TY - GEN
T1 - Channel-Aware 5G RAN Slicing with Customizable Schedulers
AU - Chen, Yongzhou
AU - Yao, Ruihao
AU - Hassanieh, Haitham
AU - Mittal, Radhika
N1 - We would like to thank our shepherd, Ganesh Anantha-narayanan, and the anonymous NSDI reviewers for their insightful comments and feedback. We’re grateful to Ammar Tahir, Emerson Sie for their feedback in the camera-ready version. We would also like to thank Yaxiong Xie for sharing the LTE SNR traces with us. This work was supported by Intel, Facebook, AG NIFA under grant 2021-67021-34418, and UIUC’s Smart Transport Infrastructure Initiative.
PY - 2023
Y1 - 2023
N2 - This paper focuses on 5G RAN slicing, where the 5G radio resources must be divided across slices (or enterprises) so as to achieve high spectrum efficiency, fairness and isolation across slices, and the ability for each slice to customize how the radio resources are divided across its own users. Realizing these goals requires accounting for the channel quality for each user (that varies over time and frequency domain) at both levels - inter-slice scheduling (i.e. dividing resources across slices) and enterprise scheduling (i.e. dividing resources within a slice). However, a cyclic dependency between the inter-slice and enterprise schedulers makes it difficult to incorporate channel awareness at both levels. We observe that the cyclic dependency can be broken if both the inter-slice and enterprise schedulers are greedy. Armed with this insight, we design RadioSaber, the first RAN slicing mechanism to do channel-aware inter-slice and enterprise scheduling. We implement RadioSaber on an open-source RAN simulator, and our evaluation shows how RadioSaber can achieve 17%-72% better throughput than the state-of-the-art RAN slicing technique (that performs channel-agnostic inter-slice scheduling), while meeting the primary goals of fairness across slices and the ability to support a wide variety of customizable enterprise scheduling policies.
AB - This paper focuses on 5G RAN slicing, where the 5G radio resources must be divided across slices (or enterprises) so as to achieve high spectrum efficiency, fairness and isolation across slices, and the ability for each slice to customize how the radio resources are divided across its own users. Realizing these goals requires accounting for the channel quality for each user (that varies over time and frequency domain) at both levels - inter-slice scheduling (i.e. dividing resources across slices) and enterprise scheduling (i.e. dividing resources within a slice). However, a cyclic dependency between the inter-slice and enterprise schedulers makes it difficult to incorporate channel awareness at both levels. We observe that the cyclic dependency can be broken if both the inter-slice and enterprise schedulers are greedy. Armed with this insight, we design RadioSaber, the first RAN slicing mechanism to do channel-aware inter-slice and enterprise scheduling. We implement RadioSaber on an open-source RAN simulator, and our evaluation shows how RadioSaber can achieve 17%-72% better throughput than the state-of-the-art RAN slicing technique (that performs channel-agnostic inter-slice scheduling), while meeting the primary goals of fairness across slices and the ability to support a wide variety of customizable enterprise scheduling policies.
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M3 - Conference contribution
AN - SCOPUS:85159281433
T3 - Proceedings of the 20th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2023
SP - 1767
EP - 1782
BT - Proceedings of the 20th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2023
PB - USENIX Association
T2 - 20th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2023
Y2 - 17 April 2023 through 19 April 2023
ER -