论文标题
机器人轨迹计划，QoS受限的IRS辅助毫米波通信
Robot Trajectory Planning With QoS Constrained IRS-assisted Millimeter-Wave Communications
论文作者
论文摘要
本文考虑了使用智能反射表面（IRS）辅助毫米波（MM-WAVE）通信的无线连接机器人进行轨迹的联合优化。目的是最大程度地减少按时间和沟通质量（QOS）约束的运动能耗。对于行业4.0来说，这是一个基本问题，机器人可能必须最大程度地提高电池自主权和沟通效率。在这种情况下，IRS和MM波可以大大提高无线通信的频谱效率，从而为新的工业应用提供高数据速率和可靠性。我们为优化问题提供了一种解决方案，该优化问题利用了MM-Wave通道特性来解除光束形成和轨迹优化。然后，通过连续的凸优化（SCO）算法解决后者。该算法考虑了障碍的位置和无线电图，并提供了避免碰撞并满足QoS约束的解决方案。此外，我们证明该算法会收敛到满足Karush-Kuhn-Tucker（KKT）条件的溶液。
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.
