Self-Adaptive Scheduling of Base Transceiver Stations in Green 5G Networks | Zendy

Uzzal Kumar Dutta | Zendy; Md Abdur Razzaque | Zendy; M. Abdullah Al-Wadud | Zendy; Md Saiful Islam | Zendy; M. Shamim Hossain | Zendy; B. B. Gupta | Zendy

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Self-Adaptive Scheduling of Base Transceiver Stations in Green 5G Networks

Author(s) -

Uzzal Kumar Dutta,

Md Abdur Razzaque,

M. Abdullah Al-Wadud,

Md Saiful Islam,

M. Shamim Hossain,

B. B. Gupta

Publication year - 2018

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2018.2799603

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

In this paper, we design self-adaptive scheduling (SAS) algorithms for base transceiver stations (BTSs) of 5G networks to improve energy efficiency, reduce carbon footprint, and develop a self-sustainable green cellular network. In the SAS algorithm, a BTS switches among its operating states (active, turned-off, and sleep), thereby exploiting the traffic loads of the BTS and the single-hop neighbor BTSs thereof. The dynamic settings of traffic thresholds help the SAS system in achieving a high degree of cooperation among the neighborhood BTSs, which in turn increases the energy savings of the network. Each active SAS BTS independently and dynamically decides in determining its operation state, thus make our proposed SAS algorithms fully distributed. Results from a simulation conducted in network simulator version 3 show that BTS scheduling significantly influences cellular networks, and the proposed SAS algorithm can significantly increase the energy savings compared with state-of-the-art protocols.

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