@inproceedings{294270e2f1a1481b83d413128e31b547,
title = "Millimeter Wave Beam Recommendation via Tensor Completion",
abstract = "Accurate and fast beam-alignment is essential to cope with the fast-varying environment in millimeter-wave communications. A data-driven approach is a promising solution to reduce the training overhead by leveraging side information and on-the-field measurements. In this work, a two-stage tensor completion algorithm is proposed to predict the received power on a set of possible users' positions, given received power measurements on a small subset of positions. Based on these predictions and on positional side information, a small subset of beams is recommended to reduce the training overhead of beam-alignment. Numerical results evaluated with the Quadriga channel simulator demonstrate that the proposed algorithm achieves correct alignment with high probability using small training overhead: given power measurement on only 20% of the possible positions when using a discrete coverage area, our algorithm attains a probability of correct alignment of 80%, with only 2% of trained beams, as opposed to a state-of-the-art scheme which achieves 50% correct alignment in the same configuration. To the best of our knowledge, this is the first work to consider the beam recommendation problem based on measurements collected on a small subset of positions.",
keywords = "Millimeter wave, beam-alignment, position-aided, sparse learning, tensor completion",
author = "Chou, {Tzu Hsuan} and Nicolo Michelusi and Love, {David J.} and Krogmeier, {James V.}",
note = "Funding Information: The authors are with the School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA; emails: {chou59, michelus, djlove, jvk}@purdue.edu. This research has been funded by NSF under grant CNS-1642982. Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE International Conference on Communications, ICC 2020 ; Conference date: 07-06-2020 Through 11-06-2020",
year = "2020",
month = jun,
doi = "10.1109/ICC40277.2020.9149275",
language = "English (US)",
series = "IEEE International Conference on Communications",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2020 IEEE International Conference on Communications, ICC 2020 - Proceedings",
}