Localization performance analysis based on channel knowledge map

This article analyzes the localization performance based on Channel Knowledge Map (CKM). A single access point (AP) is deployed in a three-dimensional (3-D) scenario and the CKM is used to localize the users, which utilizes channel information including angle of arrival (AoA), angle of departure (AoD), and path loss from both line of sight (LoS) and non-line of sight (NLoS) paths between the AP and users. Due to the impracticality of directly using NLoS paths, the virtual access point (VAP) technique is utilized to address NLoS issues. Subsequently, Cramér–Rao Lower Bound (CRLB) model that incorporates grid size effects is derived to assess localization accuracy. We analyze the impact of grid size, the number of propagation paths, and the use of single and multiple channel information metrics on CRLB. The results indicate that as the grid size decreases, localization error is reduced up to a certain threshold. Additionally, increasing the number of propagation paths enhances localization accuracy, as it provides more comprehensive spatial information. The analysis are verified through numerical results and it is found that CKM-based localization consistently achieves sub-meter accuracy.