检索结果-内蒙古大学图书馆

Maximizing coverage of a Single Frequency Network for Digital Television Services

IEEE LATIN AMERICA TRANSACTIONS 2012年第4期10卷 1881-1888页

作者： Egli, R. Torres, S. Pradenas, L. Perez, J. R. Basterrechea, J. Univ Concepcion UDEC Concepcion Bio Bio Chile Univ Cantabria UNICAN Santander Cantabria Spain

This paper approaches the problem of maximising Single Frequency Network (SFN) coverage for digital terrestrial television (DTT) based on the ISDB-T standard. An important issue to face up deals with the prioritization of specific zones in the study region (of high population density) with the aim of covering the most users possible. The optimization-based approach introduces directive receiving antennas along with transmitting sector antennas to make the network more realistic. Moreover, the ITU-R P. 1546 propagation prediction method is used and applied to digital terrain maps (DTM) and the transmitters useful and interfering contributions are estimated at every receiver point within the region. The parameters to be optimized for every transmitter using the simulated annealing algorithm include static delays, the effective radiated power (ERP) and the relative azimuth orientation for sector antennas. Representative results considering a region in northern Spain with a topography similar to any coastal region in Chile surrounded by mountain ranges, are included and discussed.

关键词： ISDB-T OFDM simulated annealing single frequency networks Digital broadcasting systems coverage optimization Digital terrestrial television

来源：评论

学校读者我要写书评

暂无评论

An Optimal WSN coverage Based on Adapted Transit Search Algorithm

引用

INTERNATIONAL JOURNAL OF SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING 2023年第10期33卷 1489-1512页

作者： Dao, Thi-Kien Nguyen, Trong-The Ngo, Truong-Giang Nguyen, Trinh-Dong Fujian Univ Technol Sch Comp Sci & Math Fujian Prov Key Lab Big Data Min & Applicat Fuzhou 350118 Peoples R China VNU Ho Chi Minh City Univ Informat Technol Multimedia Commun Lab Ho Chi Minh City Vietnam Thuyloi Univ Fac Comp Sci & Engn Hanoi Vietnam VNU Ho Chi Minh City Univ Informat Technol Fac Software Engn Ho Chi Minh City Vietnam Vietnam Natl Univ Ho Chi Minh City 700000 Vietnam

The wireless sensor network (WSN) coverage is one of the most significant impacts on the quality of service that directly determines the efficiency reality of applications. The distribution of sensor nodes in the WSN determines the size of the network monitoring coverage area, whether there is duplicate coverage, and monitoring blind regions. This study introduces an optimal coverage strategy for the sensor node positions in the sensing region based on an adapted transit search (ATS) algorithm. The transit search (TS) algorithm is a recently developed metaheuristic algorithm with several advantages, e.g. simple concept, robust process, and ease of implementation;still, TS has limitations in the ratios of exploration and exploitation for avoiding the local optimum trap when dealing with complicated node coverage optimization situations. The ATS is implemented by adapting and updating equations with stochastic reverse learning and multi-direction strategies to prevent its original algorithm drawbacks. The experimental analysis is carried out to demonstrate the efficiency of the designed coverage scheme in terms of various metrics, e.g. coverage rate, positioning errors, converge speed, and executed time. Compared experimental-result shows that the ATS scheme offers the WSN applicability coverage model to perform the deployment network application with excellent quality. Significantly, the coverage rate archived of the ATS is 87%, but the other methods are only below or equally 84% in the same comparison conditions.

关键词： Adopted transit search algorithm wireless sensor network coverage optimization sensor nodes deployment metaheuristic algorithms

来源：评论

学校读者我要写书评

暂无评论

Efficient Area coverage in Wireless Sensor Networks Using Optimal Scheduling

引用

WIRELESS PERSONAL COMMUNICATIONS 2019年第2期107卷 1187-1198页

作者： Choudhuri, Ritamshirsa Das, Rajib K. Univ Calcutta Dept Comp Sci & Engn Kolkata India

