What is beam search algorithm?

Explaining The Beam Search Algorithm Beam search is an algorithm used in many NLP and speech recognition models as a final decision making layer to choose the best output given target variables like maximum probability or next output character.

Can position be used for beam prediction?

Leveraging position for beam prediction is motivated by the directional nature of the narrow beams at mmWave and the higher dependency on Line-of-sight (LOS) paths. The mapping relation (function) between the position and the best beam could arguably be learned using prior observations of position- beam pairs, for example at the infrastructure.

Why do mmWave beams need to be adjusted?

Adjusting these beams is typically associated with large training overhead, which becomes particularly critical for highly-mobile applications. Beam selection can benefit from the knowledge of user positions to reduce the overhead in mmWave beam training.

Does position-aided beam alignment work in real-world scenarios?

However, to the best of authors’ knowledge, position-aided beam alignment is yet to be assessed in real- world scenarios. Literature holds numerous examples of leveraging user position data to optimize beam alignment.