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dc.contributor.authorSafi, Hossein
dc.contributor.authorAkbari, Mohammad
dc.contributor.authorVaezpour, Elaheh
dc.contributor.authorParsaeefard, Saeedeh
dc.contributor.authorShubair, Raed M.
dc.date.accessioned2021-09-20T17:41:35Z
dc.date.available2021-09-20T17:41:35Z
dc.date.issued2021-03-06
dc.identifier.urihttps://hdl.handle.net/1721.1/132038
dc.description.abstractAbstract The idea of employing deep autoencoders (AEs) has been recently proposed to capture the end-to-end performance in the physical layer of communication systems. However, most of the current methods for applying AEs are developed based on the assumption that there exists an explicit channel model for training that matches the actual channel model in the online transmission. The variation of the actual channel indeed imposes a major limitation on employing AE-based systems. In this paper, without relying on an explicit channel model, we propose an adaptive scheme to increase the reliability of an AE-based communication system over different channel conditions. Specifically, we partition channel coefficient values into sub-intervals, train an AE for each partition in the offline phase, and constitute a bank of AEs. Then, based on the actual channel condition in the online phase and the average block error rate (BLER), the optimal pair of encoder and decoder is selected for data transmission. To gain knowledge about the actual channel conditions, we assume a realistic scenario in which the instantaneous channel is not known, and propose to blindly estimate it at the Rx, i.e., without any pilot symbols. Our simulation results confirm the superiority of the proposed adaptive scheme over existing methods in terms of the average power consumption. For instance, when the target average BLER is equal to $$10^{-4}$$ 10 - 4 , our proposed algorithm with 5 pairs of AE can achieve a performance gain over 1.2 dB compared with a non-adaptive scheme.en_US
dc.publisherSpringer International Publishingen_US
dc.relation.isversionofhttps://doi.org/10.1186/s13638-021-01929-zen_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceSpringer International Publishingen_US
dc.titleAutoencoder-bank based design for adaptive channel-blind robust transmissionen_US
dc.typeArticleen_US
dc.identifier.citationEURASIP Journal on Wireless Communications and Networking. 2021 Mar 06;2021(1):47en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.contributor.departmentMassachusetts Institute of Technology. Research Laboratory of Electronics
dc.identifier.mitlicensePUBLISHER_CC
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2021-03-07T05:53:12Z
dc.language.rfc3066en
dc.rights.holderThe Author(s)
dspace.embargo.termsN
dspace.date.submission2021-03-07T05:53:12Z
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Needed


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