CSPS_2015_submission_67

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SCI编辑问:倾向性评分后,你验证了吗?

SCI编辑问:倾向性评分后,你验证了吗?
倾向性评分是一种统计学上的不就方法常用于观察性研究但对实验性研究但基线不均衡时也可以操作
SCI编 辑 问 : 倾 向 性 评 分 后 , 你 验 证 了 吗 ?
缘起
精鼎48期SPSS统计软件实战训练营开班啦!
倾向性评分(PS)绝对可以算上近年统计分析领域的网红了,很多大牛期刊近年都有PS相 关的论文刊出。实现倾向性评分匹配目前常用软件有,SPSS、stata、R。本号也推过几期 PSM的推文。
然而权威杂志,对PS论文都有一个要求,就是你倾向性评分匹配后,你进行了匹配效果验证 了吗?
松哥统计说 倾向性评分是一种统计学上的不就方法,常用于观察性研究,但对实验性研究,但基线不均衡 时,也可以操作。
该方法的思想:就是在现有的个案中,选择一部分符合基线条件的个案进行后续分析。虽然增 加了可比性,但也损失了样本量。倾向性评分有4种处理方法,松哥新书里有详细说明. 匹配后数据均衡性检验,对于计量资料可以采用t检验,计数资料可以采用卡方检验。
算出后,进行画图即可。
【赠人玫瑰,手留余香】 【2055】SPSS25,作图优化啦,bayes也可统计了 【2054】SPSS太不靠谱,明明没有缺失值,非说有缺失值,难道是真的? 【2053】Cox比例风险模型,等比例风险你验证了吗? 【2052】SCI编辑让做控制协变量的生存曲线 【2051】趋势性检验集锦 【2050】析因设计方差分析 【2049】SCI作图又一技能-嵌入图
【2041】为什么SPSS读取Excel数据乱码或空值,真实案例 【2040】谁说SPSS不能画统计地图
> 10%; significant P-values) in baseline variables between propensity score-matched groups should not be overlooked .】 那么你会问,这这绝对标准差值如何算呢,请参考如下公式,分别针对计量与计数资料:

elastix_registration_method -回复

elastix_registration_method -回复

elastix_registration_method -回复什么是elastix_registration_method?elastix_registration_method是一种医学图像配准方法。

