Robot Trajectory Planning With QoS Constrained IRS-assisted Millimeter-Wave Communications

TL;DR

This paper proposes a joint optimization framework for robot trajectory and beamforming in IRS-assisted millimeter-wave communications to enhance energy efficiency and communication QoS in industrial scenarios.

Contribution

It introduces a novel decoupling approach for beamforming and trajectory optimization using mm-wave channel properties and a successive-convex algorithm considering obstacles.

Findings

The proposed algorithm converges to a KKT-satisfying solution.

It effectively avoids obstacles while satisfying QoS constraints.

The method improves energy efficiency and communication reliability.

Abstract

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.