Evolutionary Algorithm Based Capacity Maximization of 5G/B5G Hybrid Pre-Coding Systems
Hybrid pre-coding strategies are considered as a potential solution for combating path loss experienced by Massive MIMO systems operating at millimeter wave frequencies. The partially connected structure is preferred over the fully connected structure due to smaller computational complexity. In orde...
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| Format: | Article |
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MDPI AG
2020-09-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/20/18/5338 |
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| author | Salman Khalid Waqas Bin Abbas Hyung Seok Kim Muhammad Tabish Niaz |
| author_facet | Salman Khalid Waqas Bin Abbas Hyung Seok Kim Muhammad Tabish Niaz |
| author_sort | Salman Khalid |
| collection | DOAJ |
| description | Hybrid pre-coding strategies are considered as a potential solution for combating path loss experienced by Massive MIMO systems operating at millimeter wave frequencies. The partially connected structure is preferred over the fully connected structure due to smaller computational complexity. In order to improve the spectral efficiency of a partially connected hybrid pre-coding architecture, which is one of the requirements of future 5G/B5G systems, this work proposes the application of evolutionary algorithms for joint computation of RF and the digital pre-coder. The evolutionary algorithm based scheme jointly evaluates the RF and digital pre-coder for a partially connected hybrid structure by taking into account the current RF chain for computations and therefore it is not based on interference cancellation from all other RF chains as in the case of successive interference cancellation (SIC). The evolutionary algorithm, i.e., Artificial Bee Colony (BEE) based pre-coding scheme outperforms other popular evolutionary algorithms as well as the SIC based pre-coding scheme in terms of spectral efficiency. In addition, the proposed algorithm is not overly sensitive to variations in channel conditions. |
| first_indexed | 2024-03-10T16:15:34Z |
| format | Article |
| id | doaj.art-5308035d0351446ea4093e508ea1c463 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T16:15:34Z |
| publishDate | 2020-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-5308035d0351446ea4093e508ea1c4632023-11-20T14:07:34ZengMDPI AGSensors1424-82202020-09-012018533810.3390/s20185338Evolutionary Algorithm Based Capacity Maximization of 5G/B5G Hybrid Pre-Coding SystemsSalman Khalid0Waqas Bin Abbas1Hyung Seok Kim2Muhammad Tabish Niaz3Department of Electrical Engineering, National University of Computer and Emerging Science, Islamabad 44000, PakistanDepartment of Electrical Engineering, National University of Computer and Emerging Science, Islamabad 44000, PakistanDepartment of Intelligent Mechatronics Engineering, Sejong University, Seoul 05006, KoreaDepartment of Intelligent Mechatronics Engineering, Sejong University, Seoul 05006, KoreaHybrid pre-coding strategies are considered as a potential solution for combating path loss experienced by Massive MIMO systems operating at millimeter wave frequencies. The partially connected structure is preferred over the fully connected structure due to smaller computational complexity. In order to improve the spectral efficiency of a partially connected hybrid pre-coding architecture, which is one of the requirements of future 5G/B5G systems, this work proposes the application of evolutionary algorithms for joint computation of RF and the digital pre-coder. The evolutionary algorithm based scheme jointly evaluates the RF and digital pre-coder for a partially connected hybrid structure by taking into account the current RF chain for computations and therefore it is not based on interference cancellation from all other RF chains as in the case of successive interference cancellation (SIC). The evolutionary algorithm, i.e., Artificial Bee Colony (BEE) based pre-coding scheme outperforms other popular evolutionary algorithms as well as the SIC based pre-coding scheme in terms of spectral efficiency. In addition, the proposed algorithm is not overly sensitive to variations in channel conditions.https://www.mdpi.com/1424-8220/20/18/53385G/B5G communication systemsachievable rateevolutionary algorithmshybrid pre-codinginterference cancellationmillimeter wave |
| spellingShingle | Salman Khalid Waqas Bin Abbas Hyung Seok Kim Muhammad Tabish Niaz Evolutionary Algorithm Based Capacity Maximization of 5G/B5G Hybrid Pre-Coding Systems Sensors 5G/B5G communication systems achievable rate evolutionary algorithms hybrid pre-coding interference cancellation millimeter wave |
| title | Evolutionary Algorithm Based Capacity Maximization of 5G/B5G Hybrid Pre-Coding Systems |
| title_full | Evolutionary Algorithm Based Capacity Maximization of 5G/B5G Hybrid Pre-Coding Systems |
| title_fullStr | Evolutionary Algorithm Based Capacity Maximization of 5G/B5G Hybrid Pre-Coding Systems |
| title_full_unstemmed | Evolutionary Algorithm Based Capacity Maximization of 5G/B5G Hybrid Pre-Coding Systems |
| title_short | Evolutionary Algorithm Based Capacity Maximization of 5G/B5G Hybrid Pre-Coding Systems |
| title_sort | evolutionary algorithm based capacity maximization of 5g b5g hybrid pre coding systems |
| topic | 5G/B5G communication systems achievable rate evolutionary algorithms hybrid pre-coding interference cancellation millimeter wave |
| url | https://www.mdpi.com/1424-8220/20/18/5338 |
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