Simulation-based evaluation of energy efficiency for millimeter-wave network

Author:

Suzuyama Taku1,Ohue Hiroshi1,Imaizumi Satoshi1,Shimizu Noriyuki1,Asanuma Tsutomu1,Asano Hiroaki1

Affiliation:

1. Technology Research & Development Division, Panasonic Connect

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

General Medicine

Reference13 articles.

1. [1] H. Zhang, S. Huang, C. Jiang, K. Long, V.C.M. Leung, and H.V. Poor, “Energy efficient user association and power allocation in millimeter-wave-based ultra dense networks with energy harvesting base stations,” IEEE J. Sel. Areas Commun., vol. 35, no. 9, pp. 1936-1947, Sept. 2017. DOI: 10.1109/JSAC.2017.2720898

2. [2] J. Gui and X. Dai, “Stabilizing mmwave backhaul energy efficiency for vehicle-mounted access points by Q-learning-based scheme,” Wireless Personal Communications, vol. 121, no. 4, pp. 2885-2909, 2021. DOI: 10.1007/s11277-021-08854-w

3. [3] H.S. Dhillon, R.K. Ganti, F. Baccelli, and J.G. Andrews, “Modeling and analysis of K-tier downlink heterogeneous cellular networks,” IEEE J. Sel. Areas Commun., vol 30, no. 3, pp. 550-560, April 2012. DOI: 10.1109/JSAC.2012.120405

4. [4] IEEE 802.11 Working Group, “IEEE Standard for Information Technology-Telecommunications and Information Exchange between Systems-Local and Metropolitan Area Networks-Specific Requirements-Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications Amendment 3: Enhancements for Very High Throughput in the 60 GHz Band,” IEEE Std, 802.11ad, 2012.

5. [5] 3rd Generation Partnership Project; Technical Specification Group Services and System Aspects, “System architecture for the 5G System (5GS); Stage 2,” 3GPP TS23.501, V17.5.0, June 2022.

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