Radio access network slicing based on C/U plane separation

Zhao, Hui; Zhao, Liqiang; Liang, Kai; Pan, Chengkang

doi:10.1109/cc.2017.8246330

Cited by 6 publications

(7 citation statements)

References 9 publications

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“…Genetic algorithm [27] Bandwidth slicing Stackelberg game approach [14] RAN runtime slicing [15] End-to-end Cloud-native approach [16] End-to-end 5GPP Generic 5G architectural framework [17] [18] RAN slicing at multiple levels [14] [19] End-to-end [20] RAN slicing using C/U separation [28] [21] End-to-end Device-triggered slice selection [22] RAN slicing to the use cases. The publications failed to identify use cases for network slicing because network slicing is in its infancy, and the authors may have deemed use cases as unimportant in this scenario.…”

Section: Discussionmentioning

confidence: 99%

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Network slicing: a next generation 5G perspective

Subedi

Alsadoon

Prasad

et al. 2021

J Wireless Com Network

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Fifth-generation (5G) wireless networks are projected to bring a major transformation to the current fourth-generation network to support the billions of devices that will be connected to the Internet. 5G networks will enable new and powerful capabilities to support high-speed data rates, better connectivity and system capacity that are critical in designing applications in virtual reality, augmented reality and mobile online gaming. The infrastructure of a network that can support stringent application requirements needs to be highly dynamic and flexible. Network slicing can provide these dynamic and flexible characteristics to a network architecture. Implementing network slicing in 5G requires domain modification of the preexisting network architecture. A network slicing architecture is proposed for an existing 5G network with the aim of enhancing network dynamics and flexibility to support modern network applications. To enable network slicing in a 5G network, we established the virtualisation of the underlying physical 5G infrastructure by utilising technological advancements, such as software-defined networking and network function virtualisation. These virtual networks can fulfil the requirement of multiple use cases as required by creating slices of these virtual networks. Thus, abstracting from the physical resources to create virtual networks and then applying network slicing on these virtual networks enable the 5G network to address the increased demands for high-speed communication.

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Section: Discussionmentioning

confidence: 99%

“…The authors in [20] proposed a RAN slicing technique based on separation of control and user planes. The authors implemented the proposed architecture to transmit control data at a low frequency and user data at a high frequency.…”

Section: Literature Reviewmentioning

confidence: 99%

Network slicing: a next generation 5G perspective

Subedi

Alsadoon

Prasad

et al. 2021

J Wireless Com Network

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“…Because the TBSs are responsible for the high speed data transmissions, we analyze the energy efficiency [9][10] of the UP, which is defined by η E = ASE PCA . The ASE is quantified in terms of b/s/Hz/m 2 , while PCA is the transmission power consumption per unit area (PCA) in W/m 2 , both of which will be explained in the next section.…”

Section: Channel Model For the User Planementioning

confidence: 99%

“…According to (9), given a predefined threshold x 0 , the coverage probability of a user served by a LoS TBS is given by…”

Section: B Energy Efficiency Of the User Planementioning

confidence: 99%

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Performance Analysis of Cellular Radio Access Networks Relying on Control- and User-Plane Separation

Liang

Liu

Zhao

et al. 2019

IEEE Trans. Veh. Technol.

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In a cellular radio access network (RAN) relying on control-and user-plane separation, control base stations (CBSs) form the control plane (CP) and take care of control coverage as well as low speed data delivery. In contrast, traffic base stations (TBSs) in the user plane (UP) are used for transmitting high speed data. Based on queuing theory and stochastic geometry, we derive the coverage probability of the CP under non-line-ofsight (NLoS) transmissions, and derive the energy efficiency of the UP under coexisting line-of-sight (LoS) and NLoS propagation modes. Numerical results show that when the traffic load is high, the coverage probability of the CP increases with the increasing CBSs' data rate or the density of CBSs. We also found that the maximum energy efficiency of the UP can be achieved by optimizing the TBS density, while achieving a high area spectral efficiency.

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