Statistical Modeling of Ultrawideband MIMO Propagation Channel in a Warehouse Environment
This paper describes an extensive propagation channel measurement campaign in a warehouse environment for line-of-sight (LOS) and nonline-of-sight (NLOS) scenarios. The measurement setup employs a vector network analyzer operating in the 2-8-GHz frequency band combined with an 8 × 8 virtual multiple...
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Published in: | IEEE transactions on antennas and propagation Vol. 64; no. 9; pp. 4049 - 4063 |
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Main Authors: | , , , , , |
Format: | Journal Article |
Language: | English |
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01-09-2016
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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Abstract | This paper describes an extensive propagation channel measurement campaign in a warehouse environment for line-of-sight (LOS) and nonline-of-sight (NLOS) scenarios. The measurement setup employs a vector network analyzer operating in the 2-8-GHz frequency band combined with an 8 × 8 virtual multiple-input multiple-output (MIMO) antenna array. We develop a comprehensive statistical propagation channel model based on high-resolution extraction of multipath components and subsequent spatiotemporal clustering analysis. The intracluster direction of departure (DoD), direction of arrival (DoA), and the time of arrival (ToA) are independent, both for the LOS and NLOS scenarios. The intracluster DoD and DoA can be approximated by the Laplace distribution, and the intracluster ToA can be approximated by an exponential mixture distribution. The intercluster analysis, however, shows a dependency between the cluster DoD, DoA, and ToA. To capture this dependency, we separately model the clusters caused by single and multiple bounce scattering along the aisles in the warehouse. The intercluster DoD distribution follows a Laplace distribution, while the cluster DoA conditioned on the DoD is approximated by a Gaussian mixture distribution. The model was validated using the capacity and delay-spread values. |
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AbstractList | This paper describes an extensive propagation channel measurement campaign in a warehouse environment for line-of-sight (LOS) and nonline-of-sight (NLOS) scenarios. The measurement setup employs a vector network analyzer operating in the 2-8-GHz frequency band combined with an 8 × 8 virtual multiple-input multiple-output (MIMO) antenna array. We develop a comprehensive statistical propagation channel model based on high-resolution extraction of multipath components and subsequent spatiotemporal clustering analysis. The intracluster direction of departure (DoD), direction of arrival (DoA), and the time of arrival (ToA) are independent, both for the LOS and NLOS scenarios. The intracluster DoD and DoA can be approximated by the Laplace distribution, and the intracluster ToA can be approximated by an exponential mixture distribution. The intercluster analysis, however, shows a dependency between the cluster DoD, DoA, and ToA. To capture this dependency, we separately model the clusters caused by single and multiple bounce scattering along the aisles in the warehouse. The intercluster DoD distribution follows a Laplace distribution, while the cluster DoA conditioned on the DoD is approximated by a Gaussian mixture distribution. The model was validated using the capacity and delay-spread values. This paper describes an extensive propagation channel measurement campaign in a warehouse environment for line-of-sight (LOS) and nonline-of-sight (NLOS) scenarios. The measurement setup employs a vector network analyzer operating in the 2-8-GHz frequency band combined with an [Formula Omitted] virtual multiple-input multiple-output (MIMO) antenna array. We develop a comprehensive statistical propagation channel model based on high-resolution extraction of multipath components and subsequent spatiotemporal clustering analysis. The intracluster direction of departure (DoD), direction of arrival (DoA), and the time of arrival (ToA) are independent, both for the LOS and NLOS scenarios. The intracluster DoD and DoA can be approximated by the Laplace distribution, and the intracluster ToA can be approximated by an exponential mixture distribution. The intercluster analysis, however, shows a dependency between the cluster DoD, DoA, and ToA. To capture this dependency, we separately model the clusters caused by single and multiple bounce scattering along the aisles in the warehouse. The intercluster DoD distribution follows a Laplace distribution, while the cluster DoA conditioned on the DoD is approximated by a Gaussian mixture distribution. The model was validated using the capacity and delay-spread values. This paper describes an extensive propagation channel measurement campaign in a warehouse environment for line-of-sight (LOS) and nonline-of-sight (NLOS) scenarios. The measurement setup employs a vector network analyzer operating in the 2-8-GHz frequency band combined with an 8×8 virtual multiple-input multiple-output (MIMO) antenna array. We develop a comprehensive statistical propagation channel model based on high-resolution extraction of multipath components and subsequent spatiotemporal clustering analysis. The intracluster direction of departure (DoD), direction of arrival (DoA), and the time of arrival (ToA) are independent, both for the LOS and NLOS scenarios. The intracluster DoD and DoA can be approximated by the Laplace distribution, and the intracluster ToA can be approximated by an exponential mixture distribution. The intercluster analysis, however, shows a dependency between the cluster DoD, DoA, and ToA. To capture this dependency, we separately model the clusters caused by single and multiple bounce scattering along the aisles in the warehouse. The intercluster DoD distribution follows a Laplace distribution, while the cluster DoA conditioned on the DoD is approximated by a Gaussian mixture distribution. The model was validated using the capacity and delay-spread values. |
Author | Molisch, Andreas F. Ruisi He Behairy, Hatim Mohammed Kristem, Vinod Tufvesson, Fredrik Sangodoyin, Seun |
Author_xml | – sequence: 1 givenname: Seun surname: Sangodoyin fullname: Sangodoyin, Seun email: sangodoy@usc.edu organization: Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA – sequence: 2 givenname: Vinod surname: Kristem fullname: Kristem, Vinod email: kristem@usc.edu organization: Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA – sequence: 3 givenname: Andreas F. surname: Molisch fullname: Molisch, Andreas F. email: molisch@usc.edu organization: Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA – sequence: 4 surname: Ruisi He fullname: Ruisi He email: he.ruisi.china@gmail.com organization: Beijing Jiaotong Univ., Beijing, China – sequence: 5 givenname: Fredrik surname: Tufvesson fullname: Tufvesson, Fredrik email: fredrik.tufvesson@eit.lth.se organization: Dept. of Electr. & Inf. Technol., Lund Univ., Lund, Sweden – sequence: 6 givenname: Hatim Mohammed surname: Behairy fullname: Behairy, Hatim Mohammed email: hbehairy@kacst.edu.sa organization: King Abdul Aziz City for Sci. & Technol., Riyadh, Saudi Arabia |
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Snippet | This paper describes an extensive propagation channel measurement campaign in a warehouse environment for line-of-sight (LOS) and nonline-of-sight (NLOS)... |
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SubjectTerms | Antenna arrays Antenna measurements Channel models Communication Systems Delays Electrical Engineering, Electronic Engineering, Information Engineering Elektroteknik och elektronik Engineering and Technology Frequency measurement Kommunikationssystem MIMO Multiple-input multiple-output (MIMO) Position measurement propagation channel statistical channel model Teknik ultrawide-band (UWB) Warehouse environment |
Title | Statistical Modeling of Ultrawideband MIMO Propagation Channel in a Warehouse Environment |
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