医学图像配准是将不同的医学图像(如CT扫描、MRI等)通过算法进行对齐和匹配的过程。

elastix_registration_method是开源软件elastix中的一种配准算法,可以实现二维和三维图像的配准。

配准是医学影像处理中重要的一环,它可以用于许多应用,包括病灶检测、手术导航和治疗规划等。

在许多医学图像中,由于不同的成像条件、位置和姿态变化,图像之间会存在一定的差异。

配准算法的目标就是通过对这些图像进行空间转换,使得它们在同一坐标系下对齐,便于后续的分析和处理。

elastix_registration_method使用弹性体变形模型将一个图像的像素点映射到另一个图像的对应位置。

通过对目标图像的每个像素点进行变形,使得目标图像和参考图像的特征点之间达到最佳的匹配。

这种变形模型可以通过最小化图像间的差异来优化,例如最小化目标图像和参考图像的灰度值差异或互信息。

elastix_registration_method具有以下几个步骤来实现图像配准:1. 数据准备:首先,需要准备待配准的图像数据。

这些图像数据可以来自同一个病例的不同时间点、不同成像设备或不同成像模态。

此外,还需要选择一个作为参考图像的基准图像。

2. 参数选择:elastix_registration_method具有许多可调节的参数,包括变形模型的类型、优化方法、正则化参数等。

根据具体的应用场景和数据特点,需要选择合适的参数。

3. 初始变形场估计:elastix_registration_method使用一个初始的变形场作为起点。

初始变形场可以是全局变形或局部变形,通过预处理方法获得。

当然,也可以根据应用场景的需要来选择是否需要初始变形场。

CS3012-ISZR,CS3011-ISZ,CS3011-ISZR,CDB30XX, 规格书,Datasheet 资料

CS3012-ISZR,CS3011-ISZ,CS3011-ISZR,CDB30XX, 规格书,Datasheet 资料

2
DS597F6
芯天下--/
CS3011 CS3012
1. CHARACTERISTICS AND SPECIFICATIONS
ELECTRICAL CHARACTERISTICS
V+ = +5 V, V- = 0V, VCM = 2.5 V (Note 1) CS3011/CS3012 Parameter Input Offset Voltage Average Input Offset Drift Long Term Input Offset Voltage Stability Input Bias Current Input Offset Current Input Noise Voltage Density RS = 100 Ω, f0 = 1 Hz RS = 100 Ω, f0 = 1 kHz Input Noise Voltage Input Noise Current 0.1 to 10 Hz 0.1 to 10 Hz • (Note 4) (Note 5) • • • • Input Noise Current Density f0 = 1 Hz Input Common Mode Voltage Range Common Mode Rejection Ratio (dc) Power Supply Rejection Ratio Large Signal Voltage Gain RL = 2 kΩ to V+/2 Output Voltage Swing RL = 2 kΩ to V+/2 RL = 100 kΩ to V+/2 Slew Rate Overload Recovery Time Supply Current PWDN active (CS3011 Only) PWDN Threshold Start-up Time CS3011 CS3012 (Note 6) (Note 6) (Note 7) • • • • • RL = 2 k, 100 pF TA = 25º C TA = 25º C • • -0.1 115 120 200 +4.7 (Note 2) (Note 2) • • Min Typ ±0.01 (Note 3) ±50 ±100 12 12 250 100 1.9 120 136 300 +4.99 2 600 0.9 1.7 (V+)-1.25 1.4 2.4 15 12 ±1000 ±2000 pA pA

PDPS入门

PDPS入门
Siemens PLM Software
1.整体界面介绍
安装软件完毕后,启动主程序Process Designer,经过登录和Logo画面,然后 就是图示项目选择画面,此列表新安装客户应当是空的,直接点击Cancel跳过
然后进入软件主界面,可以看到除了主菜单和主按钮栏,其他都是由各个小窗口构 成,这些窗口可以任意拖放,合并,隐藏(每个窗口右上角有隐藏和关闭按钮)。 这些窗口的布局称为Layout,程序内置多种方案供选择,图示是Standard方案,用 户可以根据自己操作习惯,任意修改,退出程序时,会有提示是否保存当前修改, 这里指的修改就是对界面布局的修改。
2.创建和整理结构
Process Designer是一个依赖数 据库的软件,他的所有数据分成 2部分: 一部分是3D数模,这部分数据是 放在sysroot下,这个文件夹的名 字可以随便取,只要在程序内 Options下告诉程序这个文件夹在 哪即可,所以不用担心A机器上 的成果到了B机器上看不了; 另一部分数据是3D数模的相互关 系,这部分数据是存储在Oracle 数据库中的,无法象3D数模这样 在Windows下查看,只能用程序 将这些关系以XML的形式导出和 存放。 所以,完整的PD成果必须包含该 模拟中所需要调用的数模和对应 的XML 本章将讲述如何新建项目然后导 出成果
8
Plant Simulation:
Process optimization
9
Reports:
Generation of process documentation
PS下模拟验证工艺与资源
10
© UGS Corp. 2008. All rights reserved.
工厂模拟后提出修改与 优化意见

正电子发射X射线计算机断层成像系统数字化技术专用注册审查指导原则

正电子发射X射线计算机断层成像系统数字化技术专用注册审查指导原则

正电子发射/X射线计算机断层成像系统(数字化技术专用)注册审查指导原则本指导原则是对正电子发射/X射线计算机断层成像系统(Imaging system of positron emission and X-ray computed tomography,简称“PET/CT”)中所用的数字化技术的专用要求。

注册申请人应依据具体产品的特性对注册申报资料的内容进行充实和细化。

注册申请人还应依据具体产品的特性确定其中的内容是否适用,若不适用,需具体阐述其理由及相应的科学依据。

本指导原则是供注册申请人和技术审评人员使用的指导性文件,不包括注册审批所涉及的行政事项,不作为法规强制执行。

若有满足相关法规要求的其他方法,也可采用,并应提供详细的研究资料和验证资料。

本指导原则是在现行法规和标准体系以及当前认知水平下制定的,应在遵循相关法规的前提下使用。

随着法规和标准的不断完善,以及科学技术的不断发展,本指导原则相关内容也将进行适时的调整。

本指导原则作为《正电子发射/X射线计算机断层成像系统注册技术审查指导原则》(简称“PET/CT指导原则”)的补充,是对PET/CT数字化技术的专用要求。

申报资料除符合本指导原则的要求外,还应符合“PET/CT指导原则”的要求。

一、适用范围本指导原则适用于PET/CT产品数字化技术相关的要求,该产品按照《医疗器械分类目录》,产品属于目录06医用成像器械,一级产品类别为17组合功能融合成像器械,二级产品类别为02正电子发射/X射线计算机断层成像系统,按第三类医疗器械管理。

