Energy-Efficient CoMP Joint Transmission in Hybrid-Powered mmWave Networksopen access
- Authors
- Kim, Seung-Yeon; Ko, Haneul
- Issue Date
- 2022
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- Keywords
- hybrid-power; energy efficiency; Millimeter wave communication; Renewable energy sources; Energy efficiency; Energy consumption; Stochastic processes; Cellular networks; Probability; 5G mobile communication; Millimeter wave; coordinated multi-point transmission; 5G
- Citation
- IEEE ACCESS, v.10, pp 104793 - 104800
- Pages
- 8
- Indexed
- SCIE
SCOPUS
- Journal Title
- IEEE ACCESS
- Volume
- 10
- Start Page
- 104793
- End Page
- 104800
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/145570
- DOI
- 10.1109/ACCESS.2022.3211435
- ISSN
- 2169-3536
- Abstract
- In the downlink of millimeter wave (mmWave) cellular networks, coordinated multi-point transmission (CoMP) with the joint transmission (JT) strategy can achieve a higher data rate at cell edge by multiple desired signals. However, since cooperative transmissions among multiple cells lead to increased energy consumption for these cells, an energy efficient CoMP-JT strategy is required. In this paper, we propose an energy efficient CoMP-JT (EE-CoMP) scheme with hybrid power, where a small cell base station (SC) can use both renewable power and grid power. In EE-CoMP, when the multiple neighboring SCs conduct a cooperative transmission, these SCs determine whether or not to conduct CoMP-JT in a distributed manner. To minimize the grid energy consumption of SCs while maintaining the outage probability, we consider a stochastic game model with constrains for an EE-CoMP based system. In this way, the policy for conducting CoMP-JT can be obtained by applying a best response algorithm. Evaluation results show that EE-CoMP can reduce the grid energy consumption by 80% compared with a probability-based scheme while providing a sufficiently target outage probability (e.g., 0.1).
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Collections - College of Science and Technology > Department of Computer Convergence Software > 1. Journal Articles
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