Multilevel Power Modeling of Base Station and Its ICs

A new power estimation method is proposed for base station(BS) in this paper.Based on this method,a software platform for power estimation is developed.The proposed method models power consumption on different abstraction levels by splitting a typical base station into several basic components at different levels in the view of embedded system design.In particular,our focus is on baseband IC(Integrate Circuit) due to it's the dominant power consumer in small cells.Baseband power model is based on arithmetic computing costs of selected algorithms.All computing and storage costs are calibrated using algorithm complexity,hardware architecture,activity ratio,silicon technology,and overheads on all hierarchies.Micro architecture and IC technology are considered.The model enables power comparison of different types of base stations configured with different baseband algorithms,micro architectures,and ICs.The model also supports cellular operators in power estimation of different deployment strategies and transmission schemes.The model is verified by comparing power consumption with a real LTE base station.By exposing more configuration freedoms,the platform can be used for power estimation of current and future base stations.

3D Model Retrieval Method Based on Affinity Propagation Clustering

In order to improve the accuracy and efficiency of 3D model retrieval,the method based on affinity propagation clustering algorithm is proposed. Firstly,projection ray-based method is proposed to improve the feature extraction efficiency of 3D models. Based on the relationship between model and its projection,the intersection in 3D space is transformed into intersection in 2D space,which reduces the number of intersection and improves the efficiency of the extraction algorithm. In feature extraction,multi-layer spheres method is analyzed. The two-layer spheres method makes the feature vector more accurate and improves retrieval precision. Secondly,Semi-supervised Affinity Propagation ( S-AP) clustering is utilized because it can be applied to different cluster structures. The S-AP algorithm is adopted to find the center models and then the center model collection is built. During retrieval process,the collection is utilized to classify the query model into corresponding model base and then the most similar model is retrieved in the model base. Finally,75 sample models from Princeton library are selected to do the experiment and then 36 models are used for retrieval test. The results validate that the proposed method outperforms the original method and the retrieval precision and recall ratios are improved effectively.

Dynamic 3-D Indoor Radio Propagation Model and Applications with Radios from 433 MHZ to 2.4 GHz

Proliferation of indoor sensor infrastructure has created a new niche for mobile communications, yet research in indoor radio propagation still has not generated a definite model that is able to 1) precisely capture radio signatures in 3-D environments and 2) effectively apply to radios at a wide range of frequency bands. This paper first introduces the impact of wall obstructions on indoor radio propagation by experimental results through a full cycle of an indoor construction process;it then exploits a dynamic 3-D indoor radio propagation model in a two-story building using radio technologies at both 433 MHz and 2.4 GHz. Experimental measurements and evaluation results show that the proposed 3-D model generates accurate signal strength values at all data evaluation positions. Comparing the two radio technologies, this study also indicates that low frequency radios (such as 433 MHz) might not be attractive for indoor mobile computing applications because of larger experimental errors or constant absence of measurement data.

Train crossing modeling based on measurements and best numerical approximation in subway tunnels

Communication based train control systems （CBTC） must work even in the worst situation-- train crossing. This paper models the propagation characteristics in one of the most common and piv- otal scenarios--train crossing in subway tunnels which is rarely mentioned in previous publications. Firstly, measurements for train crossing scenario at 2.4 GHz in a real subway line in Madrid have been made. The field measurement is the most reliable way to reveal the propagation characteristics involving shadowing effect and fast fading. Moreover, to precisely describe the fast fading distribu- tion and eliminate the inevitable weak points of traditional fitting way, a best numerical approxima- tion method using Legendre orthogonal polynomials has been proposed. Comparisons show that this method works better and is of greater physical significance. Finally, a complete statistical model is given and all the coefficients can be applied by system designers for the link and system level simu- lations.