正电子发射断层成像系统(简称PET)单独申报或正电子发射磁共振成像系统(简称PET/MR)设备中PET数字化技术相关要求可参照本指导原则。

二、技术分类(一)PET信号数字化技术路线数字化是指将连续模拟量通过采样、量化、编码及必要的辅助运算方式转换为离散数字量的过程。

PET数字化技术是以数字化的信号处理硬件为手段,以实现入射光子的准确测量为目的,而发展的一系列技术。

CSPS 2015 中文征稿v1

CSPS 2015 中文征稿v1

2015 The 4th International Conference on Communications,Signal Processing, and Systems(CSPS2015)第四届通信、信号处理和系统国际会议将于2015年10月23日-24日在四川成都举行。

会议旨在为世界各地的研究人员、工程师和学者提供一个交流通信与信息技术领域最新研究成果的平台。

论文将在由Springer出版的Lecture Notes in Electrical Engineering中发表,并被EI和ISTP检索。

另外,优秀论文将在SCI期刊中发表。

前三届CSPS会议分别于2012、2013和2014年在北京、天津和呼和浩特举行,所发表的会议论文全部已被EI检索,并有共计100多篇优秀论文(扩充后)发表在:∙EURASIP Journal on Wireless Communications and Networking∙Wiley Security and Communication Networks (SCN) Journal∙International Journal of Sensor Networks∙EURASIP Journal on Advances in Signal Processing∙(Elsevier) Physical Communications共5篇SCI源期刊中。

CSPS 2015会务组希望在今年的会议中出现更多的优秀论文,让科研工作者可以分享和交流自己的成果。

重要日期:◆论文提交日期(全英文):2015年8月15日◆录用通知日期:2015年9月25日◆最终稿提交时间:2015年10月10日◆会议时间:2015年10月23-24日征文主题(不局限于):∙Wireless communications∙Wireless networks∙Optical communications and networks∙Internet of Things∙Wireless sensor networks∙Wireless mesh networks∙Ad hoc networks∙Underwater sensor networks∙Network security∙Testbed of communications and networks∙Information theory and coding∙Multimedia communications∙Smart grid∙Radar signal processing∙Audio and acoustic signal processing∙Bio imaging and signal processing∙Design and implementation of signal processing systems∙Image, video and multidimensional signal processing∙Industry technology tracks∙Information forensics and security∙Machine learning for signal processing∙Multimedia signal processing∙Multisensor data fusion∙Sensor array and multichannel signal processing∙Signal processing education∙Signal processing for communications and networking∙Signal processing theory and methods∙Speech processing∙Spoken language processing∙Analog Signal Processing∙Genomics Signal Processing∙Biomedical and Life-Science Circuits, Systems and Applications ∙Circuits and Systems for Communications∙Computer-Aided Network Design∙Digital Signal Processing∙Education in Circuits and Systems∙Live Demonstrations of Circuits and Systems∙Multimedia Systems and Applications∙Nanoelectronics and Gigascale Systems∙Neural Networks and Systems∙Fuzzy Logic Systems∙Nonlinear Circuits and Systems∙Power and Energy Circuits and Systems∙Sensory Systems∙Radar Systems∙Chaos Systems∙Visual Signal Processing and Communications∙VLSI Systems and Applications文章要求全英文PDF格式投稿,投稿链接:https:///conferences/?conf=csps2015更多信息请查看会议网站:如果对会议或投稿有任何问题,请发送邮件至:Jiasong Mu <mujiasong@>Wei Wang <weiwangvip@>。

