Search Results for author: Alyosha Molnar

Found 5 papers, 0 papers with code

A Resolution-Adaptive 8 mm$^\text{2}$ 9.98 Gb/s 39.7 pJ/b 32-Antenna All-Digital Spatial Equalizer for mmWave Massive MU-MIMO in 65nm CMOS

no code implementations23 Jul 2021 Oscar Castañeda, Zachariah Boynton, Seyed Hadi Mirfarshbafan, Shimin Huang, Jamie C. Ye, Alyosha Molnar, Christoph Studer

All-digital millimeter-wave (mmWave) massive multi-user multiple-input multiple-output (MU-MIMO) receivers enable extreme data rates but require high power consumption.

Resolution-Adaptive All-Digital Spatial Equalization for mmWave Massive MU-MIMO

no code implementations23 Jul 2021 Oscar Castañeda, Seyed Hadi Mirfarshbafan, Shahaboddin Ghajari, Alyosha Molnar, Sven Jacobsson, Giuseppe Durisi, Christoph Studer

All-digital basestation (BS) architectures for millimeter-wave (mmWave) massive multi-user multiple-input multiple-output (MU-MIMO), which equip each radio-frequency chain with dedicated data converters, have advantages in spectral efficiency, flexibility, and baseband-processing simplicity over hybrid analog-digital solutions.

Compressive Light Field Reconstructions using Deep Learning

no code implementations5 Feb 2018 Mayank Gupta, Arjun Jauhari, Kuldeep Kulkarni, Suren Jayasuriya, Alyosha Molnar, Pavan Turaga

We test our network reconstructions on synthetic light fields, simulated coded measurements of real light fields captured from a Lytro Illum camera, and real coded images from a custom CMOS diffractive light field camera.

Compressive Sensing

Depth Fields: Extending Light Field Techniques to Time-of-Flight Imaging

no code implementations2 Sep 2015 Suren Jayasuriya, Adithya Pediredla, Sriram Sivaramakrishnan, Alyosha Molnar, Ashok Veeraraghavan

In this paper, we explore the strengths and weaknesses of combining light field and time-of-flight imaging, particularly the feasibility of an on-chip implementation as a single hybrid depth sensor.

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