11 citations · 22 across the 5 of their papers we have counts for
5 papers
Beyond Codebook-Based Analog Beamforming at mmWave: Compressed Sensing and Machine Learning Methods
Hamed Pezeshki, Fabio Valerio Massoli, Arash Behboodi +6
Analog beamforming is the predominant approach for millimeter wave (mmWave) communication given its favorable characteristics for limited-resource devices. In this work, we aim at…
Multi-Modal Beam Prediction Challenge 2022: Towards Generalization
Gouranga Charan, Umut Demirhan, João Morais +3
Beam management is a challenging task for millimeter wave (mmWave) and sub-terahertz communication systems, especially in scenarios with highly-mobile users. Leveraging external se…
Position Aided Beam Prediction in the Real World: How Useful GPS Locations Actually Are?
João Morais, Arash Behboodi, Hamed Pezeshki +1
Millimeter-wave (mmWave) communication systems rely on narrow beams for achieving sufficient receive signal power. Adjusting these beams is typically associated with large training…
Anywhere Decoding: Low-Overhead Uplink Interference Management for Wireless Networks
Hamed Pezeshki, Masoumeh Sadeghi, Martin Haenggi +1
Inter-cell interference (ICI) is one of the major performance-limiting factors in the context of modern cellular systems. To tackle ICI, coordinated multi-point (CoMP) schemes have…
Jamming Energy Allocation in Training-Based Multiple Access Systems
Hamed Pezeshki, Xiangyun Zhou, Behrouz Maham
We consider the problem of jamming attack in a multiple access channel with training-based transmission. First, we derive upper and lower bounds on the maximum achievable ergodic s…