低频活动漂浮潜水船声探测系统(LFATS)说明书

低频活动漂浮潜水船声探测系统(LFATS)说明书

LOW-FREQUENCY ACTIVE TOWED SONAR (LFATS)LFATS is a full-feature, long-range,low-frequency variable depth sonarDeveloped for active sonar operation against modern dieselelectric submarines, LFATS has demonstrated consistent detection performance in shallow and deep water. LFATS also provides a passive mode and includes a full set of passive tools and features.COMPACT SIZELFATS is a small, lightweight, air-transportable, ruggedized system designed specifically for easy installation on small vessels. CONFIGURABLELFATS can operate in a stand-alone configuration or be easily integrated into the ship’s combat system.TACTICAL BISTATIC AND MULTISTATIC CAPABILITYA robust infrastructure permits interoperability with the HELRAS helicopter dipping sonar and all key sonobuoys.HIGHLY MANEUVERABLEOwn-ship noise reduction processing algorithms, coupled with compact twin line receivers, enable short-scope towing for efficient maneuvering, fast deployment and unencumbered operation in shallow water.COMPACT WINCH AND HANDLING SYSTEMAn ultrastable structure assures safe, reliable operation in heavy seas and permits manual or console-controlled deployment, retrieval and depth-keeping. FULL 360° COVERAGEA dual parallel array configuration and advanced signal processing achieve instantaneous, unambiguous left/right target discrimination.SPACE-SAVING TRANSMITTERTOW-BODY CONFIGURATIONInnovative technology achievesomnidirectional, large aperture acousticperformance in a compact, sleek tow-body assembly.REVERBERATION SUPRESSIONThe unique transmitter design enablesforward, aft, port and starboarddirectional transmission. This capabilitydiverts energy concentration away fromshorelines and landmasses, minimizingreverb and optimizing target detection.SONAR PERFORMANCE PREDICTIONA key ingredient to mission planning,LFATS computes and displays systemdetection capability based on modeled ormeasured environmental data.Key Features>Wide-area search>Target detection, localization andclassification>T racking and attack>Embedded trainingSonar Processing>Active processing: State-of-the-art signal processing offers acomprehensive range of single- andmulti-pulse, FM and CW processingfor detection and tracking. Targetdetection, localization andclassification>P assive processing: LFATS featuresfull 100-to-2,000 Hz continuouswideband coverage. Broadband,DEMON and narrowband analyzers,torpedo alert and extendedtracking functions constitute asuite of passive tools to track andanalyze targets.>Playback mode: Playback isseamlessly integrated intopassive and active operation,enabling postanalysis of pre-recorded mission data and is a keycomponent to operator training.>Built-in test: Power-up, continuousbackground and operator-initiatedtest modes combine to boostsystem availability and accelerateoperational readiness.UNIQUE EXTENSION/RETRACTIONMECHANISM TRANSFORMS COMPACTTOW-BODY CONFIGURATION TO ALARGE-APERTURE MULTIDIRECTIONALTRANSMITTERDISPLAYS AND OPERATOR INTERFACES>State-of-the-art workstation-based operator machineinterface: Trackball, point-and-click control, pull-down menu function and parameter selection allows easy access to key information. >Displays: A strategic balance of multifunction displays,built on a modern OpenGL framework, offer flexible search, classification and geographic formats. Ground-stabilized, high-resolution color monitors capture details in the real-time processed sonar data. > B uilt-in operator aids: To simplify operation, LFATS provides recommended mode/parameter settings, automated range-of-day estimation and data history recall. >COTS hardware: LFATS incorporates a modular, expandable open architecture to accommodate future technology.L3Harrissellsht_LFATS© 2022 L3Harris Technologies, Inc. | 09/2022NON-EXPORT CONTROLLED - These item(s)/data have been reviewed in accordance with the InternationalTraffic in Arms Regulations (ITAR), 22 CFR part 120.33, and the Export Administration Regulations (EAR), 15 CFR 734(3)(b)(3), and may be released without export restrictions.L3Harris Technologies is an agile global aerospace and defense technology innovator, delivering end-to-endsolutions that meet customers’ mission-critical needs. The company provides advanced defense and commercial technologies across air, land, sea, space and cyber domains.t 818 367 0111 | f 818 364 2491 *******************WINCH AND HANDLINGSYSTEMSHIP ELECTRONICSTOWED SUBSYSTEMSONAR OPERATORCONSOLETRANSMIT POWERAMPLIFIER 1025 W. NASA Boulevard Melbourne, FL 32919SPECIFICATIONSOperating Modes Active, passive, test, playback, multi-staticSource Level 219 dB Omnidirectional, 222 dB Sector Steered Projector Elements 16 in 4 stavesTransmission Omnidirectional or by sector Operating Depth 15-to-300 m Survival Speed 30 knotsSize Winch & Handling Subsystem:180 in. x 138 in. x 84 in.(4.5 m x 3.5 m x 2.2 m)Sonar Operator Console:60 in. x 26 in. x 68 in.(1.52 m x 0.66 m x 1.73 m)Transmit Power Amplifier:42 in. x 28 in. x 68 in.(1.07 m x 0.71 m x 1.73 m)Weight Winch & Handling: 3,954 kg (8,717 lb.)Towed Subsystem: 678 kg (1,495 lb.)Ship Electronics: 928 kg (2,045 lb.)Platforms Frigates, corvettes, small patrol boats Receive ArrayConfiguration: Twin-lineNumber of channels: 48 per lineLength: 26.5 m (86.9 ft.)Array directivity: >18 dB @ 1,380 HzLFATS PROCESSINGActiveActive Band 1,200-to-1,00 HzProcessing CW, FM, wavetrain, multi-pulse matched filtering Pulse Lengths Range-dependent, .039 to 10 sec. max.FM Bandwidth 50, 100 and 300 HzTracking 20 auto and operator-initiated Displays PPI, bearing range, Doppler range, FM A-scan, geographic overlayRange Scale5, 10, 20, 40, and 80 kyd PassivePassive Band Continuous 100-to-2,000 HzProcessing Broadband, narrowband, ALI, DEMON and tracking Displays BTR, BFI, NALI, DEMON and LOFAR Tracking 20 auto and operator-initiatedCommonOwn-ship noise reduction, doppler nullification, directional audio。

