Distributed wireless power transfer in sensor networks with multiple Mobile Chargers

We investigate the problem of efficient wireless power transfer in wireless sensor networks. In our approach, special mobile entities (called the Mobile Chargers) traverse the network and wirelessly replenish the energy of sensor nodes. In contrast to most current approaches, we envision methods that are distributed and use limited network information. We propose four new protocols for efficient charging, addressing key issues which we identify, most notably (i) what are good coordination procedures for the Mobile Chargers and (ii) what are good trajectories for the Mobile Chargers. Two of our protocols (DC, DCLK) perform distributed, limited network knowledge coordination and charging, while two others (CC, CCGK) perform centralized, global network knowledge coordination and charging. As detailed simulations demonstrate, one of our distributed protocols outperforms a known state of the art method, while its performance gets quite close to the performance of the powerful centralized global knowledge method.     

Artificial bee colony based algorithm for maximum power point tracking (MPPT) for PV systems operating under partial shaded conditions

Artificial bee colony (ABC) algorithm has several characteristics that make it more attractive than other bio-inspired methods. Particularly, it is simple, it uses fewer control parameters and its convergence is independent of the initial conditions. In this paper, a novel artificial bee colony based maximum power point tracking algorithm (MPPT) is proposed. The developed algorithm, does not allow only overcoming the common drawback of the conventional MPPT methods, but it gives a simple and a robust MPPT scheme. A co-simulation methodology, combining Matlab/Simulink™ and Cadence/Pspice™, is used to verify the effectiveness of the proposed method and compare its performance, under dynamic weather conditions, with that of the Particle Swarm Optimization (PSO) based MPPT algorithm. Moreover, a laboratory setup has been realized and used to experimentally validate the proposed ABC-based MPPT algorithm. Simulation and experimental results have shown the satisfactory performance of the proposed approach.     

LTE系统多小区上行联合功控算法

针对传统的小区内开环功率控制算法通常以提升本小区的吞吐量性能为目标，忽略了当前小区用户对邻小区用户同频干扰的问题，为提升边缘用户性能的同时兼顾系统整体性能，提出了一种LTE系统小区间上行联合功率控制（UJPC）算法。该算法采用单基站三扇区为系统模型，以最优化系统吞吐量比例公平函数为目标，首先根据最小信干噪比（SINR）约束值和用户最大发射功率这两个约束条件得到相应的数学优化模型，然后采用连续凸近似的方法求解优化问题得出各个基站所管辖的小区内所有用户的最优发射功率。仿真结果表明，与基准的开环功控方案相比，联合功控方案在保证系统平均频谱利用率的情况下能够较大幅度地提高小区边缘频谱利用率，其最佳性能增益能达到50%。     

多带OFDM-UWB系统峰均功率比降低方法研究

针对多带OFDM—UWB信号存在高峰均功率比的问题，提出了利用扩展与交织降低系统信号峰均功率比的方法。该方法通过对传输数据进行正交扩展与交织，使得进入多载波调制的数据趋于高斯分布，减小了传输数据自相关函数的旁瓣峰值，降低了OFDM-UWB信号的峰均功率比。由于采用正交矩阵进行扩展，扩展前后的数据传输速率保持不变。仿真结果表明，扩展与交织可以有效地降低信号峰均功率比2-5dB左右。同时该方法还具有抗窄带干扰的鲁棒性。     

掺镱双包层高功率光纤激光器输出特性研究

对线形腔掺镱双包层高功率光纤激光器的输出特性进行了研究 ,通过求解速率方程 ,得到了激光器泵浦阈值功率、输出光功率和斜率效率的表达式。分析了光纤长度、腔镜反射率和泵浦波长等因素对激光器阈值功率、输出光功率和斜率效率的影响 ,为高功率光纤激光器的优化设计提供了理论依据     

Handover and Uplink Power Control Performance in the 3.84 Mcps TDD mode of UTRA Network

In this article we consider the performance of the 3.84 Mcpstime-division duplex (TDD) mode of UTRA (Universal TerrestrialRadio Access) network. We emphasize two of the radio resourcemanagement algorithms, handover and uplink power control, whoserole in the overall system performance is studied extensively.First, a handover algorithm used in WCDMA (Wideband Code DivisionMultiple Access) standard is considered in a TDD-mode operation.This gives rise to a careful setting of different handoverparameters, and the evaluation of the effects to the systemperformance. Secondly, the specified uplink power controlalgorithm is considered. Since it is based on several user-mademeasurements which may involve both random and systematic errors acareful study about the suitability of the power control scheme iscarried out.     

