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New Era in shared cellular networks: Moving into open and virtualized platform
Author(s) -
Narmanlioglu Omer,
Zeydan Engin
Publication year - 2017
Publication title -
international journal of network management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.373
H-Index - 28
eISSN - 1099-1190
pISSN - 1055-7148
DOI - 10.1002/nem.1986
Subject(s) - computer science , radio access network , computer network , cloud computing , cellular network , backhaul (telecommunications) , ran , software defined networking , virtualization , distributed computing , network architecture , core network , network virtualization , operating system , base station , mobile station
Summary Software‐defined networking (SDN) concept provides many features including hardware abstraction, programmable networking and centralized policy control. This allows benefiting from recently developed open source frameworks to build service platforms from a dynamic softwarized ecosystem of networking. There are two major technologies for building the next generation mobile network: Radio Access Network (RAN) sharing and Cloud RAN (C‐RAN). RAN sharing ensures efficient usage of network equipment among multiple mobile network operators (MNOs) and C‐RAN benefits installation, evolution, management, and performance improvements. One of the main benefits that can be used along with these features is dynamic virtualization of RAN and core/backhaul networks to ensure network sharing among multiple MNOs for efficient usage of their network infrastructures. In this work, we propose an SDN‐based C‐RAN architecture managed by C‐RAN controllers, which are integrated with a virtualization controller that is crucial for core/backhaul network sharing of the proposed next generation cellular network architecture. We further provide a use case study of shared mobile architecture for channel‐aware remote radio head (RRH) assignment to multiple MNOs. Two C‐RAN–aided cooperative algorithms, named ANCESTOR and MORGAN , that ensure load balancing among RRHs and better received signal strength levels are provided. Moreover, by selecting MNO assignments judiciously, MORGAN is shown to converge to a pure strategy Nash Equilibrium with high probability in the shared network architecture. The results reveal the proposed methods' performance advantages over static distribution and convergence properties.