cs和ncs临床试验判定标准

cs和ncs临床试验判定标准

cs和ncs临床试验判定标准随着生物医学科学的发展和临床研究的不断深入,CS和NCS临床试验的判定标准也日益完善。

CS试验代表了对某种药物或治疗方法的疗效进行评价,而NCS试验则主要评估不同治疗方法之间的差异。

本文将简要介绍CS和NCS临床试验的判定标准,并探讨其重要性和发展趋势。

CS临床试验是疗效判定的主要手段之一。

其主要目的是通过比较患者在接受治疗前后的病情变化,来评估治疗是否有效。

在进行CS临床试验时,通常需要确定一些评估指标,如病情缓解率、生存期延长和病情恶化时间等。

同时,还需要选择合适的对照组,以便进行比较。

在CS试验中,通常使用的判定标准有严格的标准化指南,如RECIST (疾病评价标准),用于判断疗效的大小。

此外,还需要考虑一些其他因素,如样本量、随机分组和盲法等。

与CS临床试验相比,NCS临床试验的判定标准更加复杂。

NCS试验通常将患者分为不同的治疗组,以评估不同治疗方法之间的差异。

对于NCS试验,判定疗效的指标也会相应改变。

常用的判定标准包括治疗效果分级、生存期和生活质量等。

此外,还需要考虑其他因素,如样本量、随机分组和盲法等。

CS和NCS临床试验的判定标准在临床研究中具有重要意义。

准确的判定标准可以使研究结果更加客观和科学,从而为患者提供更好的治疗方案。

然而,随着药物和治疗方法的不断创新,现有的判定标准也需要不断更新和完善。

因此,建立统一的判定标准和指南也变得尤为重要。

为了解决这个问题,许多国际组织和政府机构开始制定和发布相关的指南和标准。

例如,美国FDA(食品和药物管理局)制定了一系列评估新药疗效和安全性的指南,以指导临床试验的进行。

此外,世界卫生组织(WHO)也发布了一些关于临床试验判定标准的指南,以协助全球范围内的临床研究。

在未来,随着技术和医学的不断发展,CS和NCS临床试验的判定标准也将不断更新和改进。

例如,随着分子生物学和基因组学的进步,可能会引入更多的生物学指标来评估疗效。

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2 Enhanced Cell Reselection Mechanism for Heterogeneous Wireless System 2.1 Cell Reselection Mechanism in 3GPP TS 36.304
We first present cell reselection process defined in the latest technical specification (TS) [1] in 3GPP protocol in a mathematical manner. This protocol is essentially designed for 3GPP cellular wireless system. To provide more theoretical insight, we model the system in a general manner. Consider 4G LTE system and its evolution
Title Suppressed Due to Excessive Length
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scenario, where adjacent macro evolved node Bs(MeNBs) form wide-area coverage for UEs in each corresponding cell (macro cell), and low power nodes (LPNs) within each cell form hot-spot coverage. The criterion for UE to perform cell reselection is the value of reference signal power denoted by Pk , where k denotes the index of different types of nodes and cells. In real application scenarios, all overlapping RAT cells in the heterogeneous wireless system have the rank of priority, according to which UE will perform cell reselection to the specific cell when Pk meets certain thresholds requirements. Priority rank parameters are broadcasted to all UE by system information or dedicated signallings [1]. For UE that has camped on others cells adjacent to cell k, if Pk is large enough, the UE will try to reselect to cells k for better access service. Define Tkin as the threshold for Pk when UE tries to camp on cell k, above which UE will try to perform cell reselection to cell k. For UE already camped on cell k, if Pk is too small, it will try to reselect to other cells. Define Tkout as the threshold for Pk when UE tries to camp on other cells, below which UE will try to perform cell reselection to other cells. Assume UE currently camps on cell k, and try to perform cell reselection to other cells with different priority ranks. Let the cell with index h represent the cell with higher priority, and let the cell with index l represent the cell with lower priority. The algorithm for cell reselection is summarized as follows: • If Ph > Thin holds for a consecutive time treselection , UE shall perform cell reselection from cell k to cell h. • If Pl > Tlin and Pk < Tkout hold for a consecutive time treselection , UE shall perform cell reselection from cell k to cell l . If more than one cell meet the above requirements, UE shall perform cell reselection to the cell with highest priority.
Analysis for the Enhanced Cell Reselection Mechanism in Heterogeneous Wireless System
Xinran Zhang, Songlin Sun
