控制的非谐WPT系统抗偏移策略

针对无线电能传输(WPT)系统耦合线圈偏移导致输出电压增益下降的问题,提出一种基于初级可变电感补偿的WPT系统抗偏移方法。首先,建立T型CLC-S补偿网络拓扑模型,对比分析系统谐振与非谐振工况下互感与电压增益的关系。然后,介绍可变电感的技术原理,并结合系统互感变化下的电压增益曲线,得到基于初级可变电感的稳压策略。最后,搭建了仿真模型与实验平台,验证了策略的有效性。仿真和实验结果表明,采用所提稳压策略能够有效提升系统在偏移情况下的鲁棒性,相较于实验组,扩宽了互感可变化范围59.35%,恒压输出区间范围内效率稳定保持在81.6%以上。

基于等效阻抗的分数阶RLC_(α)串联谐振BD-WPT系统传输特性分析

针对谐振式无线电能传输系统中分数阶电感、电容元件的仿真实现困难的问题,采用等效阻抗实现分数阶电容的等效.基于分数阶电容的阻抗特性,给出了一种分数阶RLC_(α)串联谐振双向无线电能传输(bidirectional wireless power transfer,BD-WPT)系统结构,通过建立含分数阶电容的串联谐振式双向无线电能传输系统的电路模型,推导了其传输功率和效率关系.仿真实验结果表明,与整数阶串联谐振系统相比,系统的输出功率提升了7.82%,传输效率提升了0.58个百分点.

电动汽车多车位WPT下沉式磁屏蔽系统研究

在电动汽车无线电能传输系统中,实现高效传输的同时减少磁泄漏一直是一个技术挑战。针对这一问题,本文提出了一种应用于多无线电能传输系统的下沉式屏蔽线圈结构,该结构在减小目标面漏磁的同时不会影响系统的传输效率。首先,提出了一种基于矢量磁位的矩形线圈磁场计算方法,通过此方法对系统目标面漏磁进行分析,为后续的磁泄漏优化提供了理论依据;其次,介绍了一种漏磁优化的方法,运用该方法得到满足要求的各线圈参数,为实现高效的无线电能传输提供了关键支持;最后,根据得到的线圈参数,研制了一套带磁屏蔽结构的双车位电动汽车无线充电系统,通过仿真和实验,让提出的屏蔽结构和方法的有效性得到了充分证实。结果显示,当系统输出功率恒定在4 kW时,所提出的屏蔽结构不仅使目标区域最大泄漏磁场降低了25%,且传输效率高达95%。

石墨烯负载Pt催化剂的制备及对甲酸的电催化氧化

采用恒电位电化学还原技术制得石墨烯电极,然后采用循环伏安方法在石墨烯基体上电沉积一层Pt纳米微粒.采用电化学测试技术研究Pt/石墨烯电极材料的电子传递性能及对甲酸电催化氧化性能.相对于商用Pt电极材料,Pt纳米微粒/石墨烯电极材料对甲酸表现出优异的电催化氧化活性,氧化峰电流显著提高.该种石墨烯负载Pt催化剂有望用作直接甲酸燃料电池的优良电极材料.

基于Al_(2)O_(3)陶瓷的Pt/PtRh型厚膜热电偶封装测试

设计了一种基于氧化铝(Al_(2)O_(3))柱体的Pt/PtRh型厚膜热电偶。采用丝网印刷工艺完成传感器功能层的制备,这种方法工艺简单、可操作性强、成本低廉。对所制备的厚膜热电偶进行封装设计并进行测试。实验结果表明:带封装热电偶的迟滞大小为4.10%,小于无封装的7.65%,而且带封装热电偶在高温阶段与标准热电偶极其吻合,其平均塞贝克系数更接近于标准热电偶。实验结果均表明封装设计有利于膜状热电偶测试的准确性,达到了工程化需要。

基于交互式设计超材料建模与分析的MCR-WPT效率提升研究

超材料具有特殊的磁场调控能力,被广泛关注并应用于磁耦合谐振无线电能传输(MCR-WPT)领域,但寻求针对特定领域目标需求的超材料设计具有挑战性.目前,超材料的一般设计方法为S参数反演法和等效电路法,设计流程通常需要多次建模仿真得到目标参数,该过程较为繁琐耗时.对此,深入分析上述两种设计方法的特性并将二者结合,采用HFSS与MATLAB软件交互设计和优化用于MCR-WPT特性提升的超材料,有效简化了超材料的设计过程.以无线电能传输效率优化为目标设计方形和Koch两种超材料单元,分析对比两种单元的电磁特性.搭建工作频率为6.78 MHz的MCR-WPT系统实验平台,探究两种超材料对传输效率的影响.实验结果表明,方形超材料和Koch超材料分别实现了28.4%和24.6%的最大传输效率提升,证明了交互设计可以更简便地设计超材料并且用于无线电能传输系统传输效率的提升.