Analytical Blind Beamforming for a Multi-Antenna UAV Base-Station Receiver in Millimeter-Wave Bands
Over the last decade, unmanned aerial vehicles (UAVs) with antenna arrays have usually been employed for the enhancement of wireless communication in millimeter-wave bands. They are commonly used as aerial base stations and relay platforms in order to serve multiple users. Many beamforming methods f...
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MDPI AG
2021-09-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/21/19/6561 |
| _version_ | 1797515701617950720 |
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| author | Pingchuan Liu Kuangang Fan Yuhang Chen |
| author_facet | Pingchuan Liu Kuangang Fan Yuhang Chen |
| author_sort | Pingchuan Liu |
| collection | DOAJ |
| description | Over the last decade, unmanned aerial vehicles (UAVs) with antenna arrays have usually been employed for the enhancement of wireless communication in millimeter-wave bands. They are commonly used as aerial base stations and relay platforms in order to serve multiple users. Many beamforming methods for improving communication quality based on channel estimation have been proposed. However, these methods can be resource-intensive due to the complexity of channel estimation in practice. Thus, in this paper, we formulate an MIMO blind beamforming problem at the receivers for UAV-assisted communications in which channel estimation is omitted in order to save communication resources. We introduce one analytical method, which is called the analytical constant modulus algorithm (ACMA), in order to perform blind beamforming at the UAV base station; this relies only on data received by the antenna. The feature of the constant modulus (CM) is employed to restrict the target user signals. Algebraic operations, such as singular value decomposition (SVD), are applied to separate the user signal space from other interferences. The number of users in the region served by the UAV can be detected by exploring information in the measured data. We seek solutions that are expressible as one Kronecker product structure in the signal space; then, the beamformers that correspond to each user can be successfully estimated. The simulation results show that, by using this analytically derived blind method, the system can achieve good signal recovery accuracy, a reasonable system sum rate, and acceptable complexity. |
| first_indexed | 2024-03-10T06:51:00Z |
| format | Article |
| id | doaj.art-45c98d6649434edc8a1e44dac740490f |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T06:51:00Z |
| publishDate | 2021-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-45c98d6649434edc8a1e44dac740490f2023-11-22T16:47:57ZengMDPI AGSensors1424-82202021-09-012119656110.3390/s21196561Analytical Blind Beamforming for a Multi-Antenna UAV Base-Station Receiver in Millimeter-Wave BandsPingchuan Liu0Kuangang Fan1Yuhang Chen2School of Mechanical and Electrical Engineering, Jiangxi University of Science and Technology, Hongqi Street No. 86, Ganzhou 341000, ChinaMagnetic Suspension Technology Key Laboratory of Jiangxi Province, Jiangxi University of Science and Technology, Hongqi Street No. 86, Ganzhou 341000, ChinaMagnetic Suspension Technology Key Laboratory of Jiangxi Province, Jiangxi University of Science and Technology, Hongqi Street No. 86, Ganzhou 341000, ChinaOver the last decade, unmanned aerial vehicles (UAVs) with antenna arrays have usually been employed for the enhancement of wireless communication in millimeter-wave bands. They are commonly used as aerial base stations and relay platforms in order to serve multiple users. Many beamforming methods for improving communication quality based on channel estimation have been proposed. However, these methods can be resource-intensive due to the complexity of channel estimation in practice. Thus, in this paper, we formulate an MIMO blind beamforming problem at the receivers for UAV-assisted communications in which channel estimation is omitted in order to save communication resources. We introduce one analytical method, which is called the analytical constant modulus algorithm (ACMA), in order to perform blind beamforming at the UAV base station; this relies only on data received by the antenna. The feature of the constant modulus (CM) is employed to restrict the target user signals. Algebraic operations, such as singular value decomposition (SVD), are applied to separate the user signal space from other interferences. The number of users in the region served by the UAV can be detected by exploring information in the measured data. We seek solutions that are expressible as one Kronecker product structure in the signal space; then, the beamformers that correspond to each user can be successfully estimated. The simulation results show that, by using this analytically derived blind method, the system can achieve good signal recovery accuracy, a reasonable system sum rate, and acceptable complexity.https://www.mdpi.com/1424-8220/21/19/6561UAV base stationMIMOmillimeter-wave bandblind beamformingsignal recovery |
| spellingShingle | Pingchuan Liu Kuangang Fan Yuhang Chen Analytical Blind Beamforming for a Multi-Antenna UAV Base-Station Receiver in Millimeter-Wave Bands Sensors UAV base station MIMO millimeter-wave band blind beamforming signal recovery |
| title | Analytical Blind Beamforming for a Multi-Antenna UAV Base-Station Receiver in Millimeter-Wave Bands |
| title_full | Analytical Blind Beamforming for a Multi-Antenna UAV Base-Station Receiver in Millimeter-Wave Bands |
| title_fullStr | Analytical Blind Beamforming for a Multi-Antenna UAV Base-Station Receiver in Millimeter-Wave Bands |
| title_full_unstemmed | Analytical Blind Beamforming for a Multi-Antenna UAV Base-Station Receiver in Millimeter-Wave Bands |
| title_short | Analytical Blind Beamforming for a Multi-Antenna UAV Base-Station Receiver in Millimeter-Wave Bands |
| title_sort | analytical blind beamforming for a multi antenna uav base station receiver in millimeter wave bands |
| topic | UAV base station MIMO millimeter-wave band blind beamforming signal recovery |
| url | https://www.mdpi.com/1424-8220/21/19/6561 |
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