# A Novel Crowdsourcing-Assisted 5G Wireless Signal Ranging Technique in MEC Architecture
## 2 Background and Related Work
### Environment Perception Fingerprint Collection
#### 2.2.2 Grid-Based Street Scanning Method  
To address the aforementioned challenges, researchers have proposed grid-based street-scanning methodologies to enhance the efficiency of fingerprint acquisition. Grid-based street-scanning is a systematic data collection technique that partitions target areas into grid cells, enabling detailed reference point data collection within each grid to ensure comprehensiveness and consistency. Recent research has explored diverse strategies to optimize grid design, data collection, and signal processing. [PERSON] et al. proposed a fine-grained grid computing model for Wi-Fi indoor localization in complex environ ments, where subdividing the area into smaller grid cells and leveraging signal strength features combined with machine learning significantly enhanced localization accuracy and robustness [28]. [PERSON] et al. proposed an irregular grid map approach for large-scale Wi-Fi fingerprinting, where reference points are placed at the centers of uneven grid cells to enhance coverage and minimize localization errors [29]. Building upon systematic grid partitioning, [PERSON] et al. introduced a method based on RSSI fingerprint feature vectors, dividing the target environment into uniform grids and achieving 2-4 m localization accuracy by matching real-time RSSI measurements [30]. [PERSON] et al. further improved grid-based fingerprinting by applying a bag-of-features machine learning framework, employing k-means clustering and k-nearest neighbors to robustly model and match WLAN RSS fingerprints [31]. The above main research summaries on wireless signal ranging and fingerprinting can be summarized as shown in Table 1. However, these grid-based signal ranging schemes lack real-time fingerprint map updates and overlook matching latency in large-scale user environments. To overcome these limitations, this paper proposes a progressive fingerprint update algorithm that integrates real-time crowdsourced data with historical fingerprints via a spatiotemporal correlation model, enabling autonomous optimization of reference databases in dynamic environments. This approach bridges the gap in existing grid-based fingerprint collection methodologies. Furthermore, by innovatively leveraging mobile edge computing (MEC) architecture combined with lightweight computational engines, the scheme significantly reduces core network load while maintaining high-precision localization performance. \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt}} \hline \hline
**Category** & **Reference** & **Contribution** \\ \hline \multicolumn{3}{c}{**Base station-assisted signal ranging**} \\ \hline Multi-path aided TDOA & [PERSON] et al., 2025 [8] & Multi-path aided TDOA localization addressing synchronization challenges. \\ \hline TDOA optimization & [PERSON] et al., 2024 [5] & Unified near- and far-field TDOA processing based on modified polar representation (MPR). \\ \hline Hybrid TDOA+AOA in 5G & [PERSON] et al., 2021 [7] & UTDOA and AOA fusion with base station selective exclusion in 5G networks. \\ \hline Topology impact analysis & [PERSON] et al., 2019 [6] & Analysis of base station topology impact on TDOA and AOA performance. \\ \hline TDOA optimization & [PERSON] et al., 2015 [4] & TDOA without strict synchronization via mobile source movement. \\ \hline \multicolumn{3}{c}{**Bluetooth-assisted signal ranging**} \\ \hline Learning enhancement & [PERSON] et al., 2024 [14] & Attention-enhanced BLE fingerprinting for improved feature extraction. \\ \hline Hybrid fingerprinting & [PERSON] et al., 2024 [15] & Hybrid BLE fingerprinting adapting to dynamic environments. \\ \hline Signal fusion & [PERSON] et al., 2024 [16] & BLE and UWB signal fusion for robust localization. \\ \hline Lightweight deployment & [PERSON]/[PERSON] et al., 2024 [17] & Lightweight BLE smartwatch-based room-level tracking. \\ \hline System optimization & [PERSON] et al., 2024 [19] & BLE signal filtering and anchor placement optimization. \\ \hline \hline \end{tabular}
\end{table}