Wireless sensor networks generally have unique lifetime necessities. In any case, the density of the sensors may not be sufficiently substantial to fulfil the coverage requirement while meeting the lifetime constraint in the mean time. Once in a while coverage has to be traded for network lifetime. The proposed efficient pipeline based spatial temporal optimization scheduling for coverage optimization satisfies the coverage problem while meeting the lifetime constraint at the same time. In the proposed optimal scheduling, initially number of nodes in the network is clustered by using energy based one hop clustering algorithm. After the formation of clusters pipeline based spatial temporal optimization algorithm is used for the optimal scheduling. Here the optimization is improved by using trust of each sensor nodes and the area of clusters. Finally, data is aggregated through the optimally scheduled cluster nodes. The experimental results show that our proposed optimization scheduling substantially outperforms other schemes in terms of network lifetime, coverage redundancy and convergence time.

关键词： Clustering Trust calculation coverage optimization Scheduling Network lifetime

来源：评论

学校读者我要写书评

暂无评论

Small Cell Transmit Power Assignment Based on Correlated Bandit Learning

引用

IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2017年第5期35卷 1030-1045页

作者： Wang, Zhiyang Shen, Cong Univ Sci & Technol China Sch Informat Sci & Technol Dept Elect Engn & Informat Sci Hefei 230027 Peoples R China

Judiciously setting the base station transmit power that matches its deployment environment is a key problem in ultra-dense networks and heterogeneous in-building cellular deployments. A unique characteristic of this problem is the tradeoff between sufficient indoor coverage and limited outdoor leakage, which has to be met without explicit knowledge of the environment. In this paper, we address the small base station (SBS) transmit power assignment problem based on stochastic bandit theory. Unlike existing solutions that rely on heavy involvement of RF engineers surveying the target area, we take advantage of the human user behavior with simple coverage feedback in the network, and thus significantly reduce the planned human measurement. In addition, the proposed power assignment algorithms follow the Bayesian principle to utilize the available prior knowledge from system self-configuration. To guarantee good performance when the prior knowledge is insufficient, we incorporate the performance correlation among similar power values, and establish an algorithm that exploits the correlation structure to recover majority of the degraded performance. Furthermore, we explicitly consider power switching penalties in order to discourage frequent changes of the transmit power, which cause varying coverage and uneven user experience. Comprehensive system-level simulations are performed for both single and multiple SBS deployment scenarios, and the resulting power settings are compared with the state-of-the-art solutions. Significant performance gains of the proposed algorithms are observed. Particularly, the correlation structure enables the algorithm to converge much faster to the optimal long- term power than other methods.

关键词： coverage optimization transmit power assignment heterogeneous network (HetNet)

来源：评论

学校读者我要写书评

暂无评论

Decentralized Swarm Coordination: A Combined coverage/Connectivity Approach

引用

JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS 2011年第3-4期64卷 603-623页

作者： Stergiopoulos, Yiannis (John) Tzes, Anthony Univ Patras Dept Elect & Comp Engn Rion 26500 Achaia Greece

Decentralized motion coordination for coverage optimization purposes in mobile sensor networks is the scope of this paper. Coordination is performed based on spatial Voronoi tessellation, while taking into consideration the limited sensing capabilities of the agents. Each node performs an independent optimization in order to increase network's area coverage via its motion, while it attains information from its current and future Delaunay neighbors. A decentralized algorithm is proposed in order to achieve optimal network's coverage, based on local information. Connectivity issues are analyzed in detail, while a lower bound on the communication radius of the nodes is derived, in order to attain sufficient information for performing the corresponding optimization. An agent moves inside its region of responsibility in a way that the total area surveyed by the network is a monotonically increasing function of time. The online control action makes the network adaptive to possible changes in the environment.

关键词： Voronoi diagrams Sensor networks Decentralized control coverage optimization Motion coordination

来源：评论

学校读者我要写书评

暂无评论

Optimal Sensor Placement for Monitoring of Spatial Networks

引用

IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2018年第1期15卷 33-44页

作者： Krishnamurthy, Prashanth Khorrami, Farshad NYU Polytech Sch Engn Dept Elect & Comp Engn Control Robot Res Lab Brooklyn NY 11201 USA FarCo Technol Inc Brooklyn NY 11201 USA