A novel 3-D spatial temporal channel model for high mobility HAPS-based communications scenario

A high altitude platform station （HAPS） based communications scenario for providing Intemet access and broadband multimedia services to the passengers on board of a high speed train （traveling up to 300km/h） is proposed. Regarding the addressed scenario, when the propagation link between HAPS and train is blocked by obstacles, a three-dimensional （3-D） geometrical single cylinder spatial-temporal channel model is presented, in which closed form, mathematically tractable space-time correlation functions are obtained. It shows that the correlation functions determined by the 3-D model are of significant difference with those of the conventional 2-D model. Based on the analysis model, the paper derives a realized simulation model using sum-of-sinusoids approach, and applies method of equal areas （MEA） and modified method of equal areas （MMEA） to determine the model parameters. The fitting performance of the simulation model with the analysis one is evaluated by two means-square error （MSE） performance criteria. Finally, numerical simulation results verify the mathematical analysis conclusion, when N ≥21, simulation model has an excellent fitness with the analysis one.

Energy Estimation and Optimization Platform for 4G and the Future Base Station System Early-Stage Design

There are already several power models to estimate the power consumption of base stations at system level. However, there is so far no model that can predict power consumption of the future base station designs based on algorithms and hardware selections with insufficient physical information. We present such an energy model for typical base stations. This model can help designers in estimating, evaluating and optimizing energy/power consumption of candidate designs in early design stages. The proposed model is verified by an LTE extreme scenario. The estimated results show that digital front-end, channel equalization and channel decoding are three major power greedy modules(consuming 39.4%, 16.3%, 13.4%) in a digital baseband subsystem. The power estimation error of the proposed power amplifier(PA) power model is 3.5%(macro cell). The major contribution of this paper is that the proposed models can rapidly estimate energy/power consumption of 4G and the future base stations(such as 5G) in early design stages with well acceptable precision, even without sufficient implementation information.

Model of Real Time Architecture for Data Placement in Wireless Sensor Networks

Wireless sensor network (WSN) technology has promised fine grain monitoring in time and space as well as at a lower cost than is currently possible. These sensor networks are required to provide a robust service in hostile environments. Therefore the issue of real-time and reliable data delivery is extremely important for taking effective decisions in WSN. In this paper the architecture for reliable and real time approach by using sensor clusters has been proposed for storage management. Instead of storing information in an individual cluster head as suggested in some approaches, storing of information of all clusters, inside the cell is recommended within the corresponding base station. For data dissemination and action we have used Action and Relay Stations (ARS). We have developed programming model for formal specification and verification of our architecture.

A Potential Approach of Internet Worm Propagation Based on P2P

Various kinds of active worms have been plunging into the network flows, which make the Internet security problem more serious. Our research on a potential propagation approach of active worms, P2P-based propagation approach, is given in this paper. To measure the propagating performance of our approach, the SEI （Susceptible-Exposed-Infected） propagation model is presented. It proves that with the idea of pure P2P architecture, worms can be hidden in the early stage of propagation, and then infect most of the hosts in a shorter period. By comparing our SEI propagation model with the Simple Epidemic Model, we observe that the size of a worm is a significant parameter which can affect the propagating performance. When the size of the worm becomes large, our approach can still show an excellent propagating performance.

基于目标鲁棒的电动汽车及基站储能联合参与电力市场的决策模型

随着电动汽车(electric vehicle,EV)和第五代移动网络技术(5th generation mobile communication technology,5G)基站规模的不断增长,聚合商作为一种能够将众多EV和5G基站聚合起来的主体,在电力市场进行投标决策时会面临多重不确定因素。为应对市场电价和调频信号的不确定性以及EV和基站储能的时序响应能力可能存在互补性的问题,提出了一种基于目标鲁棒的EV和基站储能联合参与电力市场的决策方法。基于EV和基站储能单体模型建立了聚合商的聚合模型;计及市场电价和调频信号的不确定性,构建了聚合商参与电力市场的目标鲁棒优化模型;通过算例验证了所提模型相于传统不确定性优化模型的优越性,以及EV和基站储能联合参与电力市场可显著提高聚合商的收益。所提策略可为聚合商的投标决策提供参考,聚合商可利用所提模型合理地平衡决策行为的经济性和鲁棒性。

