14 papers
MAPLE-RF: Efficient Probabilistic RF Source Localization in Partially Explored Environments
Haozhe Lei, Sundeep Rangan
Localizing a radio-frequency (RF) transmitter from received signals often requires a model of the environment to predict how obstacles block and reflect the signal. In many robotic…
MAGNETAR: Multipath-Guided Spatial Posteriors for Transmitter Pose Inference in the Upper Mid-Band
Haozhe Lei, Ruibin Chen, Yuhan Jiang +3
Robots that localize a radio transmitter need more than a point estimate: in cluttered rooms, one measurement is often consistent with several transmitter locations and, because up…
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,…
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…
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)…
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…
Interference Suppression for Massive MU-MIMO Long-Term Beamforming with Matrix Inversion Approximation
Amirreza Kiani, Ali Rasteh, Marco Mezzavilla +1
Long-term beamforming (LTBF) is a widely-used scalable alternative to instantaneous multi-user MIMO processing that leverages slowly varying spatial channel statistics. VLSI implem…
A Self-Calibrating SDR for High Fidelity Beam- and Null-forming Arrays
Yongjun Kim, Aditya Dhananjay, Sundeep Rangan +5
Null forming is increasingly essential in modern wireless systems for spectrum-sharing, anti-jamming, and covert communications in contested and congested environments. Achieving d…
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…
A Spatial Array for Spectrally Agile Wireless Processing
Ali Rasteh, Andrew Hennessee, Ishaan Shivhare +3
Massive MIMO is a cornerstone of next-generation wireless communication, offering significant gains in capacity, reliability, and energy efficiency. However, to meet emerging deman…
Scalable Long-Term Beamforming for Massive Multi-User MIMO
Ali Rasteh, Amirreza Kiani, Marco Mezzavilla +1
Fully digital massive multiple-input multiple-output (MIMO) systems with large numbers (1000+) of antennas offer capacity gains from spatial multiplexing and beamforming, but recei…
Beyond Point Estimates: Likelihood-Based Full-Posterior Wireless Localization
Haozhe Lei, Hao Guo, Tommy Svensson +1
Modern wireless systems require not only position estimates, but also quantified uncertainty to support planning, control, and radio resource management. We formulate localization…
Transformer-Based Rate Prediction for Multi-Band Cellular Handsets
Ruibin Chen, Haozhe Lei, Hao Guo +4
Cellular wireless systems are facing a proliferation of frequency bands over a wide spectrum, particularly with the expansion into FR3. These bands must be supported in user equipm…
Computationally Efficient Signal Detection with Unknown Bandwidths
Ali Rasteh, Sundeep Rangan
Signal detection in environments with unknown signal bandwidth and time intervals is a fundamental problem in adversarial and spectrum-sharing scenarios. This paper addresses the p…