An Energy-Efficient Multi-Level Sleep Strategy for Periodic Uplink Transmission in Industrial Private 5G Networks
This paper proposes an energy-efficient multi-level sleep mode control for periodic transmission (MSC-PUT) in private fifth-generation (5G) networks. In general, private 5G networks meet IIoT requirements but face rising energy consumption due to dense base station (BS) deployment, particularly impa...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-11-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/23/22/9070 |
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| author | Taehwa Kim Seungjin Lee Hyungwoo Choi Hong-Shik Park Junkyun Choi |
| author_facet | Taehwa Kim Seungjin Lee Hyungwoo Choi Hong-Shik Park Junkyun Choi |
| author_sort | Taehwa Kim |
| collection | DOAJ |
| description | This paper proposes an energy-efficient multi-level sleep mode control for periodic transmission (MSC-PUT) in private fifth-generation (5G) networks. In general, private 5G networks meet IIoT requirements but face rising energy consumption due to dense base station (BS) deployment, particularly impacting operating expenses (OPEX). An approach of BS sleep mode has been studied to reduce energy consumption, but there has been insufficient consideration for the periodic uplink transmission of industrial Internet of Things (IIoT) devices. Additionally, 5G New Reno’s synchronization signal interval limits the effectiveness of the deepest sleep mode in reducing BS energy consumption. By addressing this issue, the aim of this paper is to propose an energy-efficient multi-level sleep mode control for periodic uplink transmission to improve the energy efficiency of BSs. In advance, we develop an energy-efficient model that considers the trade-off between throughput impairment caused by increased latency and energy saving by sleep mode operation for IIoT’s periodic uplink transmission. Then, we propose an approach based on proximal policy optimization (PPO) to determine the deep sleep mode of BSs, considering throughput impairment and energy efficiency. Our simulation results verify the proposed MSC-PUT algorithm’s effectiveness in terms of throughput, energy saving, and energy efficiency. Specifically, we verify that our proposed MSC-PUT enhances energy efficiency by nearly <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>27.5</mn><mo>%</mo></mrow></semantics></math></inline-formula> when compared to conventional multi-level sleep operation and consumes less energy at <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>75.21</mn><mo>%</mo></mrow></semantics></math></inline-formula> of the energy consumed by the conventional method while incurring a throughput impairment of nearly <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>4.2</mn><mo>%</mo></mrow></semantics></math></inline-formula>. Numerical results show that the proposed algorithm can significantly reduce the energy consumption of BSs accounting for periodic uplink transmission of IIoT devices. |
| first_indexed | 2024-03-09T16:28:18Z |
| format | Article |
| id | doaj.art-45ad011d4959491ca05686b8812203d7 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T16:28:18Z |
| publishDate | 2023-11-01 |
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| series | Sensors |
| spelling | doaj.art-45ad011d4959491ca05686b8812203d72023-11-24T15:05:15ZengMDPI AGSensors1424-82202023-11-012322907010.3390/s23229070An Energy-Efficient Multi-Level Sleep Strategy for Periodic Uplink Transmission in Industrial Private 5G NetworksTaehwa Kim0Seungjin Lee1Hyungwoo Choi2Hong-Shik Park3Junkyun Choi4School of Information and Communication Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of KoreaInstitute for IT Convergence, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of KoreaSchool of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of KoreaSchool of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of KoreaSchool of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of KoreaThis paper proposes an energy-efficient multi-level sleep mode control for periodic transmission (MSC-PUT) in private fifth-generation (5G) networks. In general, private 5G networks meet IIoT requirements but face rising energy consumption due to dense base station (BS) deployment, particularly impacting operating expenses (OPEX). An approach of BS sleep mode has been studied to reduce energy consumption, but there has been insufficient consideration for the periodic uplink transmission of industrial Internet of Things (IIoT) devices. Additionally, 5G New Reno’s synchronization signal interval limits the effectiveness of the deepest sleep mode in reducing BS energy consumption. By addressing this issue, the aim of this paper is to propose an energy-efficient multi-level sleep mode control for periodic uplink transmission to improve the energy efficiency of BSs. In advance, we develop an energy-efficient model that considers the trade-off between throughput impairment caused by increased latency and energy saving by sleep mode operation for IIoT’s periodic uplink transmission. Then, we propose an approach based on proximal policy optimization (PPO) to determine the deep sleep mode of BSs, considering throughput impairment and energy efficiency. Our simulation results verify the proposed MSC-PUT algorithm’s effectiveness in terms of throughput, energy saving, and energy efficiency. Specifically, we verify that our proposed MSC-PUT enhances energy efficiency by nearly <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>27.5</mn><mo>%</mo></mrow></semantics></math></inline-formula> when compared to conventional multi-level sleep operation and consumes less energy at <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>75.21</mn><mo>%</mo></mrow></semantics></math></inline-formula> of the energy consumed by the conventional method while incurring a throughput impairment of nearly <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>4.2</mn><mo>%</mo></mrow></semantics></math></inline-formula>. Numerical results show that the proposed algorithm can significantly reduce the energy consumption of BSs accounting for periodic uplink transmission of IIoT devices.https://www.mdpi.com/1424-8220/23/22/9070private 5Genergy efficiencysmall-cell base stationinternet of thingsreinforcement learning |
| spellingShingle | Taehwa Kim Seungjin Lee Hyungwoo Choi Hong-Shik Park Junkyun Choi An Energy-Efficient Multi-Level Sleep Strategy for Periodic Uplink Transmission in Industrial Private 5G Networks Sensors private 5G energy efficiency small-cell base station internet of things reinforcement learning |
| title | An Energy-Efficient Multi-Level Sleep Strategy for Periodic Uplink Transmission in Industrial Private 5G Networks |
| title_full | An Energy-Efficient Multi-Level Sleep Strategy for Periodic Uplink Transmission in Industrial Private 5G Networks |
| title_fullStr | An Energy-Efficient Multi-Level Sleep Strategy for Periodic Uplink Transmission in Industrial Private 5G Networks |
| title_full_unstemmed | An Energy-Efficient Multi-Level Sleep Strategy for Periodic Uplink Transmission in Industrial Private 5G Networks |
| title_short | An Energy-Efficient Multi-Level Sleep Strategy for Periodic Uplink Transmission in Industrial Private 5G Networks |
| title_sort | energy efficient multi level sleep strategy for periodic uplink transmission in industrial private 5g networks |
| topic | private 5G energy efficiency small-cell base station internet of things reinforcement learning |
| url | https://www.mdpi.com/1424-8220/23/22/9070 |
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