TY - GEN
T1 - Novel Scalable DNN-based Relay Selection Scheme for Wireless Powered Communication Networks
AU - Tolebi, Gulnur
AU - Amirgaliyev, Yedilkhan
AU - Nauryzbayev, Galymzhan
N1 - Funding Information:
VI. ACKNOWLEDGMENT This research is funded by Nazarbayev University under Collaborative Research Program Grant no. 11022021CRP1513 (PI: Galymzhan Nauryzbayev).
Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - In this paper, we propose an optimal relay selection scheme based on a deep neural network (DNN) to evaluate and minimize the outage probability (OP) in cooperative wireless powered communication networks (WPCNs). We explicitly split the relay selection problem into two parts: OP estimation and relay selection itself. We first consider the task from the perspective of the supervised learning regression problem. We train offline the DNN-based model on synthetic data. The proposed model is easy to scale for a network of any size since it predicts OP for each relay separately. Then, based on the results obtained in the previous step, the node with a minimum OP value is selected. Simulation results show that the proposed DNN-based relay selection scheme achieves minimum OP and exhibits the lowest mean square error than the models based on the state-of-the-art machine learning approaches.
AB - In this paper, we propose an optimal relay selection scheme based on a deep neural network (DNN) to evaluate and minimize the outage probability (OP) in cooperative wireless powered communication networks (WPCNs). We explicitly split the relay selection problem into two parts: OP estimation and relay selection itself. We first consider the task from the perspective of the supervised learning regression problem. We train offline the DNN-based model on synthetic data. The proposed model is easy to scale for a network of any size since it predicts OP for each relay separately. Then, based on the results obtained in the previous step, the node with a minimum OP value is selected. Simulation results show that the proposed DNN-based relay selection scheme achieves minimum OP and exhibits the lowest mean square error than the models based on the state-of-the-art machine learning approaches.
KW - deep neural network (DNN)
KW - outage probability (OP)
KW - Relay selection
KW - wireless powered communication network (WPCN)
UR - http://www.scopus.com/inward/record.url?scp=85165683285&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85165683285&partnerID=8YFLogxK
U2 - 10.1109/BalkanCom58402.2023.10167964
DO - 10.1109/BalkanCom58402.2023.10167964
M3 - Conference contribution
AN - SCOPUS:85165683285
T3 - 2023 International Balkan Conference on Communications and Networking, BalkanCom 2023
BT - 2023 International Balkan Conference on Communications and Networking, BalkanCom 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 International Balkan Conference on Communications and Networking, BalkanCom 2023
Y2 - 5 June 2023 through 8 June 2023
ER -