9 citations · 12 across the 5 of their papers we have counts for
5 papers · 1 filter
Superimposed DMRS for Spectrally Efficient 6G Uplink Multi-User OFDM: Classical vs AI/ML Receivers
Sajad Rezaie, Mikko Honkala, Dani Korpi +4
Fifth-generation (5G) systems utilize orthogonal demodulation reference signals (DMRS) to enable channel estimation at the receiver. These orthogonal DMRS-also referred to as pilot…
Device-Agnostic Millimeter Wave Beam Selection using Machine Learning
Sajad Rezaie, João Morais, Ahmed Alkhateeb +1
Most research in the area of machine learning-based user beam selection considers a structure where the model proposes appropriate user beams. However, this design requires a speci…
Location- and Orientation-aware Millimeter Wave Beam Selection for Multi-Panel Antenna Devices
Sajad Rezaie, João Morais, Elisabeth de Carvalho +2
While initial beam alignment (BA) in millimeter-wave networks has been thoroughly investigated, most research assumes a simplified terminal model based on uniform linear/planar arr…
A Deep Learning Approach to Location- and Orientation-aided 3D Beam Selection for mmWave Communications
Sajad Rezaie, Elisabeth de Carvalho, Carles Navarro Manchón
Position-aided beam selection methods have been shown to be an effective approach to achieve high beamforming gain while limiting the overhead and latency of initial access in mill…
Distributed Receivers for Extra-Large Scale MIMO Arrays: A Message Passing Approach
Abolfazl Amiri, Sajad Rezaie, Carles Navarro Manchon +1
We study the design of receivers in extra-large scale MIMO (XL-MIMO) systems, i.e. systems in which the base station is equipped with an antenna array of extremely large dimensions…