Fusing Channel and Sensor Measurements for Enhancing Predictive Beamforming in UAV-Assisted Massive MIMO Communications
Massive multiple-input multiple-output (MIMO) is a promising technology that can mitigate interference effectively in cellular-connected unmanned aerial vehicle (UAV) communications. In this letter, we propose a fusion of wireless and sensor data to enhance beam alignment for cellular-connected UAV...
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| Veröffentlicht in: | IEEE wireless communications letters 2024-03, Vol.13 (3), p.869-873 |
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| container_title | IEEE wireless communications letters |
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| creator | Lee, Byunghyun Marcum, Andrew C. Love, David J. Krogmeier, James V. |
| description | Massive multiple-input multiple-output (MIMO) is a promising technology that can mitigate interference effectively in cellular-connected unmanned aerial vehicle (UAV) communications. In this letter, we propose a fusion of wireless and sensor data to enhance beam alignment for cellular-connected UAV massive MIMO communications. We develop a predictive beamforming framework, including the frame structure and predictive beamformer. Moreover, we employ an extended Kalman filter (EKF) to integrate channel and sensor data. Simulation results demonstrate that the proposed scheme can improve position/orientation estimation accuracy significantly, leading to higher spectral efficiency. |
| doi_str_mv | 10.1109/LWC.2023.3348794 |
| format | Article |
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Simulation results demonstrate that the proposed scheme can improve position/orientation estimation accuracy significantly, leading to higher spectral efficiency.</description><subject>Array signal processing</subject><subject>Autonomous aerial vehicles</subject><subject>Base stations</subject><subject>Beamforming</subject><subject>Extended Kalman filter</subject><subject>Frame structures</subject><subject>information fusion</subject><subject>integrated sensing and communication (ISAC)</subject><subject>Kalman filtering</subject><subject>Massive MIMO</subject><subject>MIMO communication</subject><subject>multi-input multi-output (MIMO)</subject><subject>Symbols</subject><subject>Synchronization</subject><subject>Tracking</subject><subject>Unmanned aerial vehicle (UAV)</subject><subject>Unmanned aerial vehicles</subject><issn>2162-2337</issn><issn>2162-2345</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpNkM1Lw0AQxYMoWGrvHjwseE7dr2w2xxpaLbRU0OoxbDYT3dJs6m6i-N-7oUWcyzxmfm8GXhRdEzwlBGd3q7d8SjFlU8a4TDN-Fo0oETSmjCfnf5qll9HE-x0OJTChRI6i70XvjX1H-YeyFvZI2Qo9g_WtQ2tQvnfQgO08qsNgbgOkB_rJQWV0Z74A3YNqwrIZxsai7ew1nnlvfAcVWqugArNerjcob5umt0arzrTWX0UXtdp7mJz6ONou5i_5Y7zaPCzz2SrWVKZdLKAWdSkzDUAlScoyJQmVGQhR1glPdCpkorSuQWMscS0FT5Oq5CWTgIXAjI2j2-Pdg2s_e_BdsWt7Z8PLgmY8lVRkmAcKHyntWu8d1MXBmUa5n4LgYki4CAkXQ8LFKeFguTlaDAD8w1lYJoL9AmhGd8U</recordid><startdate>20240301</startdate><enddate>20240301</enddate><creator>Lee, Byunghyun</creator><creator>Marcum, Andrew C.</creator><creator>Love, David J.</creator><creator>Krogmeier, James V.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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| ispartof | IEEE wireless communications letters, 2024-03, Vol.13 (3), p.869-873 |
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| source | IEEE Electronic Library (IEL) |
| subjects | Array signal processing Autonomous aerial vehicles Base stations Beamforming Extended Kalman filter Frame structures information fusion integrated sensing and communication (ISAC) Kalman filtering Massive MIMO MIMO communication multi-input multi-output (MIMO) Symbols Synchronization Tracking Unmanned aerial vehicle (UAV) Unmanned aerial vehicles |
| title | Fusing Channel and Sensor Measurements for Enhancing Predictive Beamforming in UAV-Assisted Massive MIMO Communications |
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