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Although airborne base stations (ABSs) mounted on drones show a significantpotential to enhance network capacity and coverage due to their flexibledeployment, the system performance is severely limited by the endurance of theon-board battery. To overcome this key shortcoming, we are exploring roboticairborne base station (RABS) with energy neutral grasping end-effectors able toautonomously perch at tall urban landforms. This paper studies the optimaldeployment (fly to another grasping location or remain in the same one) andoperation (active or sleep at an epoch) of RABS based on the spatio-temporalcharacteristics of underlying traffic demand from end-users. Specifically, aninteger linear programming (ILP) is formulated by exploiting the couplingbetween these two decisions, that is, the RABS only needs to visit thelocations where it is active. A Lagrangian heuristic algorithm is then proposedby exploiting the totally unimodular structure of the ILP formulation. A wideset of numerical investigations reveal that thanks to its mobility, a singlerobotic aerial small cell is able to outperform five (5) fixed small cells interms of served user generated traffic within a 16 to 41 hours period.

Optimal Deployment and Operation of Robotic Aerial 6G Small Cells with Grasping End Effectors