The problem of optimal placement of sensors for monitoring a spatial network (e.g., a road network with moving ground targets or intruders) is considered in this paper. In particular, the optimization of locations of a set of sensors (that can each obtain measurements in a local region around the sensor location) is considered so as to maximize an overall sensor coverage metric defined over the spatial network. The sensor coverage optimality metric for spatial network coverage is based on a novel formulation of a sensor influence wave based on a spatiotemporal model of the measurement reach of a set of sensors given a spatial network topology, a probabilistic model of target movements on the network, and spatial weight maps that model the relative importance/utility of different locations in the spatial region. The sensor placement optimization is based on an iterative genetic algorithm for the optimization of a scalar metric computed from the spatial integration of the sensor influence wave. The efficacy of the proposed approach is demonstrated through simulation studies for several road network geometries. Note to Practitioners-This paper considers the problem of finding optimal locations for sensors for monitoring a spatial network for moving targets (e.g., a road network with moving ground targets or intruders). Sensor-based monitoring of a spatial region is relevant in a variety of applications (including, in general, such diverse application areas as traffic monitoring in transportation applications, intruder monitoring, surveillance, power systems monitoring, structural health monitoring, etc). This paper offers two primary novel aspects: an optimality metric formulation for target monitoring effectiveness on spatial networks and an iterative genetic algorithm-based method for optimization of the sensor placement configuration. The proposed approach enables addressing of multiple spatial criteria within a unified framework, including the probabilistic charact

关键词： coverage optimization road networks sensor networks sensor placement spatial monitoring

来源：评论

学校读者我要写书评

暂无评论

optimization of Multi-Frequency Network With DVB-T2 Services for Regions With Complex Geographies: A Case Study of Nepal

引用

IEEE TRANSACTIONS ON BROADCASTING 2021年第1期67卷 299-312页

作者： Nepal, Subodh Thang, Duong Quang Higashino, Takeshi Okada, Minoru Nara Inst Sci & Technol Grad Sch Sci & Technol Nara 6300192 Japan

Planning for Multi-Frequency Network (MFN) with Digital Video Broadcasting-Second Generation Terrestrial (DVB-T2) services is particularly useful during the transition from analog to digital broadcasting. For efficient management of service area as well as resource allocation, it is necessary to administer the use of network parameters, e.g., transmit power, frequency channels, and antenna parameters. This article, therefore, proposes a coverage maximization scheme for the MFN with the DVB-T2 system by using the Genetic Algorithm. In order to effectively perform the optimization over regions with diverse geographical structures, a propagation prediction method considering the complex orography together with Digital Elevation Model is used to predict signal strength at each receiving location. Based on the received signal strength and standard Quality of Service criteria, the overall radio coverage of the network is maximized using the optimum values of transmit power levels, frequency channels, and antenna parameters. Although our analysis and simulations are based on the MFN network in Nepal, the methodology presented in this work can be applied in any region with some alterations in geographical and meteorological parameters.

关键词： optimization Radio transmitters Receivers Digital video broadcasting Predictive models Planning Transmitting antennas Co-channel interference coverage optimization coverage prediction DVB-T2 network parameter optimization spectrum usage

来源：评论

学校读者我要写书评

暂无评论

HAPS Cell Design Method for coverage Extension Considering Coexistence on Terrestrial Mobile Networks

引用

IEEE ACCESS 2024年 12卷 55506-55520页

作者： Shibata, Yohei Takabatake, Wataru Hoshino, Kenji Nagate, Atsushi Ohtsuki, Tomoaki SoftBank Corp Technol Res Lab Koto Tokyo 1350064 Japan Keio Univ Grad Sch Sci & Technol Yokohama Kanagawa 2238522 Japan

