SoftSLICE: Policy-Based Dynamic Spectrum Slicing in 5G Cellular Networks

Gebremariam, Anteneh A.; Chowdhury, Mainak; Usman, Muhammad; Goldsmith, Andrea; Granelli, Fabrizio

doi:10.1109/icc.2018.8422148

Cited by 12 publications

(12 citation statements)

References 6 publications

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“…Following these observations, recent work has proposed slicing schemes to address these issues. In [9], the authors propose a resource sharing agreement policy that accounts for the correlation among data to reduce the number of dropped packets. The same authors design an interference management module to enable resource isolation.…”

Section: Related Workmentioning

confidence: 99%

“…Problem constraints define the set of feasible allocation policy solutions according to the employed mixed-numerology RB model. In detail, constraint (9) ensures that all MNVOs receive a number of RBs expressed as groups of F m contiguous RBs according to the spectrum slice m,b . Constraints (10) and (11) account for the multiplexing of RBs with different numerologies represented through the RB allocation indicator.…”

Section: B Optimal Solutionmentioning

confidence: 99%

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Interference Minimization in 5G Physical-Layer Network Slicing

Zambianco

Verticale

2020

IEEE Trans. Commun.

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The interference resulting from densification of access points and the coexistence of different numerologies within the same spectrum severely hinders inter-slice isolation. We propose a slice allocation policy that enforces inter-slice isolation by minimizing the inter-slice interference suffered by each virtual operator. In detail, we design a binary quadratic non-convex optimization problem that minimizes i) the interslice interference generated by interfering base stations and ii) the inter-slice interference generated by the multiplexing of spectrum slices having different numerologies. We also provide a heuristic algorithm to render the solution scalable in practical scenarios. We assess the performance of both approaches by evaluating the signal-to-interference-plus-noise ratio (SINR) associated to each slice through simulations. Results reveal that the heuristic algorithm provides a solution comparable with the optimal one on different minimization scenarios. Moreover, a considerable SINR improvement is observed with respect to a base-line scheme that does not account for inter-slice interference.

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Section: Related Workmentioning

confidence: 99%

Section: B Optimal Solutionmentioning

confidence: 99%

Interference Minimization in 5G Physical-Layer Network Slicing

Zambianco

Verticale

2020

IEEE Trans. Commun.

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“…To cope with these issues, it is necessary to perform dynamic spectrum slicing. In [97], Gebremariam et al presented a policy-based dynamic spectrum slicing scheme that considers network traffic variations. The distribution of user traffic is modeled using a Markov process, which has benefit of considering the correlations between consecutive points of user traffic.…”

Section: Dynamic Spectrum Slicingmentioning

confidence: 99%

Network Slicing: Recent Advances, Taxonomy, Requirements, and Open Research Challenges

et al. 2020

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Fifth-generation (5G) and beyond networks are envisioned to provide multi-services with diverse specifications. Network slicing is identified as a key enabling technology to enable 5G networks with multi-services. Network slicing allows a transition from a network-as-an-infrastructure setup to a networkas-a-service to enable numerous 5G smart services with diverse requirements. Although several surveys and tutorials have discussed network slicing in detail, there is no comprehensive study discussing the taxonomy and requirements of network slicing. In this paper, we present and investigate key recent advances of network slicing towards enabling several Internet of Things (IoT) smart applications. A taxonomy is devised for network slicing using different parameters: key design principles, enablers, slicing resources levels, service function chaining schemes, physical infrastructures, and security. Furthermore, we discuss key requirements for network slicing to enable smart services. Finally, we present several open research challenges along with possible guidelines for network slicing.

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“…The issue of dividing RAN resources among a set of MVNOs has received significant interest from the research community over the last years; for excellent surveys on the topic, the reader is referred to [14,15]. This problem (also referred to as RAN slicing problem [5,16,19]) has been addressed by designing solutions that use a variety of theoretical tools, ranging from optimization [20][21][22][23], auctions [24] and game theory [25][26][27].…”

Section: Related Workmentioning

confidence: 99%

The Slice Is Served: Enforcing Radio Access Network Slicing in Virtualized 5G Systems

DrOro

Restuccia

Talamonti

et al. 2019

IEEE INFOCOM 2019 - IEEE Conference on Computer Communications

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The notions of softwarization and virtualization of the radio access network (RAN) of next-generation (5G) wireless systems are ushering in a vision where applications and services are physically decoupled from devices and network infrastructure. This crucial aspect will ultimately enable the dynamic deployment of heterogeneous services by different network operators over the same physical infrastructure. RAN slicing is a form of 5G virtualization that allows network infrastructure owners to dynamically "slice" and "serve" their network resources (i.e., spectrum, power, antennas, among others) to different mobile virtual network operators (MVNOs), according to their current needs. Once the slicing policy (i.e., the percentage of resources assigned to each MVNO) has been computed, a major challenge is how to allocate spectrum resources to MVNOs in such a way that (i) the slicing policy defined by the network owner is enforced; and (ii) the interference among different MVNOs is minimized. In this article, we mathematically formalize the RAN slicing enforcement problem (RSEP) and demonstrate its NP-hardness. For this reason, we design three approximation algorithms that render the solution scalable as the RSEP increases in size. We extensively evaluate their performance through simulations and experiments on a testbed made up of 8 software-defined radio peripherals. Experimental results reveal that not only do our algorithms enforce the slicing policies, but can also double the total network throughput when intra-MVNO power control policies are used in conjunction.

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SoftSLICE: Policy-Based Dynamic Spectrum Slicing in 5G Cellular Networks

Cited by 12 publications

References 6 publications

Interference Minimization in 5G Physical-Layer Network Slicing

Interference Minimization in 5G Physical-Layer Network Slicing

Network Slicing: Recent Advances, Taxonomy, Requirements, and Open Research Challenges

The Slice Is Served: Enforcing Radio Access Network Slicing in Virtualized 5G Systems

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