X-band circularly polarized rectennas for microwave power transmission applications

Circularly polarized rectennas operating at X-band are studied in this paper. The quasi-square patches fed by aperture coupling are used as the circularly polarized receiving antennas, which are easily matched and integrated with the circuits of rectennas. The： double-layer structure not only minimizes the size of the rectennas but also decreases the effects of the circuits on the antenna. The receiving elements have broader bandwidth and higher gain than the single-layer patches. Two rectennas operating at 10GHz are designed, fabricated and measured. The voltage of 3.86V on a load of 200Ω is measured and a high RF-DC conversion efficiency of 75% is obtained at 9.98GHz. It is convenient for this kind of rectennas to form large arrays for high power applications.     

IMS域策略与计费控制接口的平滑演进

为了提供更好的基于流的计费和策略控制,3GPP在IMSR7版本中提出策略与计费控制体系架构,其基本思路是将IMSR6版本中的策略决策功能实体和计费策略功能实体合并为R7中的策略与计费规则功能实体。本文首先简要介绍了IMSR6和IMSR7控制模型;然后重点分析了与策略控制、计费控制相关Gx接口、Rx接口的接口消息及其参数。分析表明,通过定义特定AVP,实现了IMSR6向IMSR7策略控制和计费控制接口的平滑演进。     

诺基亚西门子通信GPRS网络容量分析体系的研究

本文通过对中国移动通信集团新疆有限公司的GPRS网络结构及容量需求分析入手,提出了容量备份方案,有效解决了业务发展带来的容量不足问题,并且通过网络结构的调整,使得GPRS网络更加安全可靠,大幅度提升了网络的健壮性,为业务高效稳定的发展奠定了基础。     

S频段锁相频率合成器的设计

介绍了小数式锁相频率合成器的设计方法及相关理论,分析了影响锁相环相位噪声的主要因素并设计了环路滤波器和Wilkinson功率分配器。由实验结果可知,小数式锁相频率合成器具有很好的相位噪声和较高的频率分辨率。     

基于差分空时调制的混沌慢跳频系统

提出一种慢跳频系统中基于差分空时调制的混沌保密通信方法。此方案集成了差分空时编码和混沌跳频扩频技术的优点。一方面,在跳频系统中,使用混沌序列代替伪随机(PN)码,增强了抗截获和抗预测的性能;另一方面,通过差分空时调制产生分集增益,降低了多径衰落效应的影响。仿真结果证实了此方案的有效性。     

Luminescence interference-free lifetime nanothermometry pinpoints in vivo temperature

Luminescence nanothermometry makes non-invasive and real-time temperature readings possible in living animals. However,the spectral fluctuation in tissues and fluids, as well as the interaction between fluorophores and environment hinders accuracy of the thermometry. Here, we report a luminescence lifetime-based nanothermometry which specifically addresses this problem. A temporal based calibration(lifetime sensing) in the NIR range, an endogenous thermal response as well as a polymer encapsulation evading environmental factors, altogether help to pinpoint temperature in vivo. Thanks to the highly condensed NdYb ions in a well-protected tiny core-shell nanocrystal(overall 11 nm), a temperature sensitivity about 2.07% K~(-1)(with 5% Yb~(3+) doped nanoparticles) and an accuracy of 0.27 K(with 25% Yb~(3+) doped nanoparticles) in biological fluids are achieved.Hopefully, combining thermally activated energy transfer nanothermometer with anti-interference lifetime thermometry would provide a more accurate temperature measurement for biological and preclinical studies.     

基于簇的寄存器堆功耗管理方法

本文采用软硬件协同设计技术,提出以寄存器簇为粒度对嵌入式处理器寄存器堆进行功耗管理的方法.在软件方面,面向寄存器簇的编译优化使循环程序段中寄存器的编号尽可能相邻;在硬件方面,采用寄存器簇缓冲器过滤对寄存器堆的访问并降低其动态功耗,采用基于寄存器簇的动态电压调节电路和门控预充电路降低存储单元和位线的泄漏功耗.实验结果表明,本文方法将寄存器堆的总功耗降低约44.7%,比传统方法达到了功耗、面积和延迟的更优折衷.     

Load Balancing Routing Algorithm Based on Extended Link States in LEO Constellation Network

As an important part of satellite communication network, LEO satellite constellation network is one of the hot research directions. Since the nonuniform distribution of terrestrial services may cause inter-satellite link congestion, improving network load balancing performance has become one of the key issues that need to be solved for routing algorithms in LEO network. Therefore, by expanding the range of available paths and combining the congestion avoidance mechanism, a load balancing routing...     

MPEG-2/4 AAC 音频编码器实时性能优化研究进展

目前,MPEG-2/4 AAC已成为广泛使用的一种音频编码压缩标准,但是MPEG-2/4 AAC标准的音频编码器存在算法复杂度高、计算量和时闻延迟大等缺点,无法满足实时性要求.从MPEG-2/4 AAC音频编码器的内部结构入手,分析了制约其实时性能的主要环节,就心理声学模型、滤波器组、量化与编码模块3个部分,归纳了当前MPEG-2/4 AAC实时音频编码器实现与优化研究的相关内容和进展,给出了若干算法的主要思想、改进结果和优缺点.在此基础上,提出了进一步优化MPEG-2/4 AAC实时性能的研究方向,以及需要解决的主要问题.     

Domain Adaptation with Data Uncertainty Measure Based on Evidence Theory

Domain adaptation aims to learn a classifier for a target domain task by using related labeled data from the source domain. Because source domain data and target domain task may be mismatched, there is an uncertainty of source domain data with respect to the target domain task. Ignoring the uncertainty may lead to models with unreliable and suboptimal classification results for the target domain task. However, most previous works focus on reducing the gap in data distribution between the source and target domains. They do not consider the uncertainty of source domain data about the target domain task and cannot apply the uncertainty to learn an adaptive classifier. Aimed at this problem, we revisit the domain adaptation from source domain data uncertainty based on evidence theory and thereby devise an adaptive classifier with the uncertainty measure. Based on evidence theory, we first design an evidence net to estimate the uncertainty of source domain data about the target domain task. Second, we design a general loss function with the uncertainty measure for the adaptive classifier and extend the loss function to support vector machine. Finally, numerical experiments on simulation datasets and real-world applications are given to comprehensively demonstrate the effectiveness of the adaptive classifier with the uncertainty measure.