51. Drone-Small-Cell-Assisted Resource Slicing for 5G Uplink Radio Access Networks.
- Author
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Shen, Hang, Ye, Qiang, Zhuang, Weihua, Shi, Weisen, Bai, Guangwei, and Yang, Geng
- Subjects
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RADIO access networks , *5G networks , *NP-hard problems , *MULTICASTING (Computer networks) , *MACHINE-to-machine communications , *ALTITUDES , *ALGORITHMS - Abstract
Radio resource slicing is critical to customize service provisioning in fifth-generation (5G) uplink radio access networks (RANs). Using drone-small-cells (DSCs) as aerial support for terrestrial base stations can enhance the flexibility for resource provisioning in response to traffic distribution variations. In this paper, we study a multi-DSC-assisted radio resource slicing problem for 5G uplink RANs, with the objective of minimizing the total uplink resource consumption under differentiated quality-of-service (QoS) constraints for both human-type and machine-type communication services. We begin with an interference-aware graph model to formulate the joint DSC three-dimension (3D) placement and device-DSC association problem for uplink radio resource slicing and prove that the proposed problem is NP-hard. A complexity-adjustable problem approximation is presented via screening candidate DSC deployment positions, which incorporates flight height adaptation to balance the uplink communication coverage and resource utilization. A lightweight approximation using a fixed DSC flight altitude is also provided with reduced complexity. For mathematical traceability, the DSC placement and device-DSC associations in each approximation are transformed as a special weight clique problem. An upgraded clique algorithm is then developed to determine how to deploy DSCs for a given number of DSCs. Simulation results demonstrate the proposed scheme's effectiveness in terms of resource utilization, network coverage, and drone dispatching cost. [ABSTRACT FROM AUTHOR]
- Published
- 2021
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