Show simple item record

dc.contributor.authorKumar, Swarun
dc.contributor.authorVasisht, Deepak
dc.contributor.authorRahul, Hariharan Shankar
dc.contributor.authorKatabi, Dina
dc.date.accessioned2018-05-11T20:01:46Z
dc.date.available2018-05-11T20:01:46Z
dc.date.issued2016-08
dc.identifier.issn978-1-4503-4193-6
dc.identifier.urihttp://hdl.handle.net/1721.1/115348
dc.description.abstractThis paper focuses on a simple, yet fundamental question: ``Can a node infer the wireless channels on one frequency band by observing the channels on a different frequency band?'' This question arises in cellular networks, where the uplink and the downlink operate on different frequencies. Addressing this question is critical for the deployment of key 5G solutions such as massive MIMO, multi-user MIMO, and distributed MIMO, which require channel state information. We introduce R2-F2, a system that enables LTE base stations to infer the downlink channels to a client by observing the uplink channels from that client. By doing so, R2-F2 extends the concept of reciprocity to LTE cellular networks, where downlink and uplink transmissions occur on different frequency bands. It also removes a major hurdle for the deployment of 5G MIMO solutions. We have implemented R2-F2 in software radios and integrated it within the LTE OFDM physical layer. Our results show that the channels computed by R2-F2 deliver accurate MIMO beamforming (to within 0.7~dB of beamforming gains with ground truth channels) while eliminating channel feedback overhead.en_US
dc.language.isoen_US
dc.publisherAssociation for Computing Machineryen_US
dc.relation.isversionofhttp://dx.doi.org/10.1145/2934872.2934895en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceMIT Web Domainen_US
dc.titleEliminating Channel Feedback in Next-Generation Cellular Networksen_US
dc.typeArticleen_US
dc.identifier.citationVasisht, Deepak, et al. "Eliminating Channel Feedback in Next-Generation Cellular Networks." Proceedings of the 2016 ACM SIGCOMM Conference, 22-26 August, 2016, Florianopolis, Brazil, ACM Press, 2016, pp. 398–411.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
dc.contributor.mitauthorVasisht, Deepak
dc.contributor.mitauthorRahul, Hariharan Shankar
dc.contributor.mitauthorKatabi, Dina
dc.relation.journalProceedings of the 2016 conference on ACM SIGCOMM 2016 Conference - SIGCOMM '16en_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dspace.orderedauthorsVasisht, Deepak; Kumar, Swarun; Rahul, Hariharan; Katabi, Dinaen_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0003-4959-8472
dc.identifier.orcidhttps://orcid.org/0000-0003-4854-4157
mit.licenseOPEN_ACCESS_POLICYen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record