Efficient Beam Search for Initial Access Using Collaborative Filtering
George Yammine, Georgios Kontes, Norbert Franke, Axel Plinge,, Christopher Mutschler

TL;DR
This paper introduces a scalable, easy-to-implement beam search method for initial access in beamforming systems, leveraging collaborative filtering to improve beam alignment efficiency and robustness across multiple base stations.
Contribution
It proposes a novel recommender system-based algorithm for initial beam discovery that outperforms standard methods and is scalable and simple to deploy.
Findings
Outperforms baseline algorithms in simulations
Effective in multi-base station setups
Robust and efficient beam discovery
Abstract
Beamforming-capable antenna arrays overcome the high free-space path loss at higher carrier frequencies. However, the beams must be properly aligned to ensure that the highest power is radiated towards (and received by) the user equipment (UE). While there are methods that improve upon an exhaustive search for optimal beams by some form of hierarchical search, they can be prone to return only locally optimal solutions with small beam gains. Other approaches address this problem by exploiting contextual information, e.g., the position of the UE or information from neighboring base stations (BS), but the burden of computing and communicating this additional information can be high. Methods based on machine learning so far suffer from the accompanying training, performance monitoring and deployment complexity that hinders their application at scale. This paper proposes a novel method for…
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Taxonomy
TopicsMillimeter-Wave Propagation and Modeling · Advanced MIMO Systems Optimization · Antenna Design and Optimization
MethodsBalanced Selection