移动通信系统中功率控制研究

在阐述功率控制在移动通信系统中的发展过程的基础上，着重研究了WCDMA系统的功率控制，最后对功率控制未来的研究方向做了简要的分析。     

Range Assignment for Biconnectivity and k-Edge Connectivity in Wireless Ad Hoc Networks

Depending on whether bidirectional links or unidirectional links are used for communications, the network topology under a given range assignment is either an undirected graph referred to as the bidirectional topology, or a directed graph referred to as the unidirectional topology. The Min-Power Bidirectional (resp., Unidirectional) k-Node Connectivity problem seeks a range assignment of minimum total power subject to the constraint that the produced bidirectional (resp. unidirectional) topology is k-vertex connected. Similarly, the Min-Power Bidirectional (resp., Unidirectional) k-Edge Connectivity problem seeks a range assignment of minimum total power subject to the constraint the produced bidirectional (resp., unidirectional) topology is k-edge connected. The Min-Power Bidirectional Biconnectivity problem and the Min-Power Bidirectional Edge-Biconnectivity problem have been studied by Lloyd et al. [23]. They show that range assignment based the approximation algorithm of Khuller and Raghavachari [18], which we refer to as Algorithm KR, has an approximation ratio of at most 2(2 – 2/n)(2 + 1/n) for Min-Power Bidirectional Biconnectivity, and range assignment based on the approximation algorithm of Khuller and Vishkin [19], which we refer to as Algorithm KV, has an approximation ratio of at most 8(1 – 1/n) for Min-Power Bidirectional Edge-Biconnectivity. In this paper, we first establish the NP-hardness of Min-Power Bidirectional (Edge-) Biconnectivity. Then we show that Algorithm KR has an approximation ratio of at most 4 for both Min-Power Bidirectional Biconnectivity and Min-Power Unidirectional Biconnectivity, and Algorithm KV has an approximation ratio of at most 2k for both Min-Power Bidirectional k-Edge Connectivity and Min-Power Unidirectional k-Edge Connectivity. We also propose a new simple constant-approximation algorithm for both Min-Power Bidirectional Biconnectivity and Min-Power Unidirectional Biconnectivity. This new algorithm applies only to Euclidean instances, but is best suited for distributed implementation. A preliminary version of this work appeared in the proceedings of the 2nd International Conference on AD-HOC Network and Wireless (Adhoc-Now 2003). Research performed in part while visiting the Max-Plank-Institut fur Informatik. Gruia Calinescu is an Assistant Professor of Computer Science at the Illinois Institute of Technology since 2000. He held postdoc or visiting researcher positions at DIMACS, University of Waterloo, and Max-Plank Institut fur Informatik. Gruia has a Diploma from University of Bucharest and a Ph.D. from Georgia Insitute of Technology. His research interests are in the area of algorithms. Peng-Jun Wan has joined the Computer Science Department at Illinois Institute of Technology in 1997 and has been an Associate Professor since 2004. He received his Ph.D. in Computer Science from University of Minnesota in 1997, M.S. in Operations Research and Control Theory from Chinese Academy of Science in 1993, and B.S. in Applied Mathematics from Tsinghua University in 1990. His research interests include optical networks and wireless networks.     

动力环境集中监控系统可靠性的提高

为实现电源设备乃至通信机房的少人或无人值守和集中维护,必须建立一套完善的电信局动力环境集中监控系统。文中结合番禺区电信局的实际,讨论了提高系统运行可靠性的几点措施,包括硬件方面与软件方面的手段,关键在于加强系统的运行管理。     

游梁式抽油机间歇供电装置的研制与应用

针对游梁抽油机电动机效率低和井场窃电问题,研制了具有节电和防井场窃电功能的游梁抽油机调压+间歇供电装置。该装置通过控制可控硅的导通角实现在电动机做功期调压供电,在电动机发电期不供电。分析了间歇供电对电动机、抽油机和电网的影响;根据现场实测数据分析了该装置的节电效果及现场应用情况。该装置节电效果显著,能防止井场窃电,可用于对游梁抽油机电动机的长期驱动。