@inproceedings{3984b439e60a414eba9ee6e74483d3e7,
title = "LSTM-Based Multi-Link Prediction for mmWave and Sub-THz Wireless Systems",
abstract = "A key challenge in mmWave systems is the rapid variations in channel quality along different beam directions. MmWave links are highly susceptible to blockage and small changes in the orientation of the device or appearance of blockers can lead to dramatic changes in link quality along any given direction. Many low-latency applications need to accurately predict link quality from multiple directions and multiple cells. This paper presents a novel long short term memory (LSTM)-based method for predicting multi-directional link quality in mmWave systems. The method is validated on two problems: A realistic simulation of multi-cell link tracking in an environment with randomly moving human and vehicular blockers at 28 and 140 GHz, and beam prediction in a real indoor setting at 60 GHz.",
keywords = "LSTM, Millimeter wave, cellular wireless, machine learning",
author = "Shah, {Syed Hashim Ali} and Manali Sharma and Sundeep Rangan",
note = "Funding Information: VI. CONCLUSIONS Link prediction in the mmWave and sub-THz frequencies requires predicting link quality from multiple cells and multiple directions. Classical statistical prediction methods for link quality evaluation are difficult since the underlying process has complex dependencies in time and across links. We propose an LSTM method and evaluate the technique and both realistic multi-cellular simulations at 28 and 140 GHz and actual indoor data at 60 GHz. The results show that LSTMs can offer significantly better link prediction performance than simple baseline linear estimators. ACKNOWLEDGEMENTS This work was supported by the National Science Foundation under Grants 1302336, 1564142, and 1547332, NIST, SRC and the industrial affiliates of NYU WIRELESS. 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/ICC40277.2020.9148975",
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",
}