Search Results for author:
Found 4 papers, 0 papers with code
Device-Agnostic Millimeter Wave Beam Selection using Machine Learning
However, this design requires a specific model for each user-device beam codebook, where a model learned for a device with a particular codebook can not be reused for another device with a different codebook.
Location- and Orientation-aware Millimeter Wave Beam Selection for Multi-Panel Antenna Devices
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 arrays with isotropic antennas.
A Deep Learning Approach to Location- and Orientation-aided 3D Beam Selection for mmWave Communications
This paper proposes a location- and orientation-based beam selection method to enable context information (CI)-based beam alignment in applications where the UT can take arbitrary orientation at each location.
Distributed Receivers for Extra-Large Scale MIMO Arrays: A Message Passing Approach
In this paper, we propose a distributed receiver for such an XL-MIMO system that can address both challenges.
