A Sensing-Assisted Environment Classification Technique for CF-mMIMO Enabled Non-Terrestrial Networks
IEEE Wireless Communications Letters, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Basım Tarihi: 2026
- Doi Numarası: 10.1109/lwc.2026.3686233
- Dergi Adı: IEEE Wireless Communications Letters
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Compendex, INSPEC, Technology Collection (ProQuest)
- Anahtar Kelimeler: 6G, CF-mMIMO ISAC, environment classification, HAP, NTN, UAV
- İstanbul Medipol Üniversitesi Adresli: Evet
Özet
This letter proposes a sensing-assisted user environment classification framework for cell-free massive multiple-input multiple-output (CF-mMIMO) enabled non-terrestrial networks (NTNs) to accurately distinguish user environments under different channel and deployment scenarios. Specifically, a swarm of unmanned aerial vehicles (UAVs), coordinated by a high-altitude platform (HAP), transmits positioning reference signals (PRSs) embedded with radar-like sensing features. Thereby, the UAVs are allowed to infer propagation characteristics without increasing user-side complexity. Following this, the proposed framework jointly leverages spatial diversity, frequency diversity, and coding diversity to enhance detection robustness under multipath conditions and vertical-level differentiation of user positions by utilizing a bit-error-rate (BER)–driven classifier. Simulation results under standardized NTN channel models show up to 95% improvement in environment classification accuracy and significantly reduced false indoor detections compared to single-domain aggregation methods.