Precoding and Beamforming Techniques in mmWave-Massive MIMO: Performance Assessment
Massive MIMO and mmWave communication are the technologies for achieving 5G design goals. Fortunately, these two technologies share a symbiotic integration. As a result, amalgamating mmWave communications with massive MIMO forms,mmWave-massive MIMO,” which significantly improves spectral...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9705623/ |
| _version_ | 1824045710829420544 |
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| author | Tewelgn Kebede Yihenew Wondie Johannes Steinbrunn Hailu Belay Kassa Kevin T. Kornegay |
| author_facet | Tewelgn Kebede Yihenew Wondie Johannes Steinbrunn Hailu Belay Kassa Kevin T. Kornegay |
| author_sort | Tewelgn Kebede |
| collection | DOAJ |
| description | Massive MIMO and mmWave communication are the technologies for achieving 5G design goals. Fortunately, these two technologies share a symbiotic integration. As a result, amalgamating mmWave communications with massive MIMO forms,mmWave-massive MIMO,” which significantly improves spectral and energy efficiency. It also achieves high multiplexing gains and increases mobile network capacity. However, massive MIMO, mmWave communications, and mmWave-massive MIMO systems have been studied independently. Consequently, this article explores the ideas, performances, comparisons, and discussions of these three 5G technologies jointly, considering their precoding and beamforming methods. On the other hand, the complexity of these technologies increases when a large number of antennas and radio frequencies (RFs) are used. Thus, several investigations are going on to search for the appropriate precoding and beamforming strategies with low cost, power, and complexity. Therefore, massive MIMO linear precoding techniques such as zero-forcing, maximum ratio transmission, regularized zero-forcing, truncated polynomial expansion and phased zero forcing are addressed in this work. In addition, the most common non-linear precoding schemes: dirty-paper coding, Tomlinson-Harashima, and vector perturbation, are presented. Furthermore, a detailed discussion of the beamforming techniques called analog, digital, and hybrid analog-digital beamforming schemes is included. We also examine the potential of hybrid analog-digital beamforming with its fully-connected and sub-connected architecture approaches in making mmWave massive MIMO a reality. We evaluate their performance with the parameters: bit error rate, signal to noise ratio, complexity, spectral efficiency, and energy efficiency. According to the analytical and simulation results, the partially-connected hybrid analog/digital beamforming architecture offers better all-over performance for mmWave-Massive MIMO communications by compromising: power consumption, cost, complexity, and performance. Finally, the potential future directions in mmWave-massive MIMO precoding and beamforming challenges are addressed. |
| first_indexed | 2024-12-23T00:28:13Z |
| format | Article |
| id | doaj.art-5152fb33151040658c1f189988036cea |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-23T00:28:13Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-5152fb33151040658c1f189988036cea2022-12-21T18:07:01ZengIEEEIEEE Access2169-35362022-01-0110163651638710.1109/ACCESS.2022.31493019705623Precoding and Beamforming Techniques in mmWave-Massive MIMO: Performance AssessmentTewelgn Kebede0https://orcid.org/0000-0002-6494-2609Yihenew Wondie1https://orcid.org/0000-0003-4802-360XJohannes Steinbrunn2Hailu Belay Kassa3Kevin T. Kornegay4Addis Ababa Institute of Technology, Addis Ababa University, Addis Ababa, EthiopiaAddis Ababa Institute of Technology, Addis Ababa University, Addis Ababa, EthiopiaFaculty of Electrical Engineering, Kempten University of Applied Science, Kempten, GermanyDepartment of Electrical and Computer Engineering, Morgan State University, Baltimore, MD, USADepartment of Electrical and Computer Engineering, Morgan State University, Baltimore, MD, USAMassive MIMO and mmWave communication are the technologies for achieving 5G design goals. Fortunately, these two technologies share a symbiotic integration. As a result, amalgamating mmWave communications with massive MIMO forms,mmWave-massive MIMO,” which significantly improves spectral and energy efficiency. It also achieves high multiplexing gains and increases mobile network capacity. However, massive MIMO, mmWave communications, and mmWave-massive MIMO systems have been studied independently. Consequently, this article explores the ideas, performances, comparisons, and discussions of these three 5G technologies jointly, considering their precoding and beamforming methods. On the other hand, the complexity of these technologies increases when a large number of antennas and radio frequencies (RFs) are used. Thus, several investigations are going on to search for the appropriate precoding and beamforming strategies with low cost, power, and complexity. Therefore, massive MIMO linear precoding techniques such as zero-forcing, maximum ratio transmission, regularized zero-forcing, truncated polynomial expansion and phased zero forcing are addressed in this work. In addition, the most common non-linear precoding schemes: dirty-paper coding, Tomlinson-Harashima, and vector perturbation, are presented. Furthermore, a detailed discussion of the beamforming techniques called analog, digital, and hybrid analog-digital beamforming schemes is included. We also examine the potential of hybrid analog-digital beamforming with its fully-connected and sub-connected architecture approaches in making mmWave massive MIMO a reality. We evaluate their performance with the parameters: bit error rate, signal to noise ratio, complexity, spectral efficiency, and energy efficiency. According to the analytical and simulation results, the partially-connected hybrid analog/digital beamforming architecture offers better all-over performance for mmWave-Massive MIMO communications by compromising: power consumption, cost, complexity, and performance. Finally, the potential future directions in mmWave-massive MIMO precoding and beamforming challenges are addressed.https://ieeexplore.ieee.org/document/9705623/Beamforminghybridmassive MIMOmmWavemmWave-massive MIMOprecoding |
| spellingShingle | Tewelgn Kebede Yihenew Wondie Johannes Steinbrunn Hailu Belay Kassa Kevin T. Kornegay Precoding and Beamforming Techniques in mmWave-Massive MIMO: Performance Assessment IEEE Access Beamforming hybrid massive MIMO mmWave mmWave-massive MIMO precoding |
| title | Precoding and Beamforming Techniques in mmWave-Massive MIMO: Performance Assessment |
| title_full | Precoding and Beamforming Techniques in mmWave-Massive MIMO: Performance Assessment |
| title_fullStr | Precoding and Beamforming Techniques in mmWave-Massive MIMO: Performance Assessment |
| title_full_unstemmed | Precoding and Beamforming Techniques in mmWave-Massive MIMO: Performance Assessment |
| title_short | Precoding and Beamforming Techniques in mmWave-Massive MIMO: Performance Assessment |
| title_sort | precoding and beamforming techniques in mmwave massive mimo performance assessment |
| topic | Beamforming hybrid massive MIMO mmWave mmWave-massive MIMO precoding |
| url | https://ieeexplore.ieee.org/document/9705623/ |
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