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Found 5 papers, 0 papers with code
Proximal Policy Optimization for Integrated Sensing and Communication in mmWave Systems
In wireless communication systems, mmWave beam tracking is a critical task that affects both sensing and communications, as it is related to the knowledge of the wireless channel.
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.
Sparse Estimation using Bayesian Hierarchical Prior Modeling for Real and Complex Linear Models
Motivated by the relative scarcity of formal tools for SBL in complex-valued models, this paper proposes a GSM model - the Bessel K model - that induces concave penalty functions for the estimation of complex sparse signals.