High-altitude platform stations (HAPSs) that provide direct communication services to smartphones on the ground are garnering significant attention as innovative mobile communication platforms suitable for ultrawide coverage areas. The deployment of a multi-cell configuration is essential for enhancing communication capacity over large geographical regions. However, designing and optimizing multi-cell configurations proves challenging due to the numerous antenna parameters involved, such as beamwidth and beam direction. HAPSs also hold promise in serving as reliable networks during disasters, as they can quickly restore coverage when terrestrial base stations (BSs) are in failure, allowing users to maintain connectivity via HAPSs using the same frequency band as terrestrial networks. Despite this advantage, HAPSs can potentially cause interference in terrestrial networks during such scenarios, necessitating careful considerations to avoid disrupting existing terrestrial networks. However, the optimization of cell configurations in the coexistence of HAPSs and terrestrial networks remains largely unexplored. To address this gap, this paper proposes a design scheme that leverages a genetic algorithm (GA) to optimize antenna parameters for each cell, thereby maximizing both user coverage and area coverage while ensuring coexistence with terrestrial networks. We optimize antenna parameters to increase user coverage and area coverage as a multi-objective optimization problem, resulting in a Pareto front that illustrates the trade-off choices. Additionally, the proposed method protects terrestrial networks by setting the initial beam direction of each cell to avoid interference with terrestrial BSs. Consequently, the GA can initiate optimization with candidate combinations that adhere to the interference constraints of terrestrial networks, thus expediting the optimization process and yielding improved coverage. Simulation results demonstrate that the proposed scheme outp

关键词： Interference optimization Genetic algorithms Disasters Base stations Statistics Social factors Smart phones coverage optimization genetic algorithm HAPS non-uniform user distribution coexistence between HAPS and terrestrial networks

来源：评论

学校读者我要写书评

暂无评论

Autonomous Non-Terrestrial Base Station Deployment for Non-Terrestrial Networks: A Reinforcement Learning Approach

引用

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2022年第10期71卷 10894-10909页

作者： Lien, Shao-Yu Deng, Der-Jiunn Natl Chung Cheng Univ Dept Comp Sci & Informat Engn Chiayi 62102 Taiwan Natl Changhua Univ Educ Dept Comp Sci & Informat Engn Changhua 50007 Taiwan

Non-Terrestrial Networks (NTN) consisting of multiple space-borne and airborne non-terrestrial base stations (NT-BSs) have recently been introduced by 3GPP as a new paradigm of infrastructure to extend the capacity and coverage of existing terrestrial networks to further support non-terrestrial UEs (NT-UEs). Mobility of NT-BSs and NT-UEs however leads to a dynamic and non-stationary environment, which creates unique challenges in the coverage optimization particularly for the dynamic deployment of multiple NT-BSs. Under the dynamic and non-stationary environment, each NT-BS should autonomously predict not only moving trajectories of NT-UEs and other NT-BSs but also the probability of presence of NT-UEs at any given location, and consequently a new machine learning (ML) scheme is desired. In this paper, instead of adopting the recent innovation of deep reinforcement learning (DRL) approaches inducing an unaffordable complexity for NT-BSs with a limited computing capability, new reinforcement learning (RL) schemes are therefore proposed, by which each of multiple NT-BSs autonomously determines the deployment trajectories to maximize the number of NT-UEs that can access NT-BSs. Through the comprehensive analysis, we justify the convergence of the performance of the proposed schemes. The simulation results also show the effectiveness of the proposed schemes and the outstanding performances as compared with state-of-the-art schemes.

关键词： Convergence optimization Complexity theory Q-learning Wireless communication Vehicle dynamics Trajectory optimization NTN multiple NT-BSs NT-UEs non-stationary environment RL coverage optimization autonomous deployment

来源：评论

学校读者我要写书评

暂无评论

Classifiers selection in ensembles using genetic algorithms for bankruptcy prediction

引用

EXPERT SYSTEMS WITH APPLICATIONS 2012年第10期39卷 9308-9314页

作者： Kim, Myoung-Jong Kang, Dae-Ki Dongseo Univ Div Comp & Informat Engn Pusan 617716 South Korea Pusan Natl Univ Sch Business Pusan South Korea

Ensemble learning is a method to improve the performance of classification and prediction algorithms. Many studies have demonstrated that ensemble learning can decrease the generalization error and improve the performance of individual classifiers and predictors. However, its performance can be degraded due to multicollinearity problem where multiple classifiers of an ensemble are highly correlated with. This paper proposes a genetic algorithm-based coverage optimization technique in the purpose of resolving multicollinearity problem. Empirical results with bankruptcy prediction on Korea firms indicate that the proposed coverage optimization algorithm can help to design a diverse and highly accurate classification system. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： Ensemble learning Genetic algorithm coverage optimization Bankruptcy prediction

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：