Energy efficiency of ultra-dense small-cell downlink networks with adaptive cell breathing
- Authors
- Jin, Hu; Wu, Xuelian; Kim, Hyung-sup; Jung, Bang Chul
- Issue Date
- Feb-2018
- Publisher
- INST ENGINEERING TECHNOLOGY-IET
- Keywords
- cellular radio; energy conservation; telecommunication power management; RSSI; stochastic processes; geometry; energy efficiency; ultra-dense small-cell downlink networks; adaptive cell breathing technique; ACB technique; small-cell base stations; transmission power; received signal strength; aggressive BS on-off technique; ABO technique; stochastic geometry
- Citation
- IET COMMUNICATIONS, v.12, no.3, pp.367 - 372
- Indexed
- SCIE
SCOPUS
- Journal Title
- IET COMMUNICATIONS
- Volume
- 12
- Number
- 3
- Start Page
- 367
- End Page
- 372
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/6759
- DOI
- 10.1049/iet-com.2016.1420
- ISSN
- 1751-8628
- Abstract
- The authors propose an adaptive cell-breathing (ACB) technique to improve the energy efficiency (EE) of a downlink cellular network consisting of small-cell base stations (BSs), wherein each BS adaptively adjusts its transmission power such that the received signal strength of the worst-case user is larger than a pre-defined threshold. They also propose an aggressive BS on-off (ABO) technique in which the small-cell BSs having a number of users smaller than a certain value, Nth, are turned off, whereas conventional techniques only turn off the empty BSs. They adopt a stochastic geometry for modelling the locations of both BSs and users. Simulation results show that the ACB technique yields a much better EE than the power on-off technique with a fixed power, including the ABO technique. In particular, the EE of the ACB technique is proportional to (.b) c (c > 0), where.b denotes the BS density and the exponent c denotes the increasing ratio of the EE to.b in the log -log domain. The EE of the ABO technique tends to increase as Nth increases.
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