Uplink Scheduling in CDMA Packet-Data Systems

Uplink scheduling in wireless systems is gaining importance due to arising uplink intensive data services (ftp, image uploads etc.), which could be hampered by the currently in-built asymmetry in favor of the downlink. In this work, we propose and study algorithms for efficient uplink packet-data scheduling in a CDMA cell. The algorithms attempt to maximize system throughput under transmit power limitations on the mobiles assuming instantaneous knowledge of user queues and channels. However no channel statistics or traffic characterization is necessary. Apart from increasing throughput, the algorithms also improve fairness of service among users, hence reducing chances of buffer overflows for poorly located users. The major observation arising from our analysis is that it is advantageous on the uplink to schedule “strong” users one-at-a-time, and “weak” users in larger groups. This contrasts with the downlink where one-at-a-time transmission for all users has shown to be the preferred mode in much previous work. Based on the optimal schedules, we propose less complex and more practical approximate methods, both of which offer significant performance improvement compared to one-at-a-time transmission, and the widely acclaimed Proportional Fair (PF) algorithm, in simulations. When queue content cannot be fed back, we propose a simple modification of PF, Uplink PF (UPF), that offers similar improvement. Hereafter, we refer to users with low recieved power at the base even when transmitting at peak transmit power as “weak” users, and the strongly recieved users at the base as “strong” users. Krishnan Kumaran is currently a member of the Complex Systems Modeling section in the Corporate Strategic Research of ExxonMobil Corp., Clinton, NJ. Formerly, he was a Member of Technical Staff in the Mathematics of Networks and Systems Research Department at Bell Labs in Murray Hill, NJ, where his research interests were in modeling, analysis and simulation of design, resource management and scheduling issues in telecommunication networks. Lijun Qian is an assistant professor in the Department of Electrical Engineering at Prairie View A&M University. He received his B.S. from Tsinghua University in Beijing, M.S. from Technion-Israel Institute of Technology, and Ph.D. from WINLAB, Rutgers University, all in electrical engineering. Before joining PVAMU, he was a researcher at Networks and Systems Research Department of Bell Labs in Murray Hill, NJ. His major research interests are in wireless communications and networking technologies, especially in radio resource management, protocol design, TCP/RLP optimization and MPLS traffic engineering.     

龙潭水电站励磁装置可控硅易损原因及改进措施

通过龙潭水电站对励磁装置可控硅元件实施过电压保护改进前后实际效果的分析,介绍了一种有效的过压保护方式.     

小波变换在光谱特征提取方面的应用

人们在处理高光谱图像时一般要对一些典型地物进行光谱分析、特征波段的提取,以便提取出最大量的有效信息,剔除无用或冗余的信息,然后再进行分类识别.采用小波变换的分析方法,选用合适的小波进行分解,根据分解后的高频分量中包含的重要信息,利用局部相邻的正负极值点找出对应于原始光谱曲线上每个吸收带的左右边界;利用局部过零点,即可比较精确的提取出各个吸收带的中心波长.该方法比传统的光谱特征提取方法更简洁、有效,实验证明为一种比较理想的光谱特征提取方法.     

高功率脉冲水中放电的应用及其发展

首先介绍了高功率脉冲水下放电的机理，然后综合论述了其应用和研究的状况，从较为成熟的脉冲水处理技术到医疗领域的ESWL应用技术，以及在脉冲电场食品杀菌和水下目标探测方面的最新发展和研究，最后指出了高功率脉冲电技术应用前景以及进行更系统和深入研究的必要性。     

结构化编程实现Sniffer

随着各高校校园网络规模的不断扩大和各种应用的急剧增加,各种新的网络问题也在不断出现。Sniffer是网络管理员进行网络管理的有效工具,可以有效地对网络进行实时监控,及时发现网络中存在的各种问题。本文首先介绍了Sniffer的工作原理,其次给出了实现Sniffer功能的编程流程图,并用C语言给出了编程所需的关键代码。     

浅谈如何有效学习计算机软件知识

计算机软件知识的学习并不是完全线性的，而是不断循环往复、迭代的过程。本对如何深入、广泛、有效地学习计算机软件知识做出了一些探讨。     

扩声系统在体育馆中的典型应用

针对体育馆举办不同类型的大型活动,分别对扩声系统的音质及扩声特点提出要求,以人声和乐器声的频率特性为依据,阐述了调音师在不同场合中对于不同的扩声对象按所要达到的扩声效果应采取的调控方法。     

数字电视用户管理系统

课题实现了数字电视用户管理系统的设计与开发,以Oracle数据库作为后台数据库,以C Builder 6作为前台开发工具,包括表的设计与界面的设计.实现了数字电视用户管理系统基本功能,基本上满足了实际商业运营的需要.     

Water sorption of glycol-modified cross-linked gelatin-based hydrogels

The water sorption behaviour of several cross-linked gelatin-based systems were investigated and compared. The systems were gelatin, gelatin/ethyleneglycol, gelatin/polyoxypropylenediamine, and gelatin/polyethylene oxide. For all the systems, an increased water gain was obtained by raising the concentration of the second component, while the swelling was reduced by an increase of the cross-linking density. This revised version was published online in November 2006 with corrections to the Cover Date.     

基于信息的智能控制理论研究

本文介绍的基于信息的智能控制理论的发展过程，主要分为智能控制的信息指标和智能控制的信息结构分析两部分，文中在最后对这套理论可能的发展方向进行了探讨。