Abstract—This paper presents a novel approach to optimizing resource allocation in Internet of Things (IoT) networks, focusing on enhancing energy efficiency (EE) while maintaining age of information (AoI) awareness through device-to-device (D2D) communication. Our proposed solution integrates simultaneous wireless information and power transfer (SWIPT) with energy harvesting (EH) techniques. Specifically, D2D users employ time switching (TS) to harvest energy from the environment, while IoT users utilize power splitting (PS) to obtain energy from base stations (BS).

DOI Link: 
10.21227/fkkw-m915
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[1] Parisa Parhizgar, Mehdi Mahdavi, Mohammad Reza Ahmadzadeh, Melike Erol-Kantarci, "Code of Paper: Federated Reinforcement Learning for Energy-Efficient D2D-IoT Networks with AoI Awareness", IEEE Dataport, 2023. [Online]. Available: http://dx.doi.org/10.21227/fkkw-m915. Accessed: Feb. 07, 2025.
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doi = {10.21227/fkkw-m915},
url = {http://dx.doi.org/10.21227/fkkw-m915},
author = {Parisa Parhizgar; Mehdi Mahdavi; Mohammad Reza Ahmadzadeh; Melike Erol-Kantarci },
publisher = {IEEE Dataport},
title = {Code of Paper: Federated Reinforcement Learning for Energy-Efficient D2D-IoT Networks with AoI Awareness},
year = {2023} }
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T1 - Code of Paper: Federated Reinforcement Learning for Energy-Efficient D2D-IoT Networks with AoI Awareness
AU - Parisa Parhizgar; Mehdi Mahdavi; Mohammad Reza Ahmadzadeh; Melike Erol-Kantarci
PY - 2023
PB - IEEE Dataport
UR - 10.21227/fkkw-m915
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Parisa Parhizgar, Mehdi Mahdavi, Mohammad Reza Ahmadzadeh, Melike Erol-Kantarci. (2023). Code of Paper: Federated Reinforcement Learning for Energy-Efficient D2D-IoT Networks with AoI Awareness. IEEE Dataport. http://dx.doi.org/10.21227/fkkw-m915
Parisa Parhizgar, Mehdi Mahdavi, Mohammad Reza Ahmadzadeh, Melike Erol-Kantarci, 2023. Code of Paper: Federated Reinforcement Learning for Energy-Efficient D2D-IoT Networks with AoI Awareness. Available at: http://dx.doi.org/10.21227/fkkw-m915.
Parisa Parhizgar, Mehdi Mahdavi, Mohammad Reza Ahmadzadeh, Melike Erol-Kantarci. (2023). "Code of Paper: Federated Reinforcement Learning for Energy-Efficient D2D-IoT Networks with AoI Awareness." Web.
1. Parisa Parhizgar, Mehdi Mahdavi, Mohammad Reza Ahmadzadeh, Melike Erol-Kantarci. Code of Paper: Federated Reinforcement Learning for Energy-Efficient D2D-IoT Networks with AoI Awareness [Internet]. IEEE Dataport; 2023. Available from : http://dx.doi.org/10.21227/fkkw-m915
Parisa Parhizgar, Mehdi Mahdavi, Mohammad Reza Ahmadzadeh, Melike Erol-Kantarci. "Code of Paper: Federated Reinforcement Learning for Energy-Efficient D2D-IoT Networks with AoI Awareness." doi: 10.21227/fkkw-m915