Abstract This work proposes an enhanced algorithm for cell reselection mechanism in heterogeneous wireless system. A Markov model based analytical method is proposed to describe system behavior and derive performance metric. The optimal QoS control parameter for the algorithm is derived based on system model and analysed in numerical results. It is shown the network performance can be improved by utilizing the proposed algorithm, and the optimal value of QoS control parameter varies according to system traffic condition, which provides insight for network deployment and radio resource ll reselection process of user equipment (UE) is an important physical-layer process of cellular wireless communication system. It is defined and described in third generation partner project (3GPP) physical layer specifications [1, 2], and essentially specifies UE’s behavior to choose other access cells when the power or quality of the received signal varies. In tradition simple scenarios of cellular system like Global System for Mobile Communication (GSM) system or third generation (3G) Wideband Code Division Multiple Access (WCDMA) system, the radio access network (RAN) is constituted by the so-called macro cells, where the base station (BS) or node B (NB) serves as the access point for UEs in a wide coverage area. In that case the cell reselection behavior happens when UE moves through the edge of different cells and requires handoff to the cell with best access quality. This sXinran Zhang Beijing Univ. of Posts and Telecomm., No.10 Xitucheng Road, Beijing e-mail: zhangxr.wspn@ Songlin Sun Beijing Univ. of Posts and Telecomm., No.10 Xitucheng Road, Beijing e-mail: slsun@
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Xinran Zhang, Songlin Sun
cenario can be construed as homogeneous wireless system. With the emergence of fourth generation (4G)long term evolution (LTE) standard and its rapid deployment around the world, more complex network scenarios unlike traditional homogeneous wireless system are introduced and referred as the heterogeneous wireless systems. The concept of heterogeneity and its related theories have become heated research topics in the past decade. In the family of 3GPP cellular systems, the typical scenario of heterogeneous wireless system consists of GSM system, Enhanced Data Rate for GSM Evolution (EDGE) system, WCDMA system, LTE system, and even in the future, fifth generation (5G) system. Within theses systems, different nodes are involved such as pico nodes and femto nodes, along with macro nodes deployed in a overlapping manner. To make the scenario more complicated, the wireless local area network (WLAN) system are also considered in heterogeneous wireless system, since the convergence of different radio access technologies (RATs) is a fundamental aspect for 3GPP cellular system and an inevitable trend of future wireless communication system. These conditions provide a much more complicated scenario for UE mobility management problem, in which the cell reselection problem has already become an important technique applied in current cellular wireless systems as well as an interesting theoretical research point. In the field of mobility management and radio resource management (RRM) research, the Markov-related model is extensively studied and discussed in existing literatures [3] - [7] due to its accuracy, simplicity and validity, and is considered to be an ideal research methodology to model the cell reselection mechanism in heterogeneous wireless system. In this work we first present the proposed mechanism for cell reselection in heterogeneous wireless system defined in 3GPP specifications, then derived a Markov model based analytical method for the system to obtain system performance metric, then provide detailed analysis for optimal parameter in the algorithm. The paper is organized as follows: in Section 2 the cell reselection mechanism in [1] and the proposed algorithm is described. Then in Section 3 we present the mathematical model for the system, and derived the optimal parameter solutions to the model. Section 4 presents the main results for the optimal quality of service (QoS) parameter analysis. Section 5 concludes the paper.
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