Joint Tracking of Multiple Beams in Beamspace MIMO Systems
Liza Afeef, Murat Karabacak, and H\"useyin Arslan

TL;DR
This paper introduces a joint beam and channel tracking algorithm using the unscented Kalman filter for mmWave MIMO systems with lens antenna arrays, significantly improving tracking performance over traditional methods.
Contribution
It proposes a novel joint tracking algorithm based on UKF for multi-beam scenarios in beamspace MIMO, outperforming EKF and enabling efficient beam management in high mobility environments.
Findings
UKF outperforms EKF in various channel variation conditions.
Joint tracking achieves around 62% performance improvement over individual beam tracking.
The algorithm effectively tracks multiple beams at both user and base station sides.
Abstract
In millimeter-wave (mmWave) systems, beamforming is needed to overcome harsh channel environments. As a promising beamforming solution, lens antenna array (LAA) implementation can provide a cost-effective solution without notable performance degradation compared to its counterpart. However, an appropriate beam selection is a challenge since it requires efficient channel estimation via an extensive beam training process for perfect beam alignment. In this paper, we propose a high mobility beam and channel tracking algorithm based on the unscented Kalman filter (UKF) to address this challenge, where the channel changes can be monitored over a certain time. The proposed algorithm tracks the channel changes after establishing a connection with an appropriate beam. The algorithm is first introduced in a multi-user beamspace multiple-input multiple-output (MIMO) system with LAA where a single…
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Taxonomy
TopicsAdvanced MIMO Systems Optimization · Millimeter-Wave Propagation and Modeling · Antenna Design and Analysis
