A high‐performance switch architecture based on mesh of trees

With emergence of various new Internet‐enabled devices, such as tablet PCs or smart phones along with their own applications, the traffic growth rate is getting faster and faster these days and demands more communication bandwidth at even faster rate than before. To accommodate this ever‐increasing network traffic, even faster Internet routers are required. To respond for these needs, we propose a new mesh of trees based switch architecture, called MOTS(N) switch. In addition, we also propose two more variations of MOTS(N) to further improve it. MOTS(N) is inspired by crossbar with crosspoint buffers. It forms a binary tree for each output line, where each gridpoint buffer ? ? Because the fabric of MOTS(N) switch is not pure crossbar, we call the buffers in the same location in pure crossbar gridpoint buffers. Details will be presented in the following sections.
is a leaf node and each internal node is 2‐in 1‐out merge buffer § § 2‐in 1‐out merge buffer can accommodate two memory writes and one memory read simultaneously by using its modularized architecture 31 .
emulating FIFO queues. Because of this FIFO characteristic of internal buffers, MOTS(N) ensures QoS like FIFO output‐queued switch. The root node of the tree for each output line is the only component connected to the output port where each cell is transmitted to output port without any contention. To limit the number of buffers in MOTS(N) switch, we present one of its improved (practical) variations, IMOTS(N) switch, as well. For IMOTS(N) switch architecture, sizes of the buffers in the fabric are limited by a certain amount. As a downside of IMOTS(N), however, every cell should go through log ₂N + 1 number of buffers in the fabric to be transmitted to the designated output line. Therefore, for even further improvement, IMOTS(N) with cut‐through, denoted as IMOTS‐CT(N), is also proposed in this paper. In IMOTS‐CT(N) switch, the cells can cut through one or more empty buffers to be transferred from inputs to outputs with simple 1 or 2 bit signal exchanges between buffers. We analyze the throughput of MOTS(N), IMOTS(N), and IMOTS‐CT(N) switches and show that they can achieve 100% throughput under Bernoulli independent and identically distributed uniform traffic. Our quantitative simulation results validate the theoretical analysis. Copyright © 2012 John Wiley & Sons, Ltd.     

A LUT-based scheme for LNA linearization in direct RF sampling receivers

Direct RF sampling receiver – a fully digital receiver architecture – undoubtedly becomes a favored choice for HF/VHF as this approach inherently bypasses the legacy nonlinearities caused by analog components. In DRF-RF and wideband multichannel in general, LNA is still an indispensable component to ensure the receiver’s sensitivity. However, with the presence of multiple channels, the total RF power often surpasses the linear threshold that LNA and the amplified signal become severely distorted. This paper proposed a method for mitigating the LNA distortion using the look-up table (LUT) approach. Specifically, our receiver is designed with two modes of operation. In training mode, a built-in signal circuit generates a training signal for extracting the LNA characteristic and eventually reconstructs the inverse LNA nonlinear model in the form of a LUT memory. During the receiving mode, a linearization circuit reverses the distortion impact by matching the RF power level with the inverse nonlinear model pre-stored in the LUT. The effectiveness of the proposed distortion compensation method first is evaluated by a MATLAB simulation with a multi-channel DRF-RF model. The simulation results show that the proposed approach significantly improved the SNDR for the channel of interest. Furthermore, the model has been practically verified, where the actual distorted signals are sampled from a commercial LNA (ZFL-500LN+) by a customized FPGA board. Results from measurements show an improvement of $\sim$7 dB for SNDR and 27% for EVM in a strong distortion scenario of QPSK modulation signal.     

毫米波射频互连微组装工艺优化研究

在毫米波产品的装配中,射频互连微组装工艺是影响产品性能的一个重要因素。采用三维电磁仿真软件对毫米波频段的组装缝隙宽度、金丝热超声楔焊跨距及拱高进行了建模仿真,分析了上述因素对驻波的影响。针对模拟仿真优化结果,给出了毫米波射频互连装配精度控制、接地焊接效果优化、金丝热超声楔焊线型及键合参数优化等相应的工艺优化措施,从而达到毫米波射频互连微组装工艺优化的目的。     

FPGA的静态功耗分析与降低技术

FPGA已经被广泛用于实现大规模的数字电路和系统,随着CMOS工艺发展到深亚微米,芯片的静态功耗已成为关键挑战之一。文章首先对FPGA的结构和静态功耗在FPGA中的分布进行了介绍。接下来提出了晶体管的漏电流模型,并且重点对FPGA中漏电流单元亚阈值漏电流和栅漏电流进行了详细的分析。最后根据FPGA的特点采用双阈值电压晶体管,关键路径上的晶体管采用低阈值电压栅的晶体管,非关键路径上的晶体管采用高阈值电压栅的晶体管,以此来降低芯片的静态功耗。     

