The integration of advanced localization techniques in the upcoming next generation networks (B5G/6G) is becoming increasingly important for many use cases comprising contact tracing, natural disasters, terrorist attacks, etc. Therefore, emerging lightweight and passive technologies that allow accurately controlling the propagation environment, such as reconfigurable intelligent surfaces (RISs), may help to develop advance positioning solutions relying on channel statistics and beamforming. In this paper, we devise PAPIR, a practical localization system leveraging on RISs by designing a two-stage solution building upon prior statistical information on the target user equipment (UE) position. PAPIR aims at finely estimating the UE position by performing statistical beamforming, direction-of-arrival (DoA) and time-of-arrival (ToA) estimation on a given three-dimensional search space, which is iteratively updated by exploiting the likelihood of the UE position.

翻译：将先进的本地化技术纳入即将到来的下一代网络(B5G/6G)对于许多使用案例,包括联系追踪、自然灾害、恐怖袭击等,越来越重要。 因此,新出现的轻量技术和被动技术,如可重新配置的智能表面(RIS)等,可以准确控制传播环境,可能有助于开发依靠频道统计数据和波束成形的先进定位解决方案。在本文件中,我们设计了PAPIR,这是一个利用本地化系统,通过在目标用户设备位置先前的统计信息的基础上设计一个两阶段的本地化系统。 PAPIR旨在通过对特定三维搜索空间进行统计成形、抵达方向和抵达时间估计来精确估计UE位置,通过利用UE位置的可能性进行迭接更新。