Novel Sparse-Coded Ambient Backscatter Communication for Massive IoT Connectivity

Tae Yeong Kim and Dong In Kim
Additional contact information
Tae Yeong Kim: School of Information and Communication Engineering, Sungkyunkwan University, Suwon 440-746, Korea
Dong In Kim: School of Information and Communication Engineering, Sungkyunkwan University, Suwon 440-746, Korea

Energies, 2018, vol. 11, issue 7, 1-25

Abstract: Low-power ambient backscatter communication (AmBC) relying on radio-frequency (RF) energy harvesting is an energy-efficient solution for batteryless Internet of Things (IoT). However, ambient backscatter signals are severely faded by dyadic backscatter channel (DBC), limiting connectivity in conventional orthogonal time-division-based AmBC (TD-AmBC). In order to support massive connectivity in AmBC, we propose sparse-coded AmBC (SC-AmBC) based on non-orthogonal signaling. Sparse code utilizes inherent sparsity of AmBC where power supplies of RF tags rely on ambient RF energy harvesting. Consequently, sparse-coded backscatter modulation algorithm (SC-BMA) can enable non-orthogonal multiple access (NOMA) as well as M -ary modulation for concurrent backscatter transmissions, providing additional diversity gain. These sparse codewords from multiple tags can be efficiently detected at access point (AP) using iterative message passing algorithm (MPA). To overcome DBC along with intersymbol interference (ISI), we propose dyadic channel estimation algorithm (D-CEA) and dyadic MPA (D-MPA) exploiting weighted-sum of the ISI for information exchange in the factor graph. Simulation results validate the potential of the SC-AmBC in terms of connectivity, detection performance and sum throughput.

Keywords: RF energy harvesting; ambient backscatter communication (AmBC); sparse code multiple access (SCMA); dyadic backscatter channel (DBC); iterative decoder (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/1996-1073/11/7/1780/pdf (application/pdf)
https://www.mdpi.com/1996-1073/11/7/1780/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:11:y:2018:i:7:p:1780-:d:156686

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().