collaborators

12 papers

eess.SP2026

LOCUS-DT: Localization via Observation-Conditioned Uncertainty Scoring with Digital Twins

Haozhe Lei, Roberto Bomfin, Marwa Chafii +1

Accurate indoor localization is essential for emerging applications in robotic navigation and search and rescue. While classical methods typically focus on single-point estimates,…

eess.SP2026

Efficient Upper Mid-Band Spectrum Sensing with Multiple Signals

Yongjun Kim, Ali Rasteh, Sundeep Rangan +1

Spectrum sensing is a fundamental problem in the upper mid-band, where spectrum resources are shared with incumbent systems. This paper considers frequency-domain occupancy estimat…

eess.SP2026

Near Field Multi-Band Localization: CRB, Efficient Estimator, and Threshold SNR

Roberto Bomfin, Marco Mezzavilla, Sundeep Rangan +1

This paper presents a theoretical framework for multi-band localization for a single-path single-input multiple-output (SIMO) system. We derive closed-form Cramer-Rao bounds (CRBs)…

cs.NI2026

Advancing Network Digital Twin Framework for Generating Realistic Datasets

Oscar Stenhammar, Sundeep Rangan, Gábor Fodor +1

The integration of accurate and reproducible wireless network simulations is a key enabler for research on open, virtualized, and intelligent communication systems. Network Digital…

eess.SP2026

Low-rank Preconditioning in Beamspace Domain For Massive MU-MIMO Long-Term Beamforming

Amirreza Kiani, Ali Rasteh, Marco Mezzavilla +1

Long-term beamforming substantially reduces the channel estimation and inversion overhead of conventional massive MU-MIMO receivers; yet, its construction still hinges on the inver…

eess.SP2026

Scalable Long-Term Beamforming for Massive Multi-User MIMO

Ali Rasteh, Amirreza Kiani, Marco Mezzavilla +1

Fully digital massive MIMO systems with large numbers (1000+) of antennas offer dramatically increased capacity gains from spatial multiplexing and beamforming. Designing digital r…