Fast Beam Search for Massive MIMO Based on Mainlobe Overlapping State of Training Beam
To reduce beam search complexity without decreasing feedback efficiency for millimeter-wave communication in the LoS environment, this paper proposes a fast beam search scheme based on joint judgment, which requires a masterly design of the training beams and let their mainlobe overlap according to...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2019-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8720162/ |
| _version_ | 1818667710427430912 |
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| author | Weixia Zou Mingyang Cui Chao Guo |
| author_facet | Weixia Zou Mingyang Cui Chao Guo |
| author_sort | Weixia Zou |
| collection | DOAJ |
| description | To reduce beam search complexity without decreasing feedback efficiency for millimeter-wave communication in the LoS environment, this paper proposes a fast beam search scheme based on joint judgment, which requires a masterly design of the training beams and let their mainlobe overlap according to certain rules. As a consequence, its state utilization efficiency has been improved to 100% while keeping feedback efficiency is still 100%. In this paper, through theoretical analysis, we find that to encode the index of every subinterval A<sub>q</sub> using the Gray mapping can decrease the possibility and the impact of misestimating, compared with using a binary index, which is adopted. The transceiver emits the training beam in turn and then jointly determines optimal communication beam pair according to the relationship between the receiving power and the threshold. The simulation results show that our proposed scheme is more efficient and its search complexity has been further decreased while its FE remains 100%. Especially, this method has more obvious advantages in multi-user simultaneously beam search scenarios. |
| first_indexed | 2024-12-17T06:24:45Z |
| format | Article |
| id | doaj.art-15309235e6884a02914b089fb1225f5f |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-17T06:24:45Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-15309235e6884a02914b089fb1225f5f2022-12-21T22:00:19ZengIEEEIEEE Access2169-35362019-01-017660076601910.1109/ACCESS.2019.29182818720162Fast Beam Search for Massive MIMO Based on Mainlobe Overlapping State of Training BeamWeixia Zou0Mingyang Cui1https://orcid.org/0000-0003-1398-702XChao Guo2Key Laboratory of Universal Wireless Communications, MOE, Beijing University of Posts and Telecommunications, Beijing, ChinaKey Laboratory of Universal Wireless Communications, MOE, Beijing University of Posts and Telecommunications, Beijing, ChinaKey Laboratory of Universal Wireless Communications, MOE, Beijing University of Posts and Telecommunications, Beijing, ChinaTo reduce beam search complexity without decreasing feedback efficiency for millimeter-wave communication in the LoS environment, this paper proposes a fast beam search scheme based on joint judgment, which requires a masterly design of the training beams and let their mainlobe overlap according to certain rules. As a consequence, its state utilization efficiency has been improved to 100% while keeping feedback efficiency is still 100%. In this paper, through theoretical analysis, we find that to encode the index of every subinterval A<sub>q</sub> using the Gray mapping can decrease the possibility and the impact of misestimating, compared with using a binary index, which is adopted. The transceiver emits the training beam in turn and then jointly determines optimal communication beam pair according to the relationship between the receiving power and the threshold. The simulation results show that our proposed scheme is more efficient and its search complexity has been further decreased while its FE remains 100%. Especially, this method has more obvious advantages in multi-user simultaneously beam search scenarios.https://ieeexplore.ieee.org/document/8720162/Fast beam searchmillimeter-waveGray mappingstate utilization efficiency |
| spellingShingle | Weixia Zou Mingyang Cui Chao Guo Fast Beam Search for Massive MIMO Based on Mainlobe Overlapping State of Training Beam IEEE Access Fast beam search millimeter-wave Gray mapping state utilization efficiency |
| title | Fast Beam Search for Massive MIMO Based on Mainlobe Overlapping State of Training Beam |
| title_full | Fast Beam Search for Massive MIMO Based on Mainlobe Overlapping State of Training Beam |
| title_fullStr | Fast Beam Search for Massive MIMO Based on Mainlobe Overlapping State of Training Beam |
| title_full_unstemmed | Fast Beam Search for Massive MIMO Based on Mainlobe Overlapping State of Training Beam |
| title_short | Fast Beam Search for Massive MIMO Based on Mainlobe Overlapping State of Training Beam |
| title_sort | fast beam search for massive mimo based on mainlobe overlapping state of training beam |
| topic | Fast beam search millimeter-wave Gray mapping state utilization efficiency |
| url | https://ieeexplore.ieee.org/document/8720162/ |
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