Joint Robotic Aerial Base Station Deployment and Wireless Backhauling in 6G Multi-hop Networks
Wen Shang, Yuan Liao, Vasilis Friderikos, Halim Yanikomeroglu

TL;DR
This paper introduces a method for deploying and managing robotic aerial base stations in 6G networks to dynamically support high data rates through optimized placement, resource allocation, and routing, enhancing network efficiency.
Contribution
It presents a joint optimization framework for RABS deployment, resource block assignment, and routing in mmWave 6G networks, with a low-complexity greedy algorithm for real-time adaptation.
Findings
Robotic base stations can serve up to 65% more traffic than fixed small cells.
The proposed greedy algorithm achieves competitive solutions with low computational complexity.
Dynamic relocation of RABS improves overall network traffic capacity.
Abstract
Due to their ability to anchor into tall urban landforms, such as lampposts or street lights, robotic aerial base stations (RABSs) can create a hyper-flexible wireless multi-hop heterogeneous network to meet the forthcoming green, densified, and dynamic network deployment to support, inter alia, high data rates. In this work, we propose a network infrastructure that can concurrently support the wireless backhaul link capacity and access link traffic demand in the millimeter-wave (mmWave) frequency band. The RABSs grasping locations, resource blocks (RBs) assignment, and route flow control are simultaneously optimized to maximize the served traffic demands. Robotic base stations capitalize on the fact that traffic distribution varies considerably across both time and space within a given geographical area. Hence, they are able to relocate to suitable locations, i.e., 'follow' the traffic…
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Taxonomy
TopicsAdvanced Wireless Communication Technologies · UAV Applications and Optimization · Satellite Communication Systems
