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Multiple ray received power modelling for mmWave indoor and outdoor scenarios

机译：MMWAVE室内和户外场景的多射线接收功率建模

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Wahab Khawaja; Ozgur Ozdemir; Fatih Erden; Ender Ozturk; Ismail Guvenc;
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1. Outdoor-to-Indoor and Indoor-to-Indoor Propagation Path Loss Modeling Using Smart 3D Ray Tracing Algorithm at 28 GHz mmWave [J] . Ubaid Ullah, Usman Rauf Kamboh, Ferdous Hossain, Arabian Journal for Science and Engineering. Section A, Sciences . 2020,第12期

机译：28 GHz MMWAVE中使用SMART 3D射线跟踪算法的户外到室内和室内环球传播路径损耗模型
2. A study on outdoor localization method based on deep learning using model-based received power estimation data of low power wireless tag [J] . Takuto Jikyo, Takahiro Yamanishi, Tomio Kamada, IEICE Communications Express . 2019,第12期

机译：基于深度学习的低功耗无线标签基于模型的接收功率估计数据的室外定位方法研究
3. The Comparative Study of S-V Model Between 3.5 and 28 GHz in Indoor and Outdoor Scenarios [J] . IEEE Transactions on Vehicular Technology . 2020,第3期

机译：室内和室外场景中3.5和28 GHz之间的S-V模型的比较研究
4. Comparison of ray tracing simulations and channel measurements at mmWave bands for indoor scenarios [C] . Anders Karstensen, Wei Fan, Ines Carton, European Conference on Antennas and Propagation . 2016

机译：室内场景下mmWave波段的光线追踪模拟和通道测量的比较
5. Indoor /outdoor location of cellular handsets based on received signal strength [D] . Zhu, Jian 2006

机译：基于接收信号强度的蜂窝手机的室内/室外位置
6. A Two-Hop mmWave MIMO NR-Relay Nodes to Enhance the Average System Throughput and BER in Outdoor-to-Indoor Environments [O] . Randy Verdecia-Peña, José I. Alonso 2021

机译：两个跳MMWAVE MIMO NR-RELAY节点以增强室外到室内环境中的平均系统吞吐量和BER
7. Comparison of Ray Tracing Simulations and Channel Measurements At mmWave Bands for Indoor Scenarios [O] . Karstensen Anders, Fan Wei, Llorente Ines Carton, 2016

机译：室内场景下mmWave波段的光线跟踪仿真和信道测量的比较
8. Modeling the Effects of Outdoor Gasoline Powered Generator Use on Indoor Carbon Monoxide Exposures - Phase II [R] . Wang, L., Emmerich, S. J., Powell, R. 2010

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Multiple ray received power modelling for mmWave indoor and outdoor scenarios

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