Enhancing IoT Connectivity in Massive MIMO Networks through Systematic Scheduling and Power Control Strategies
Massive MIMO systems can support a large number of Internet of Things (IoT) devices, even if the number of IoT devices exceeds the number of service antennas in a single base station (BS) located at the data center. In order to improve the performance of Massive MIMO with massive IoT connectivity in...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-07-01
|
| Series: | Mathematics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-7390/11/13/3012 |
| _version_ | 1797591211156963328 |
|---|---|
| author | Byung Moo Lee |
| author_facet | Byung Moo Lee |
| author_sort | Byung Moo Lee |
| collection | DOAJ |
| description | Massive MIMO systems can support a large number of Internet of Things (IoT) devices, even if the number of IoT devices exceeds the number of service antennas in a single base station (BS) located at the data center. In order to improve the performance of Massive MIMO with massive IoT connectivity in a BS, simple scheduling and power control schemes can be of great help, but typically, they require high power consumption in the situation of serious shadow fading. In this paper, we try to improve the performance of Massive MIMO with massive IoT connectivity by using the dropping technique that drops the IoT devices that require high power consumption. Several scheduling and power control schemes have been proposed to increase the spectral efficiency (SE) and the energy efficiency (EE) of Massive MIMO systems. By the combination of these schemes with the dropping technique, we show that the performance can be even further increased under some circumstances. There is a dropping coefficient factor (DCF) to determine the IoT devices that should be dropped. This technique gives more benefits to the power control schemes that require higher power consumption. Simulation results and relevant analyses are provided to verify the effectiveness of the proposed technique. |
| first_indexed | 2024-03-11T01:34:15Z |
| format | Article |
| id | doaj.art-7516987b21dc4478b2d6dc73c3663f0b |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-11T01:34:15Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-7516987b21dc4478b2d6dc73c3663f0b2023-11-18T17:04:33ZengMDPI AGMathematics2227-73902023-07-011113301210.3390/math11133012Enhancing IoT Connectivity in Massive MIMO Networks through Systematic Scheduling and Power Control StrategiesByung Moo Lee0Department of Intelligent Mechatronics Engineering and Convergence Engineering for Intelligent Drone, Sejong University, Seoul 05006, Republic of KoreaMassive MIMO systems can support a large number of Internet of Things (IoT) devices, even if the number of IoT devices exceeds the number of service antennas in a single base station (BS) located at the data center. In order to improve the performance of Massive MIMO with massive IoT connectivity in a BS, simple scheduling and power control schemes can be of great help, but typically, they require high power consumption in the situation of serious shadow fading. In this paper, we try to improve the performance of Massive MIMO with massive IoT connectivity by using the dropping technique that drops the IoT devices that require high power consumption. Several scheduling and power control schemes have been proposed to increase the spectral efficiency (SE) and the energy efficiency (EE) of Massive MIMO systems. By the combination of these schemes with the dropping technique, we show that the performance can be even further increased under some circumstances. There is a dropping coefficient factor (DCF) to determine the IoT devices that should be dropped. This technique gives more benefits to the power control schemes that require higher power consumption. Simulation results and relevant analyses are provided to verify the effectiveness of the proposed technique.https://www.mdpi.com/2227-7390/11/13/3012massive connectivityInternet of Thingsenergy efficiencyMassive MIMOscheduling |
| spellingShingle | Byung Moo Lee Enhancing IoT Connectivity in Massive MIMO Networks through Systematic Scheduling and Power Control Strategies Mathematics massive connectivity Internet of Things energy efficiency Massive MIMO scheduling |
| title | Enhancing IoT Connectivity in Massive MIMO Networks through Systematic Scheduling and Power Control Strategies |
| title_full | Enhancing IoT Connectivity in Massive MIMO Networks through Systematic Scheduling and Power Control Strategies |
| title_fullStr | Enhancing IoT Connectivity in Massive MIMO Networks through Systematic Scheduling and Power Control Strategies |
| title_full_unstemmed | Enhancing IoT Connectivity in Massive MIMO Networks through Systematic Scheduling and Power Control Strategies |
| title_short | Enhancing IoT Connectivity in Massive MIMO Networks through Systematic Scheduling and Power Control Strategies |
| title_sort | enhancing iot connectivity in massive mimo networks through systematic scheduling and power control strategies |
| topic | massive connectivity Internet of Things energy efficiency Massive MIMO scheduling |
| url | https://www.mdpi.com/2227-7390/11/13/3012 |
| work_keys_str_mv | AT byungmoolee enhancingiotconnectivityinmassivemimonetworksthroughsystematicschedulingandpowercontrolstrategies |