基于改进邻域粗糙集和优化BPNN的火灾预测算法

针对传统森林火灾检测算法精度低,以及大规模、多特征的火灾数据存在冗余信息等问题,该文提出了一种基于改进邻域粗糙集的优化反向传播神经网络(BPNN)火灾预测方法。首先,考虑到数据集具有高维特征空间和高度特征冗余等特点,设计出一种基于混沌反学习蝙蝠(BA)算法的邻域粗糙集特征选择算法,对火灾原始数据集进行特征寻优,得到约简属性子集;然后,构建BA算法优化的BPNN预测模型,将约简属性子集输入该模型中,得到火灾预测的结果;最后,通过平均分类准确度、F1值、精确度、曲线面积、召回率、平均误差率这6种评价指标,在UCI公开森林火灾数据集上分析和检验模型的分类性能。在2个数据集上的实验结果显示,基于混沌反学习策略的算法准确率为94.3%和52.7%,与邻域粗糙集结合后准确率达到98.1%和59.6%,证明了该文算法具备较高的检测精度。

航天地面站低代码开发平台方案设计

为了满足新形势下航天地面站快速交付、灵活部署与升级的需求,分析了基于模型的系统工程(Model-based Systems Engineering,MBSE)的航天地面系统模型,设计了一种适用于航天地面系统的低代码开发平台。该平台基于MBSE模型并通过可视化接口来构建包含软件功能、运行流程、数据处理等内容的应用程序。应用低代码软件平台,降低了软件开发的复杂性,满足装备快速升级的需求,研制时间较传统方法缩短了近45%。

基于地形网格化和遗传算法的MLAT基站选址研究

针对不同多点定位(Mulilateration,MLAT)地面站的布站方式对定位精度影响的问题,提出一种基于地形实际计算最优布站方式的方法。该方法结合实际地形因素,构建地形网格化模型生成初始可选站点,通过XDraw算法计算地面基站的覆盖性对初始站点进行初筛,再结合遗传算法计算最优布站组合。最后选取不规则图形区域进行选址实验验证,在选址区域内随机生成地形,通过初筛减少初始可选点,得到布站方式,并计算几何精度因子和多点定位均方根误差,与传统布站方式进行比较。实验数据表明,该方法计算得出的布站组合与传统布站方式相比,多点定位均方根误差要比传统布站中最小的菱形布站减小4.0159 m,且该方法可用于实际考虑地形因素的MLAT最优基站选址。

基于GA-BPNN算法的碳纸原纸性能指标建模预测研究

本研究通过改变碳纤维长度、碳纤维占比、分散剂用量等工艺参数,制备不同碳纸原纸,探究不同工艺参数对其抗张强度、孔隙率、透气性、电阻率的影响,采用遗传算法改进反向传播神经网络算法(GA-BPNN算法),构建了碳纸原纸性能预测模型。结果表明,碳纤维长度与碳纸原纸抗张强度、孔隙率、透气性呈正相关,与电阻率呈负相关;碳纤维占比与碳纸原纸抗张强度呈负相关,与孔隙率、透气性、电阻率呈正相关;分散剂用量与碳纸原纸抗张强度、电阻率呈正相关,与孔隙率、透气性呈负相关;碳纸原纸抗张强度、孔隙率、透气性、电阻率预测模型平均相对误差(MRE)分别为5.49%、5.75%、5.21%、5.54%,预测模型MRE均小于10%,与实验得到的工艺参数对碳纸原纸性能的关系趋势一致。

基于PCA-SBM的轨道交通站点接驳评价体系——以厦门市轨道交通站点为例

以慢行交通规划为指导,搭建基于PCA-SBM(主成分分析-基于松弛值测算)的效率评价模型,从管理者视角对厦门市轨道交通单车接驳现状作出评价。研究发现:厦门市站点接驳效率整体偏低,多呈现高投入、中回报的数据表现,需加强高峰日的引导轮次;电子围栏使用率低,应加强政企联动,做好及时的高峰时期车辆调度与用户前端引导,提升用户对电子围栏的感知,推动落实智能化管理。

蓄电池精准配置分析模型开发与应用研究

作为基站备用电源,蓄电池除能保证通信网络的可靠性与稳定性,还能在削峰填谷、平衡电网负荷及降低通信设备能耗的情况下发挥重要作用。调查发现,在蓄电池正常运行的情况下,仍存在容量下降过快、使用寿命大幅缩短的问题,初步认为与蓄电池本身状况及使用环境有关。为此,该文开发一种电池容量测评模型,该模型建立4个一级指标和17个二级指标,在指标赋值的情况下对蓄电池的基础信息、运行环境、社会影响和维护情况作出综合评价,根据最终的评分判断电池等级,并为下一步的蓄电池管理提供指导。

