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Self-organized Low-power IoT Networks: ADistributed Learning Approach
KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS, Radio Systems Laboratory (RS Lab).ORCID iD: 0000-0003-0125-2202
KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS, Radio Systems Laboratory (RS Lab).ORCID iD: 0000-0003-0525-4491
2018 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Enabling large-scale energy-efficient Internet-ofthings(IoT) connectivity is an essential step towards realizationof networked society. While legacy wide-area wireless systemsare highly dependent on network-side coordination, the level ofconsumed energy in signaling, as well as the expected increase inthe number of IoT devices, makes such centralized approachesinfeasible in future. Here, we address this problem by selfcoordinationfor IoT networks through learning from pastcommunications. To this end, we first study low-complexity distributedlearning approaches applicable in IoT communications.Then, we present a learning solution to adapt communicationparameters of devices to the environment for maximizing energyefficiency and reliability in data transmissions. Furthermore,leveraging tools from stochastic geometry, we evaluate theperformance of proposed distributed learning solution againstthe centralized coordination. Finally, we analyze the interplayamongst energy efficiency, reliability of communications againstnoise and interference over data channel, and reliability againstadversarial interference over data and feedback channels. Thesimulation results indicate that compared to the state of the artapproaches, both energy efficiency and reliability in IoT communicationscould be significantly improved using the proposedlearning approach. These promising results, which are achievedusing lightweight learning, make our solution favorable in manylow-cost low-power IoT applications.

Place, publisher, year, edition, pages
2018.
Keywords [en]
Coexistence, IoT, Reliability, Battery lifetime, Low-power wide-area network
Keywords [fa]
همزیستی، اینترنت اشیا، عمر باتری، شبکه های کم توان وسیع
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:kth:diva-232212OAI: oai:DiVA.org:kth-232212DiVA, id: diva2:1233081
Conference
IEEE Globecom 2018
Note

QC 20180716

Available from: 2018-07-15 Created: 2018-07-15 Last updated: 2018-07-16Bibliographically approved

Open Access in DiVA

fulltext(1084 kB)34 downloads
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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • vancouver
  • Other style
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Language
  • de-DE
  • en-GB
  • en-US
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  • nn-NO
  • nn-NB
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  • Other locale
More languages
Output format
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  • asciidoc
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