中性线的转换对UPS性能的影响和对策

由于低压配电系统接地故障保护（GFP）的需要,市电与备用发电机组电源转换电路必须采用4极自动转换开关（ATS）,而有些4极ATS在转换过程中存在中性线中断现象,严重影响了UPS的正常运行,由此引发的UPS故障和负载停电事件越来越受到关注。文中分析电信和数据中心常用市电和备用发电机组电源转换电路的性能及其对GFP和UPS运行的影响,提出工程实用解决方案。     

衬底负偏压及溅射功率对SiO_2/Cu薄膜形貌的影响

采用射频磁控溅射镀膜技术,分别以不同的衬底负偏压和射频溅射功率下在p型Si(100)基片上制备了SiO2/Cu薄膜。用原子力显微镜(AFM)对薄膜的表面形貌进行扫描分析,实验结果表明,衬底负偏压和射频溅射功率对SiO2/Cu薄膜的表面形貌都有显著的影响。衬底负偏压在0～15 V内,薄膜表面颗粒尺寸和均方根粗糙度都随着衬底负偏压的增大呈减小的趋势,而溅射功率在100～200 W内,薄膜表面颗粒尺寸和均方根粗糙度都随溅射功率的升高呈增大的趋势。成膜初期是层状生长模式,后期为岛状生长模式,整个成膜过程是典型的层岛生长模式。     

MIMO雷达射频隐身性能的评估

电子干扰、反辐射导弹的现实威胁使射频隐身性能成军用雷达关键的指标之一,评估雷达的隐身能力因此也越来越重要。针对MIMO新体制雷达的射频隐身性能评估问题展开研究,详细描述了敌方电子侦察设备截获雷达信号的过程,分析时域、空域、频域对准和功率影响截获概率的若干重要因素,结合传统意义上的抗截获性能评估方法,提出了一种计算MIMO雷达截获概率的模型。仿真分析和对比了各个因素对截获概率的影响,验证了这一模型的实用性和有效性。     

基于Zigbee和电容触控技术的灯光控制开关设计

为了满足家居智能化和网络化的发展需求,提出了一种基于Zigbee和电容触控技术的灯光控制器的设计方案,并完成了系统设计。重点描述了系统的电源驱动电路、触摸感应电路以及CC2530片上系统的实现。实际应用表明,该系统具有安全可靠、操控精准、组网方便的特点,达到了设计要求。     

基于射频识别物联网电磁场原理的研究

为了了解物联网应用拓展,探索RFID(射频识别技术)技术,文章从理论上对射频识别技术电磁场原理进行了探讨,从天线的电流模型出发,通过理论推导得出电磁量的计算公式,该公式对物联网具体的技术应用有一定的理论指导作用,对射频信号自动识别目标对象并获取相关数据,起到理论支撑作用。     

土壤水分去除算法的田间原位光谱反演棉田有机质

田间原位可见-近红外光谱(VIS-NIR)能够有效的提高土壤属性的检测效率,但由于原位土壤中水分因素的影响,土壤属性的预测精度很难达到预期。如何有效去除土壤中的水分对土壤其他属性光谱预测的影响,是利用田间原位光谱高精度预测土壤属性所面临的难题,也是土壤光谱技术由室内转向田间的突破口。该问题的有效解决,可减除土壤样品的采集与室内预处理等过程,实现土壤属性的田间原位光谱测定。以新疆南部地区阿拉尔垦区十二团棉田为研究区,采用网格采样法共采集了116个0～20 cm深度的表层土壤样品,剔除1个异常值样品,得到115个有用样品,利用SR-3500型便携式地物光谱仪采集了231个样点的田间原位光谱数据,土样经风干、研磨和过筛等处理后测定其室内光谱和有机质含量。利用Kennard-Stone算法将115个土样分为69个转换子集及46个预测集,采用外部参数正交化法(EPO)、光谱直接转换法(DS)及光谱间接转换法(PDS)三种去除水分算法结合原位光谱反射率(R)、反射率一阶微分(R′)、反射率对数(LOG(R))以及反射率倒数(1/R)四种数学变换方式,运用随机森林(RF)模型进行不同组合模型的构建及精度评价。结果表明：(1)土壤有机质含量越高,土壤光谱反射率越低。土壤田间原位光谱反射率低于土壤室内光谱反射率;(2)室内光谱反射率与土壤有机质含量之间的相关性大于田间原位光谱,室内光谱经一阶微分变换后与土壤有机质含量之间的相关性显著提升。(3)土壤室内光谱反射率模型预测精度(R2=0.86, RPD=2.08, RMSE=1.55 g·kg-1, MAPE= 0.14)高于田间原位光谱反射率模型(R2=0.71, RPD=1.49, RMSE=2.17 g·kg-1, MAPE=0.20)。在去除水分算法模型中,以EPO一阶微分模型去除水分效果最好,决定系数R2由0.71提高到0.83,RPD由1.49提高到2.04,RMSE由2.17 g·kg-1降低至1.58 g·kg-1,MAPE由0.20降低至0.14。本研究实现了去除土壤水分因素的影响,提高了田间原位光谱预测土壤有机质的精度,为南疆棉田大尺度土壤有机质的预测及土壤肥力的评价提供了重要的参考。