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Deep Reinforcement Learning for mmWave Initial Beam Alignment
We investigate the applicability of deep reinforcement learning algorithms to the adaptive initial access beam alignment problem for mmWave communications using the state-of-the-art proximal policy optimization algorithm as an example.
Improving Triplet-Based Channel Charting on Distributed Massive MIMO Measurements
The objective of channel charting is to learn a virtual map of the radio environment from high-dimensional CSI that is acquired by a multi-antenna wireless system.
Geometry-Based Phase and Time Synchronization for Multi-Antenna Channel Measurements
Synchronization of transceiver chains is a major challenge in the practical realization of massive MIMO and especially distributed massive MIMO.
Massive MIMO Channel Measurements and Achievable Rates in a Residential Area
In this paper we present a measurement set-up for massive MIMO channel sounding that shows very good long-term phase stability.
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