Intelligent Reflecting Surface Enhanced Indoor Robot Path Planning: A Radio Map based Approach

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 communicates with the AP. In the multiple-user scenario, the AP serves one mobile robotic user and one static robotic user employing either NOMA or OMA transmission. The considered system is optimized for minimization of the travelling time/distance of the mobile robotic user from a given starting point to a predefined final location, while satisfying constraints on the communication quality of the robotic users. To tackle this problem, 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 mobile robotic user 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, an achievable communication rate map is constructed. It characterizes the spatial distribution of the maximum expected rate of the mobile robotic user for the optimal power allocation at the AP and the optimal IRS phase shifts subject to a minimum rate requirement for the static robotic user. 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.