3G认证和密钥分配协议的形式化分析及改进

介绍了第三代移动通信系统所采用的认证和密钥分配(AKA)协议,网络归属位置寄存器/访问位置寄存器(HLR/VLR)对用户UE(用户设备)的认证过程和用户UE对网络HLR/VLR的认证过程分别采用了两种不同的认证方式,前者采用基于"询问-应答"式的认证过程,后者采用基于"知识证明"式的认证过程.使用BAN形式化逻辑分析方法分别对这两种认证过程进行了分析,指出在假定HLR与VLR之间系统安全的前提下,基于"知识证明"式的认证过程仍然存在安全漏洞.3GPP采取基于顺序号的补充措施;同时,文中指出了另一种改进方案.     

Mesh结构P/G布线网络层次化快速分析方法

本文提出了一个基于网络划分的P／G布线网络层次化快速分析方法。其中，对于子网运算，通过对Cholesky分解法三角化对称正定阵的图模型分析，并基于Mesh结构网络的自身特点，提出了一个基于图顶点排序的加速子网分析运算策略；并用基于MPI的并行结构实现了P／G布线网络分析的并行运算。     

信道粒度可变的分块自适应OFDM传输系统

满足不同服务质量(QoS)业务是Beyond 3G系统必须考虑的一个问题。本文提出一种可变信道粒度的分块自适应OFDM系统。系统能够根据不同用户多样化的速率需求，自适应地改变分块的大小，并且在每个分块上进行自适应调制，在满足用户速率要求的基础上降低了对子载波分配信息(SAI)和自适应调制信息(AMI)的需求。仿真结果表明，本文提出的系统在系统容量和频谱效率上比固定分块自适应OFDM系统有更好的性能。     

Mesh-Tree两级层次结构P/G网布线优化方法

本文采用Mesh-Tree两级层次结构作为P／G网布线拓扑结构，并提出了一个对于该结构的线宽优化方法，使超大型P／G网的布线优化速度大大提高。     

国内3G网络共享问题之研究

随着国内3G时代的来临，3G网络共享问题越来越受到人们的关注。本文结合国内移动通信的现状，着重分析了3G网络共享的模式及经济效益，论述了3G网络共享的相应策略。     

ON THE PRODUCT OF GATEAUX DIFFERENTIABILITY LOCALLY CONVEX SPACES

A locally convex space is said to be a Gateaux differentiability space (GDS)provided every continuous convex function defined on a nonempty convex open subset D of the space is densely Gateaux differentiable in D.This paper shows that the product of a GDS and a family of separable Frechet spaces is a GDS,and that the product of a GDS and an arbitrary locally convex space endowed with the weak topology is a GDS.     

Crossover from high-temperature vortex-liquid to low-temperature vortex-glass behavior in single phase HgBa2Ca2Cu3O8+δ superconductor

The ρ-T curves in our single phase HgBa₂Ca₂Cu₃O_8+δ superconductor were measured as a function of temperature and magnetic field, ρ=ρ₀exp(−U_eff/κ_BT). It can be transformed to another form d(lnρ)/d(1/T)=−U_eff+TdU_eff/dT, then this becomes a plot of the activation energy U_eff as a function of temperature. Our data plotted in these ways show a clear crossover from high-temperature two-dimensional vortex-liquid to a critical region associated with the low-temperature three-dimensional vortex-glass phase transition. The critical exponents v(z−1)=3.9±1.9 in this system are little different with previous measurements in BSCCO and YBCO systems.     

Small angle neutron scattering from oxygen precipitates in silicon

The formation of silicon oxide precipitates from Czochralski grown silicon depends on the time and temperature of the heat treatment as well as on the initial content of interstitially dissolved oxygen. Samples containing between 5×10¹⁷ O_i/cm³ and 13×10¹⁷ O_i/cm³ have been heated at 750° C for 96 h. SiO₂ precipitates of various shape and size have been obtained and investigated by means of small angle neutron scattering (SANS) in the Q-range 0.05 Å^–1<Q<0.2 Å^–1. The obtained SANS patterns reveal a typical anisotropy of their intensity distribution, which splits into a central peak at Q<0.1 Å^–1 due to the shape of the individual particles and a number of weak intensities for large Q-values, originating from a correlation between defects, possibly between the precipitates. While these correlation peaks in the SANS patterns are seen best for rather low values of about (5–7)×10¹⁷ O_i/cm³ oxygen content, the central peak anisotropy is most pronounced for higher values of ca 10×10¹⁷ O_i/cm³. The integrated intensity of the central peak increases with increasing initial oxygen content. For comparison, untreated samples of the same initial oxygen content do not reveal any anisotropic SAN scattering or a broadened central peak beam.     

Properties of nonparametric estimators of autocovariance for stationary random fields

Summary We introduce nonparametric estimators of the autocovariance of a stationary random field. One of our estimators has the property that it is itself an autocovatiance. This feature enables the estimator to be used as the basis of simulation studies such as those which are necessary when constructing bootstrap confidence intervals for unknown parameters. Unlike estimators proposed recently by other authors, our own do not require assumptions such as isotropy or monotonicity. Indeed, like nonparametric function estimators considered more widely in the context of curve estimation, our approach demands only smoothness and tail conditions on the underlying curve or surface (here, the autocovariance), and moment and mixing conditions on the random field. We show that by imposing the condition that the estimator be a covariance function we actually reduce the numerical value of integrated squared error.