论文标题
智能反射表面增强室内机器人路径计划:基于无线电地图的方法
Intelligent Reflecting Surface Enhanced Indoor Robot Path Planning: A Radio Map based Approach
论文作者
论文摘要
在本文中,研究了室内机器人导航系统,其中采用智能反射表面(IRS)来增强接入点(AP)和机器人用户之间的连接性。都考虑了单用户和多用户方案。在单用户方案中,一个移动机器人用户(MRU)与AP进行通信。在多用户方案中,AP使用非正交多访问(NOMA)或正交多访问(OMA)传输提供一个MRU和一个静态机器人用户(SRU)。优化了考虑的系统,可将MRU从给定的起点到预定义的最终位置最小化,同时满足机器人用户的通信质量的限制。为此,提出了基于无线电图的方法来利用与位置有关的通道传播知识。对于单用户方案,构建了通道功率增益图,这表征了最佳IRS相位移位的最大预期有效通道功率增益的空间分布。基于获得的通道功率增益图,通过利用图理论来解决通信感知的机器人路径计划问题。对于多用户方案,构建了一个通信率图,该图的特征是AP处的最佳功率分配的MRU的最大预期率的空间分布,以及最佳IRS相位偏移的SRU对最低率要求。通过调用一分配搜索和连续的凸近似方法,可以有效地解决关节优化问题。然后,通过利用获得的通信速率图来得出针对机器人路径计划问题的基于图形的解决方案。我们的数值结果验证了所提出的设计的有效性。
In this paper, an indoor robot navigation system is investigated, where an intelligent reflecting surface (IRS) is employed to enhance the connectivity between the access point (AP) and robotic users. Both single-user and multiple-user scenarios are considered. In the single-user scenario, one mobile robotic user (MRU) communicates with the AP. In the multiple-user scenario, the AP serves one MRU and one static robotic user (SRU) employing either non-orthogonal multiple access (NOMA) or orthogonal multiple access (OMA) transmission. The considered system is optimized for minimization of the travelling time/distance of the MRU from a given starting point to a predefined final location, while satisfying constraints on the communication quality of the robotic users. To this end, a radio map based approach is proposed to exploit location-dependent channel propagation knowledge. For the single-user scenario, a channel power gain map is constructed, which characterizes the spatial distribution of the maximum expected effective channel power gain of the MRU for the optimal IRS phase shifts. Based on the obtained channel power gain map, the communication-aware robot path planing problem is solved by exploiting graph theory. For the multiple-user scenario, a communication rate map is constructed, which characterizes the spatial distribution of the maximum expected rate of the MRU for the optimal power allocation at the AP and the optimal IRS phase shifts subject to a minimum rate requirement for the SRU. The joint optimization problem is efficiently solved by invoking bisection search and successive convex approximation methods. Then, a graph theory based solution for the robot path planning problem is derived by exploiting the obtained communication rate map. Our numerical results verify the effectiveness of the proposed designs.