Towards full-dimensional positioning by leveraging intelligent omni-surface

Reconfigurable intelligent surface (RIS)-assisted received signal strength (RSS) positioning technology has attracted widespread attention due to its low deployment cost and ability to customize the wireless environment. Through regulating the RIS's electromagnetic responses, the transmission channels are altered to amplify the differences in RSS values between neighbouring locations, thereby enhancing the accuracy of positioning. However, existing works only consider reflective RIS, and thus can only improve the positioning accuracy of users on a single face of the surface. To offer positioning services to users on either sides of the surfaces, we propose to utilize Intelligent Omni-Surface (IOS), a special kind of RIS that is capable of reflecting and refracting incoming signals concurrently, to assist the RSS-based positioning. Specifically, by modulating the RSS distribution on the two sides of the IOS through adjusting the reflection and refraction phase shifts induced by the surface, positioning accuracy for individuals on either sides of the surface can undergo effective improvements, so as to realize full-dimensional localization. However, since the reflection and refraction phase shifts of the IOS are coupled, it is challenging to jointly optimize them so as to minimize the positioning error. To address this challenge, within this letter, we investigated an IOS-aided full-dimensional localization system based on RSS, in which IOS is placed in the centre of the room to adjust the RSS distribution of users on both sides, and designed an IOS-aided localization protocol to coordinate IOS and users. Based on this protocol, we formulate a phase shift optimization problem to reduce users' positioning error, and develop a phase shift optimization algorithm based on gradient descent for iteratively to solve it. Simulation results confirm the efficiency of the suggested IOS-aided positioning method.