With the rapid development of wireless communications systems, different system standards are being merged. Operators take stringent measures to reduce Operational Expenditure （OPEX） and Capital Expenditure （CAPEX...With the rapid development of wireless communications systems, different system standards are being merged. Operators take stringent measures to reduce Operational Expenditure （OPEX） and Capital Expenditure （CAPEX）; and as a result, soft base stations supporting multiple standards become the evolutionary tend of wireless base stations. This paper introduces the background of soft base stations and analyzes their architecture design, system modules. The key technologies in system implementation and future directions are also presented.展开更多
Weather events put human lives at risk mostly when people might occupy areas susceptible to natural disasters.Deploying Professional Weather Stations(PWS)in vulnerable areas is key for monitoring weather with reliable...Weather events put human lives at risk mostly when people might occupy areas susceptible to natural disasters.Deploying Professional Weather Stations(PWS)in vulnerable areas is key for monitoring weather with reliable measurements.However,such professional instrumentation is notably expensive while remote sensing from a number of stations is paramount.This imposes challenges on the large-scale weather station deployment for broad monitoring from large observation networks such as in Cemaden—The Brazilian National Center for Monitoring and Early Warning of Natural Disasters.In this context,in this paper,we propose a Low-Cost Automatic Weather Station(LCAWS)system developed from Commercial Off-The-Shelf(COTS)and open-source Internet of Things(IoT)technologies,which provides measurements as reliable as a reference PWS for natural disaster monitoring.When being automatic,LCAWS is a stand-alone photovoltaic system connected wirelessly to the Internet in order to provide real-time reliable end-to-end weather measurements.To achieve data reliability,we propose an intelligent sensor calibration method to correct measures.From a 30-day uninterrupted observation with sampling in minute resolution,we show that the calibrated LCAWS sensors have no statistically significant differences from the PWS measurements.As such,LCAWS has opened opportunities for reducing maintenance costs in Cemaden's observational network.展开更多
为了提高无人机基站(unmanned aerial vehicle base stations,UAV-BS)为地面多用户服务时的数据速率,提出一种基于决斗深度神经网络(dueling deep Q-network,Dueling-DQN)的深度强化学习(deep reinforcement learning,DRL)算法。采用决...为了提高无人机基站(unmanned aerial vehicle base stations,UAV-BS)为地面多用户服务时的数据速率,提出一种基于决斗深度神经网络(dueling deep Q-network,Dueling-DQN)的深度强化学习(deep reinforcement learning,DRL)算法。采用决斗网络(dueling network,DN)结构以克服动态环境的部分可观测问题,联合优化了UAV-BS的位置和下行链路功率分配,在更符合实际的空地概率信道模型中检验了Dueling-DQN算法的性能。结果表明,相较于对比算法,所提出的Dueling-DQN算法可以提供更高的数据速率和服务公平性,且随着地面用户数量的增大,算法的优势更加明显。Dueling-DQN算法可有效解决复杂非凸性问题,为UAV-BS的资源分配问题提供理论参考。展开更多
确保无线电波的质量和安全播出是广播电视行业的基本要求,依赖无线发射台站的高效管理。传统的基于客户端的台站管理系统因其高成本、低效率等缺点逐渐不能满足当前的需求。因此,提出基于WebGIS(Web Geographic Information System)的...确保无线电波的质量和安全播出是广播电视行业的基本要求,依赖无线发射台站的高效管理。传统的基于客户端的台站管理系统因其高成本、低效率等缺点逐渐不能满足当前的需求。因此,提出基于WebGIS(Web Geographic Information System)的广播电视无线发射台站管理系统,旨在提升广播电视无线发射台站的管理能力。首先阐述系统特点,其次设计系统的总体结构,分析系统的主要功能模块,最后研究各功能模块的实现。展开更多
文摘With the rapid development of wireless communications systems, different system standards are being merged. Operators take stringent measures to reduce Operational Expenditure （OPEX） and Capital Expenditure （CAPEX）; and as a result, soft base stations supporting multiple standards become the evolutionary tend of wireless base stations. This paper introduces the background of soft base stations and analyzes their architecture design, system modules. The key technologies in system implementation and future directions are also presented.
基金partially funded by Sao Paulo Research Foundation(FAPESP),Brazil,grant numbers#2015/18808-0,#2018/23064-8,#2019/23382-2.
文摘Weather events put human lives at risk mostly when people might occupy areas susceptible to natural disasters.Deploying Professional Weather Stations(PWS)in vulnerable areas is key for monitoring weather with reliable measurements.However,such professional instrumentation is notably expensive while remote sensing from a number of stations is paramount.This imposes challenges on the large-scale weather station deployment for broad monitoring from large observation networks such as in Cemaden—The Brazilian National Center for Monitoring and Early Warning of Natural Disasters.In this context,in this paper,we propose a Low-Cost Automatic Weather Station(LCAWS)system developed from Commercial Off-The-Shelf(COTS)and open-source Internet of Things(IoT)technologies,which provides measurements as reliable as a reference PWS for natural disaster monitoring.When being automatic,LCAWS is a stand-alone photovoltaic system connected wirelessly to the Internet in order to provide real-time reliable end-to-end weather measurements.To achieve data reliability,we propose an intelligent sensor calibration method to correct measures.From a 30-day uninterrupted observation with sampling in minute resolution,we show that the calibrated LCAWS sensors have no statistically significant differences from the PWS measurements.As such,LCAWS has opened opportunities for reducing maintenance costs in Cemaden's observational network.
文摘为了提高无人机基站(unmanned aerial vehicle base stations,UAV-BS)为地面多用户服务时的数据速率,提出一种基于决斗深度神经网络(dueling deep Q-network,Dueling-DQN)的深度强化学习(deep reinforcement learning,DRL)算法。采用决斗网络(dueling network,DN)结构以克服动态环境的部分可观测问题,联合优化了UAV-BS的位置和下行链路功率分配,在更符合实际的空地概率信道模型中检验了Dueling-DQN算法的性能。结果表明,相较于对比算法,所提出的Dueling-DQN算法可以提供更高的数据速率和服务公平性,且随着地面用户数量的增大,算法的优势更加明显。Dueling-DQN算法可有效解决复杂非凸性问题,为UAV-BS的资源分配问题提供理论参考。
文摘确保无线电波的质量和安全播出是广播电视行业的基本要求,依赖无线发射台站的高效管理。传统的基于客户端的台站管理系统因其高成本、低效率等缺点逐渐不能满足当前的需求。因此,提出基于WebGIS(Web Geographic Information System)的广播电视无线发射台站管理系统,旨在提升广播电视无线发射台站的管理能力。首先阐述系统特点,其次设计系统的总体结构,分析系统的主要功能模块,最后研究各功能模块的实现。
