Robotic Aerial 6G Small Cells with Grasping End Effectors for mmWave Relay Backhauling

TL;DR

This paper proposes using robotic aerial small cells with grasping end effectors as flexible, deployable relay nodes for mmWave backhaul in 6G networks, demonstrating significant reductions in equipment needs.

Contribution

It introduces a novel deployment of robotic aerial small cells with grasping capabilities for dynamic backhaul support in 6G networks, optimizing network capacity and reducing costs.

Findings

RASCs require 25-65% fewer units than fixed small cells for the same throughput.

Network flow-based MILP effectively optimizes RASC deployment.

Flexible RASCs enhance network densification and cost efficiency.

Abstract

Deployment of small cells in dense urban areas dedicated to the heterogeneous network (HetNet) and associated relay nodes for improving backhauling is expected to be an important structural element in the design of beyond 5G (B5G) and 6G wireless access networks. A key operational aspect in HetNets is how to optimally implement the wireless backhaul links to efficiently support the traffic demand. In this work, we utilize the recently proposed Robotic Aerial Small Cells (RASCs) that are able to grasp at different tall urban landforms as wireless relay nodes for backhauling. This can be considered as an alternative to fixed small cells (FSCs) which lack flexibility since once installed their position cannot be altered. More specifically, on-demand deployment of RASCs is considered for constructing a millimeter-wave (mmWave) backhaul network to optimize available network capacity using a network flow-based mixed integer linear programming (MILP) formulation. Numerical investigations reveal that for the same required achievable throughput, the number of RASCs required are 25\% to 65\% less than the number of required FSCs. This result can have significant implications in reducing required wireless network equipment (capex) to provide a given network capacity and allows for an efficient and flexible network densification.