6 papers
Autonomous CSI Prediction Framework for O-RAN-Enabled 5G mmWave Vehicular Networks
Abidemi Orimogunje, Vukan Ninkovic, Nemanja Petrovic +4
Establishing and maintaining 5G mmWave vehicular connectivity poses a challenge due to high user mobility, requiring the design of robust and efficient beam switching procedures. U…
Occlusion-Aware Multimodal Beam Prediction and Pose Estimation for mmWave V2I
Abidemi Orimogunje, Hyunwoo Park, Kyeong-Ju Cha +3
We propose an occlusion-aware multimodal learning framework that is inspired by simultaneous localization and mapping (SLAM) concepts for trajectory interpretation and pose predict…
Sensing-Assisted Adaptive Beam Probing with Calibrated Multimodal Priors and Uncertainty-Aware Scheduling
Abidemi Orimogunje, Vukan Ninkovic, Ognjen Kundacina +5
Highly directional mmWave/THz links require rapid beam alignment, yet exhaustive codebook sweeps incur prohibitive training overhead. This letter proposes a sensing-assisted adapti…
System-Level Comparison of Multimodal and In-Band mmWave Sensing for Beam Prediction in 6G ISAC
Abidemi Orimogunje, Hyunwoo Park, Igbafe Orikumhi +2
Integrated sensing and communication (ISAC) can reduce beam-training overhead in mmWave vehicle-to-infrastructure (V2I) links by enabling in-band sensing-based beam prediction, whi…
Mobility-Aware Localization in mmWave Channel: Adaptive Hybrid Filtering Approach
Abidemi Orimogunje, Kyeong-Ju Cha, Hyunwoo Park +3
Precise user localization and tracking enhances energy-efficient and ultra-reliable low latency applications in the next generation wireless networks. In addition to computational…
Autonomous Self-Trained Channel State Prediction Method for mmWave Vehicular Communications
Abidemi Orimogunje, Vukan Ninkovic, Evariste Twahirwa +2
Establishing and maintaining 5G mmWave vehicular connectivity poses a significant challenge due to high user mobility that necessitates frequent triggering of beam switching proced…