Base Station Operation and User Association Mechanisms for Energy-Delay Tradeoffs in Green Cellular Networks

By Kyunghwan Son, Hongseok Kim, Yung Yi, Bhaskar Krishnamachari. IEEE Journal on Selected Areas in Communications, 2011

501 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/4fda3112a78c3b3ceb21b4c54b8dd6e1b5f08be8

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Qingqing Wu
2. Geoffrey Y. Li
3. Shunqing Zhang
4. Shugong Xu
5. Rui Zhang
6. Tony Q. S. Quek
7. Marios Kountouris
8. Yaohua Sun

In Electrical and Electronic Engineering

1. Qingqing Wu
2. Rui Zhang
3. Geoffrey Y. Li
4. Shunqing Zhang
5. Shugong Xu
6. Yaohua Sun
7. Mugen Peng
8. Yuzhen Huang

Citations in the corpus

• Fundamental Green Tradeoffs: Progresses, Challenges, and Impacts on 5G Networks (2016, methodology): “[145]–[147] SE-EE, DE-EE User Scheduling DL Dynamic user association and load balancing for cell cooperation”
• Energy-Efficient Base-Stations Sleep-Mode Techniques in Green Cellular Networks: A Survey (2015, background): “A similar but more complicated system cost function considering flow-level performance and system energy consumption is proposed in [105].”
• Ultra-Dense HetNets Meet Big Data: Green Frameworks, Techniques, and Approaches (2017, methodology): “There have been some works to address the BS operation problems from different perspectives [8], [12]–[14].”
• Dynamic Base Station Switching-On/Off Strategies for Green Cellular Networks (2013, background): “So there exist some works in literature [1], [8], [25], where the authors proposed similar forms of switching on/off algorithms based on the system load (or sometimes called the utilization) in slightly different formulations.”
• Cost Efficient Resource Management in Fog Computing Supported Medical Cyber-Physical System (2017, background): “[14] develop a theoretical framework for BS energy saving that encompasses dynamic BS operation and”
• Application of Machine Learning in Wireless Networks: Key Techniques and Open Issues (2018, background): “Assuming a full knowledge of traffic loads, authors in [155] greedily turn off as many as BSs to get the optimal BS switching solution, which is taken by [18] as a comparison scheme to verify the effectiveness of transfer learning based BS switching.”
• Energy Efficient Heterogeneous Cellular Networks (2013, background): “These small cells can potentially improve spatial reuse and coverage by allowing future cellular systems to achieve higher data rates, while retaining seamless connectivity and mobility in cellular networks.”