Massive MIMO system lower bound spectral efficiency analysis with precoding and perfect CSI
The analytical lower bound of Spectral Efficiency (SE) of downlink transmission of the Massive Multiple Input Multiple Output (Ma-MIMO) system is analyzed. In this paper, we derive some novel and approximate mathematical expressions for the lower bound of the SE of a Ma-MIMO with linear precoding sc...
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| Format: | Article |
| Language: | English |
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KeAi Communications Co., Ltd.
2021-08-01
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| Series: | Digital Communications and Networks |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S235286481930135X |
| _version_ | 1818910351400370176 |
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| author | Tasher Ali Sheikh Joyatri Bora Md Anwar Hussain |
| author_facet | Tasher Ali Sheikh Joyatri Bora Md Anwar Hussain |
| author_sort | Tasher Ali Sheikh |
| collection | DOAJ |
| description | The analytical lower bound of Spectral Efficiency (SE) of downlink transmission of the Massive Multiple Input Multiple Output (Ma-MIMO) system is analyzed. In this paper, we derive some novel and approximate mathematical expressions for the lower bound of the SE of a Ma-MIMO with linear precoding schemes, i.e., Minimum Mean Square Error (MMSE) and Zero-Forcing (ZF). For simulation analysis of the SE, we consider three joint users and antenna scheduling algorithms, namely, the semi-orthogonal, random, and distance-based user scheduling algorithms, whereas the antennas are selected based on Maximum Signal to Noise Ratio (MSNR) with scheduled users. The channel between the user and the transmitter is assumed to have characteristics of Small Scale Fading (SSF) and Large Scale Fading (LSF) with the Rayleigh fading model. We investigate the effect of the variation of transmitting SNR, the number of base station antennas (M), and the radius (R) of the cell area on the SE. We simulate the downlink transmission of Ma-MIMO and compare the simulation and analytical results. It is observed that the trends of variation of both results are similar to the variation of identical factors, and the difference between the simulated and analytical lower bounds of the SE is approximately 1–1.5 bits. The analytical lower bound is smaller than the simulation result. |
| first_indexed | 2024-12-19T22:41:25Z |
| format | Article |
| id | doaj.art-213a3a5b8be54a1abf0e50ed86ac07cd |
| institution | Directory Open Access Journal |
| issn | 2352-8648 |
| language | English |
| last_indexed | 2024-12-19T22:41:25Z |
| publishDate | 2021-08-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Digital Communications and Networks |
| spelling | doaj.art-213a3a5b8be54a1abf0e50ed86ac07cd2022-12-21T20:03:03ZengKeAi Communications Co., Ltd.Digital Communications and Networks2352-86482021-08-0173342351Massive MIMO system lower bound spectral efficiency analysis with precoding and perfect CSITasher Ali Sheikh0Joyatri Bora1Md Anwar Hussain2Corresponding author.; Department of Electronics and Communication Engineering, North Eastern Regional Institute of Science and Technology, Nirjuli, Arunachal Pradesh, 791109, IndiaDepartment of Electronics and Communication Engineering, North Eastern Regional Institute of Science and Technology, Nirjuli, Arunachal Pradesh, 791109, IndiaDepartment of Electronics and Communication Engineering, North Eastern Regional Institute of Science and Technology, Nirjuli, Arunachal Pradesh, 791109, IndiaThe analytical lower bound of Spectral Efficiency (SE) of downlink transmission of the Massive Multiple Input Multiple Output (Ma-MIMO) system is analyzed. In this paper, we derive some novel and approximate mathematical expressions for the lower bound of the SE of a Ma-MIMO with linear precoding schemes, i.e., Minimum Mean Square Error (MMSE) and Zero-Forcing (ZF). For simulation analysis of the SE, we consider three joint users and antenna scheduling algorithms, namely, the semi-orthogonal, random, and distance-based user scheduling algorithms, whereas the antennas are selected based on Maximum Signal to Noise Ratio (MSNR) with scheduled users. The channel between the user and the transmitter is assumed to have characteristics of Small Scale Fading (SSF) and Large Scale Fading (LSF) with the Rayleigh fading model. We investigate the effect of the variation of transmitting SNR, the number of base station antennas (M), and the radius (R) of the cell area on the SE. We simulate the downlink transmission of Ma-MIMO and compare the simulation and analytical results. It is observed that the trends of variation of both results are similar to the variation of identical factors, and the difference between the simulated and analytical lower bounds of the SE is approximately 1–1.5 bits. The analytical lower bound is smaller than the simulation result.http://www.sciencedirect.com/science/article/pii/S235286481930135XFifth-generationSpectral efficiencyMa-MIMOLSF coefficientPrecoding |
| spellingShingle | Tasher Ali Sheikh Joyatri Bora Md Anwar Hussain Massive MIMO system lower bound spectral efficiency analysis with precoding and perfect CSI Digital Communications and Networks Fifth-generation Spectral efficiency Ma-MIMO LSF coefficient Precoding |
| title | Massive MIMO system lower bound spectral efficiency analysis with precoding and perfect CSI |
| title_full | Massive MIMO system lower bound spectral efficiency analysis with precoding and perfect CSI |
| title_fullStr | Massive MIMO system lower bound spectral efficiency analysis with precoding and perfect CSI |
| title_full_unstemmed | Massive MIMO system lower bound spectral efficiency analysis with precoding and perfect CSI |
| title_short | Massive MIMO system lower bound spectral efficiency analysis with precoding and perfect CSI |
| title_sort | massive mimo system lower bound spectral efficiency analysis with precoding and perfect csi |
| topic | Fifth-generation Spectral efficiency Ma-MIMO LSF coefficient Precoding |
| url | http://www.sciencedirect.com/science/article/pii/S235286481930135X |
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