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81.
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. 相似文献
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Jinman Kim Weidong Cai Dagan Feng Hao Wu 《IEEE transactions on information technology in biomedicine》2006,10(3):598-607
The advances in digital medical imaging and storage in integrated databases are resulting in growing demands for efficient image retrieval and management. Content-based image retrieval (CBIR) refers to the retrieval of images from a database, using the visual features derived from the information in the image, and has become an attractive approach to managing large medical image archives. In conventional CBIR systems for medical images, images are often segmented into regions which are used to derive two-dimensional visual features for region-based queries. Although such approach has the advantage of including only relevant regions in the formulation of a query, medical images that are inherently multidimensional can potentially benefit from the multidimensional feature extraction which could open up new opportunities in visual feature extraction and retrieval. In this study, we present a volume of interest (VOI) based content-based retrieval of four-dimensional (three spatial and one temporal) dynamic PET images. By segmenting the images into VOIs consisting of functionally similar voxels (e.g., a tumor structure), multidimensional visual and functional features were extracted and used as region-based query features. A prototype VOI-based functional image retrieval system (VOI-FIRS) has been designed to demonstrate the proposed multidimensional feature extraction and retrieval. Experimental results show that the proposed system allows for the retrieval of related images that constitute similar visual and functional VOI features, and can find potential applications in medical data management, such as to aid in education, diagnosis, and statistical analysis. 相似文献
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85.
磷酸酯类离子液体在燃油深度脱硫中的应用 总被引:16,自引:6,他引:10
研究了3种磷酸酯类离子液体,即1,3-二甲基咪唑磷酸二甲酯盐([MM im]DM P)、1-乙基-3-甲基咪唑磷酸二乙酯盐([EM im]DEP)和1-丁基-3-甲基咪唑磷酸二丁酯盐([BM im]DBP)的制备过程,考察了这3种磷酸酯类离子液体对模型油中3-甲基噻吩、苯并噻吩和二苯并噻吩的脱除效果及磷酸酯类离子液体的电化学再生方法。实验结果表明,这3种磷酸酯类离子液体的脱硫能力强弱顺序为:[EM im]DEP>[BM im]DBP[MM im]DM P;且对二苯并噻吩的脱除效果最好,对苯并噻吩的脱除效果次之,对3-甲基噻吩的脱除效果较差。以[EM im]DEP为萃取剂,油剂质量比为1∶1时,经5次萃取后,二苯并噻吩的脱除率可达到99.5%。利用电解法对[EM im]DEP进行了再生,在5~10V电压下电解10h,[EM im]DEP的脱硫率可以达到新鲜[EM im]DEP的90%以上。 相似文献
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89.
可验证秘密分享在实用密码学领域内是一个非常重要的工具,它在密钥管理协议、门限或分布式签名协议、电子商务、多方安全计算及团体式密码系统等许多方面都有极为广泛的应用。针对一类突发事务须及时、安全解决的特点, 利用离散对数问题的难解性,在假设初始化阶段和秘密恢复阶段始终有一位值得信赖的分发者参与的情况下,提出了一个可公开验证的门限秘密分享方案。 相似文献
90.