面向5G-A的无线网络节能关键技术分析

阐述5G-A无线网络中的网络能耗建模、基站不连续发送/接收模式、公共信令轻量化传输、动态通道关断及测量上报增强技术,通过分析原理和应用场景,探讨5G-A无线网络节能的实现策略。

基于IEC 61850的智能水电站建设研究

随着智能水电站的不断发展,水电站产生的海量数据因采用不同的通信标准导致数据孤岛问题加剧。为有效实现数据的共享与整合,研究基于IEC 61850通信标准建设智能水电站。从电站物理对象层级划分、信息对象建模、通信系统建设、一体化管控平台建设等过程阶段,研究基于IEC 61850的智能水电站全过程建设方案框架及流程方法,并从设备对象化建模、标准通信建设、一体化管控平台应用等方面详细阐述了基于IEC 61850的智能水电站全过程建设的关键技术。研究成果可为智能水电站建设打通数据底板基础,对智能水电站的建设及应用具有一定参考价值。

Empirical Studies on Topographical Influences on Crbc/Akbc Terrestrial Television Stations’ Signals in Akpabuyo Local Council Area, Nigeria

Dissemination of information to citizens is a relevant component of governance. Expectedly, viewers tuned to broadcast stations within and outside their localities, expecting their receivers to faithfully reproduce the exact features of the transmitted signal. Akpabuyo is a dense forest zone near the creeks leading to the Atlantic ocean in Cross River State, Nigeria. The location has distinct environmental characteristics that made Akpabuyo Area Council, a challenging location to propagate electromagnetic waves;and therefore recipe for further investigation. Radio frequency analyzer, with 24 channels spectrum, ranging between 46 - 870 MHz (model: RO.VE.R.-“DLM3-T”) was deployed to capture signals from terrestrial television stations (TV). CATV measured signal of TV stations in dB, dBμV and dBmV. Its frequency ranged from 40 - 860 MHz;while varying from channel 1 to channel 69. Measurements taken from Akpabuyo L.G.A. showed the following results: the signal strength received from VHF Channel 11 ranged from 20 dBμV to 49 dBμV. From recorded empirical statistics from the study, 50% of the area received signal from this station above 30 dBμV, while other regions had signals below this value;representing the fringe zone of the frequency. The results obtained from the study relatively showed acceptance with Egli’s model. The study recorded a steady fluctuation between 17 dBμV and 19 dBμV from both propagating stations. However, Channel 27 signal at 519 MHz, had very weak signal coverage in Akpabuyo Local Government Area;with signal strength dropped to as low as 13 dB in many parts of the rural area. The study discovered that the state’s broadcasting stations, both at UHF and VHF channels did not transmit successfully across this densely forest (rural) location. Remedial measures such as installing Repeater stations at different locations as signal booster were recommended.

5G零碳基站配置模型研究与应用

国家3060的碳排放目标,对运营商5G基站建设提出了更高的要求。本文针对5G基站高能耗的问题,总结了5G零碳基站配置模型和方案,基本实现了5G基站纯光供电。总结的模型和方案对5G基站节能减排工作的开展有较大的指导意义。

信息疫情中真假信息竞争性传播研究

[目的/意义]信息疫情传播的实质是真假信息竞争性传播的过程,厘清信息疫情中真假信息竞争性传播机理,对信息疫情管控策略的制定具有重要意义。[方法/过程]基于流行病模型结合用户创作行为特性构建了FT-SIR模型,求解所构建动力学模型的平衡点并进行稳定性分析,利用NetLogo模拟真假信息竞争性传播过程,同时针对微博的典型案例数据验证模型的有效性。[结果/结论]实验表明,在用户创作行为的作用下,单一信息在传播过程中会发生变异并催生真假信息的竞争性传播;“信息茧房”效应及意见领袖的存在使得用户具有不同的角色特质,进而对真假信息的竞争性传播产生显著影响。为政府采取措施降低信息疫情的危害提供了具体的管控策略与建议。