Position Fingerprint-Based Beam Selection in Millimeter Wave Heterogeneous Networks
The traditional beam selection algorithms determine the optimal beam direction by feeding back the perfect channel state information (CSI) in a millimeter wave (mmWave) massive Multiple-Input Multiple-Output (MIMO) system. Popular beam selection algorithms mostly focus on the methods of feedback and...
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| Format: | Article |
| Language: | English |
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MDPI AG
2017-09-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/17/9/2009 |
| _version_ | 1811307386603831296 |
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| author | Zufan Zhang Yanbo Chen |
| author_facet | Zufan Zhang Yanbo Chen |
| author_sort | Zufan Zhang |
| collection | DOAJ |
| description | The traditional beam selection algorithms determine the optimal beam direction by feeding back the perfect channel state information (CSI) in a millimeter wave (mmWave) massive Multiple-Input Multiple-Output (MIMO) system. Popular beam selection algorithms mostly focus on the methods of feedback and exhaustive search. In order to reduce the extra computational complexity coming from the redundant feedback and exhaustive search, a position fingerprint (PFP)-based mmWave multi-cell beam selection scheme is proposed in this paper. In the proposed scheme, the best beam identity (ID) and the strongest interference beam IDs from adjacent cells of each fingerprint spot are stored in a fingerprint database (FPDB), then the optimal beam and the strongest interference beams can be determined by matching the current PFP of the user equipment (UE) with the PFP in the FPDB instead of exhaustive search, and the orthogonal codes are also allocated to the optimal beam and the strongest interference beams. Simulation results show that the proposed PFP-based beam selection scheme can reduce the computational complexity and inter-cell interference and produce less feedback, and the system sum-rate for the mmWave heterogeneous networks is also improved. |
| first_indexed | 2024-04-13T09:03:27Z |
| format | Article |
| id | doaj.art-9ba803e9cac243f191e9a0ce034adef4 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T09:03:27Z |
| publishDate | 2017-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-9ba803e9cac243f191e9a0ce034adef42022-12-22T02:53:03ZengMDPI AGSensors1424-82202017-09-01179200910.3390/s17092009s17092009Position Fingerprint-Based Beam Selection in Millimeter Wave Heterogeneous NetworksZufan Zhang0Yanbo Chen1School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, ChinaSchool of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, ChinaThe traditional beam selection algorithms determine the optimal beam direction by feeding back the perfect channel state information (CSI) in a millimeter wave (mmWave) massive Multiple-Input Multiple-Output (MIMO) system. Popular beam selection algorithms mostly focus on the methods of feedback and exhaustive search. In order to reduce the extra computational complexity coming from the redundant feedback and exhaustive search, a position fingerprint (PFP)-based mmWave multi-cell beam selection scheme is proposed in this paper. In the proposed scheme, the best beam identity (ID) and the strongest interference beam IDs from adjacent cells of each fingerprint spot are stored in a fingerprint database (FPDB), then the optimal beam and the strongest interference beams can be determined by matching the current PFP of the user equipment (UE) with the PFP in the FPDB instead of exhaustive search, and the orthogonal codes are also allocated to the optimal beam and the strongest interference beams. Simulation results show that the proposed PFP-based beam selection scheme can reduce the computational complexity and inter-cell interference and produce less feedback, and the system sum-rate for the mmWave heterogeneous networks is also improved.https://www.mdpi.com/1424-8220/17/9/2009millimeter wavemulti-cellheterogeneous networksposition fingerprint matchingbeam selection |
| spellingShingle | Zufan Zhang Yanbo Chen Position Fingerprint-Based Beam Selection in Millimeter Wave Heterogeneous Networks Sensors millimeter wave multi-cell heterogeneous networks position fingerprint matching beam selection |
| title | Position Fingerprint-Based Beam Selection in Millimeter Wave Heterogeneous Networks |
| title_full | Position Fingerprint-Based Beam Selection in Millimeter Wave Heterogeneous Networks |
| title_fullStr | Position Fingerprint-Based Beam Selection in Millimeter Wave Heterogeneous Networks |
| title_full_unstemmed | Position Fingerprint-Based Beam Selection in Millimeter Wave Heterogeneous Networks |
| title_short | Position Fingerprint-Based Beam Selection in Millimeter Wave Heterogeneous Networks |
| title_sort | position fingerprint based beam selection in millimeter wave heterogeneous networks |
| topic | millimeter wave multi-cell heterogeneous networks position fingerprint matching beam selection |
| url | https://www.mdpi.com/1424-8220/17/9/2009 |
| work_keys_str_mv | AT zufanzhang positionfingerprintbasedbeamselectioninmillimeterwaveheterogeneousnetworks AT yanbochen positionfingerprintbasedbeamselectioninmillimeterwaveheterogeneousnetworks |