# Evaluation of 5G Positioning Based on Uplink SRS and Downlink PRS Under LOS and NLOS Environments
## 1 Introduction
The objective of this scheme is to mitigate consecutive collisions and enhance both sensing accuracy and communication reliability under varying traffic conditions [13]. Researcher [PERSON] proposes an analysis of 3 GPP NR V2X sidelink communication, focusing on key physical-layer and security procedures [14]. Most analyses of 5G positioning performance have been conducted through simulation-based methods [15], employing standardized propagation models [16] and proprietary tools [17; 18]. However, experimental validation of these systems using 5G signal transmissions remains limited, with only a few studies available [19]. As stated in [20], research was conducted to assess the effect of various PRS allocations within a slot on localization. Similarly, Ref. [21] explored the performance of PRS in supporting Observed Time Difference of Arrival (OTDOA). Research works such as [22] and [23] explore 5G NR-based indoor positioning, while [24; 25] examine positioning in urban canyon environments. A range of scenarios, including indoor office and factory environments [26], have been examined through the application of diverse positioningmethodologies, including TDOA and TOA. [PERSON] [27] proposes a 5G positioning performance evaluation and examines the design and detection of DL-PRS, emphasizing its application in TDOA-based positioning. [PERSON] and [PERSON] propose a GNSS-5G hybrid positioning technique that integrates TOA and AOA measurements [28]. Researchers [PERSON] and [PERSON] propose a joint positioning and synchronization method that addresses the challenge of inter-base station synchronization errors in imperfectly synchronous 5G mm-wave systems [29]. [PERSON] and [PERSON] propose a Variational Bayesian Adaptive Kalman Filter (VBAKF) to enhance the accuracy of 5G positioning in environments with significant noise changes, addressing the limitations of current methods like the Extended Kalman Filter (EKF) [30]. In the context of dense urban deployments, sub-meter level mean positioning accuracy is expected due to the presence of favorable propagation conditions and the implementation of advanced signal processing methodologies [31]. Time Division Duplexing (TDD) systems facilitate uplink channel estimation through UL-SRS transmitted by the UE, enabling base stations (BS) to infer downlink propagation characteristics via channel reciprocity. A number of studies have examined 5G positioning methods that utilize SRS signals for localization purposes [32]. Radio signal-based positioning is commonly performed using estimation methods that extract features from signal properties. The environmental multipath characteristics are inherently captured in Channel State Information (CSI) [33], which can be used to describe and exploit the radio environment for positioning [34]. Additional studies examine localization using beam information and Reference Signal Received Power (RSRP) [35]. In radio-based positioning, specialized signals are typically required to enable a receiver to estimate relevant propagation characteristics. This process is commonly referred to as channel sounding [36]. In a TDD system, the uplink propagation environment is estimated using SRS transmitted by each UE. This allows the BS to infer the downlink propagation conditions by leveraging channel reciprocity [37]. The process of uplink channel estimation requires the determination of critical parameters, including the TOA and AOA, which function as pivotal metrics for the estimation of the position of the UE. While research on uplink-based positioning approaches remains limited, a researcher in [38] proposes a novel framework. This framework utilizes simulated UL-SRS channel measurements to assess the feasibility of 3D localization through joint angle-time estimation and expectation-maximization techniques. [PERSON] and [PERSON] [39] propose an alternative UL-centric strategy tailored for indoor environments. This strategy employs simulated UL-SRS transmissions to address localization challenges.