Tracking abruptly changing channels in mmWave systems using overlaid data and training

Karthik Upadhya, Robert W. Heath Jr., Sergiy Vorobyov

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

2 Citations (Scopus)

Abstract

Millimeter-wave (mmWave) multiple-input multiple-output (MIMO) links are sensitive to abrupt changes in the channel due to blockage and node mobility. We propose to estimate the channel by overlaying pilot and data transmissions. The data transmission is performed over the signal subspace of the channel matrix, while the training, for estimating the parameters of newly appearing paths, is performed over the null-space of the channel matrix. A sparse Bayesian learning-based approach is employed for jointly estimating the channel and data at the receiver. Simulations are used to validate the performance of the proposed method in abruptly changing channel scenarios.
Original languageEnglish
Title of host publicationIEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2017)
PublisherIEEE
Number of pages5
ISBN (Print)978-1-5386-1251-4
DOIs
Publication statusPublished - 2017
MoE publication typeA4 Article in a conference publication
EventIEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing - Caracao, Dutch Antilles, Caracao, Netherlands
Duration: 10 Dec 201713 Dec 2017
Conference number: 7
http://www.cs.huji.ac.il/conferences/CAMSAP17/

Workshop

WorkshopIEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing
Abbreviated titleCAMSAP
CountryNetherlands
CityCaracao
Period10/12/201713/12/2017
Internet address

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    Upadhya, K., Heath Jr., R. W., & Vorobyov, S. (2017). Tracking abruptly changing channels in mmWave systems using overlaid data and training. In IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2017) IEEE. https://doi.org/10.1109/CAMSAP.2017.8313188