Open AccessEnergy‐efficient BBU pool virtualisation for C‐RAN with quality of service guarantees
Author(s) -
Abdelhakam Mostafa M.,
Elmesalawy Mahmoud M.,
Elhattab Mohamed K.,
Esmat Haitham H.
Publication year - 2020
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2019.0187
Subject(s) - computer science , c ran , quality of service , cloud computing , energy consumption , heuristic , virtualization , transmission (telecommunications) , computer network , radio access network , baseband , distributed computing , base station , bandwidth (computing) , telecommunications , mobile station , ecology , artificial intelligence , biology , operating system
Cloud radio access network (C‐RAN) has been introduced as a promising network paradigm for improving the spectral and energy efficiency of next‐generation mobile systems. In C‐RAN, the computation resources of the centralised baseband units (BBUs) can be virtualised and dynamically shared among cells for energy‐efficient BBU pool utilisation. In this study, a BBU virtualisation scheme is proposed to minimise the total power consumption in the BBU pool subject to constraints on users’ quality of service in terms of real‐time requirements, individual fronthaul capacity and BBU capacity. As the BBU processing time and transmission delay for each user data can be compromised to meet the user's real‐time requirements while minimising the BBU power consumption, a priori user association phase is proposed and formulated as an optimisation problem to maximise the users’ transmission rate, and hence minimising their transmission delay. Then, the BBU processing allocation phase is formulated as a bin‐packing problem to minimise the overall power consumption in the BBU pool. Since this problem is combinatorial, a heuristic algorithm is proposed based on best‐fit‐decreasing algorithm to solve it. Extensive simulations show that the proposed scheme outperforms the comparable ones in terms of power consumption with reduction up to 33%.