Throughput Optimization in Ambient Backscatter-Based Energy Constraint Cognitive Radio Networks

Title
Throughput Optimization in Ambient Backscatter-Based Energy Constraint Cognitive Radio Networks
Publication Date
2024
Author(s)
Shah, Syed Tariq
Fazal, Maheen
Shawky, Mahmoud A
Sohaib, Rana M
Hasan, Syed Faraz
( author )
OrcID: https://orcid.org/0009-0006-5345-2790
Email: shasan3@une.edu.au
UNE Id une-id:shasan3
Imran, M Ali
Abbasi, Qammer H
Type of document
Conference Publication
Language
en
Entity Type
Publication
Publisher
Institute of Electrical and Electronics Engineers
Place of publication
United States of America
DOI
10.1109/ICCWorkshops59551.2024.10615668
UNE publication id
une:1959.11/62944
Abstract

Efficient utilisation of scarce resources, mainly radio and power, are the key research issues in the future Internet of Things (IoT) networks. This paper proposes an ambient energy harvesting and backscatter-enabled, energy-constrained cognitive IoT network. In our proposed scheme, the nodes in the secondary network efficiently utilise the primary network. More specifically, depending on the communication states (i.e. between busy or idle) of the primary network, the secondary nodes chose to operate either in energy harvesting mode (EHM), backscattering mode (BSM), or radio-frequency transmission mode (RFM). Furthermore, to maximise the sum-throughput of the secondary network, an optimisation problem is formulated and solved. The simulation results show that the proposed scheme outperforms the existing scheme regarding network sum-throughput.

Link
Citation
Proceedings of the International Conference on Communications Workshops, ICC Workshops 2024, p. 2029-2033
ISSN
2694-2941
2164-7038
ISBN
9798350304053
9798350304060
Start page
2029
End page
2033

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