The reliability of indoor 5G connectivity remains a critical bottleneck in modern urban infrastructure, predominantly due to the complex attenuation caused by architectural elements in high-rise environments. While Unmanned Aerial Vehicles (UAVs) offer a versatile platform for external Radio Frequency (RF) sensing, deriving an accurate internal signal landscape from sparse exterior measurements presents a significant inversion problem. To address this, we introduce a novel framework leveraging Dynamic Graph Attention Network (DGAT) to reconstruct indoor 5G signal quality. Deviating from traditional Euclidean-based connectivity models, our approach infers a latent connectivity structure governed by feature affinity, thereby capturing the non-linear propagation characteristics inherent to complex buildings. This learned topology supports a deep residual propagation encoder, which feeds into a bifurcated decoding mechanism specifically optimized for the divergent physical behaviors of Received Signal Strength Indicator (RSSI) and Channel Quality Indicator (CQI). Furthermore, prediction variance is mitigated through a meta-ensemble fusion layer. Experimental validation on a multi-level 5G dataset confirms that the proposed architecture significantly outperforms existing location-aware baselines, achieving a reduction in Root Mean Square Error (RMSE) of 76% for RSSI and 89% for CQI, with R2 fidelity scores surpassing 0.99. By effectively bridging the gap between non-invasive aerial sensing and interior coverage estimation, this framework provides a robust foundation for next-generation urban wireless planning.
- Spatial-Temporal Inference of Indoor RSSI and CQI for 3D Coverage Mapping using Dynamic Graph Attention Networks
- David Hason RuddA B M Mehedi HasanJohan Sebastian Ramirez VallejoMd. Rafiqul IslamAndrew LevulaCesar Sanin
- WWW '26: The ACM Web Conference 2026
- Companion Proceedings of the ACM Web Conference 2026, pp.251-257
- ACM Conferences
- ACM
- 7
- 9912351310161
- School of Business
- English
- Conference proceeding