2020/10/27 by Tatino, Cristian, Pappas, Nikolaos, Yuan, Di
#FOS: Computer and information sciences #Networking and Internet Architecture (cs.NI)
paper · doi:10.48550/arxiv.2010.14653
This paper considers the joint optimization of trajectory and beamforming of a wirelessly connected robot using intelligent reflective surface (IRS)-assisted millimeter-wave (mm-wave) communications. The goal is to minimize the motion energy consumption subject to time and communication quality of service (QoS) constraints. This is a fundamental problem for industry 4.0, where robots may have to maximize their battery autonomy and communication efficiency. In such scenarios, IRSs and mm-waves can dramatically increase the spectrum efficiency of wireless communications providing high data rates and reliability for new industrial applications. We present a solution to the optimization problem that exploits mm-wave channel characteristics to decouple beamforming and trajectory optimizations. Then, the latter is solved by a successive-convex optimization (SCO) algorithm. The algorithm takes into account the obstacles' positions and a radio map and provides solutions that avoid collisions and satisfy the QoS constraint. Moreover, we prove that the algorithm converges to a solution satisfying the Karush-Kuhn-Tucker (KKT) conditions.