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Cited 7 time in webofscience Cited 8 time in scopus
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Robust Transmit Power Control With Imperfect CSI Using a Deep Neural Network

Authors
Lee, WoongsupLee, Kisong
Issue Date
Nov-2021
Publisher
Institute of Electrical and Electronics Engineers
Keywords
Power control; Device-to-device communication; Quality of service; Optimization; Interference; Channel estimation; Resource management; Deep neural network; imperfect channel state information; robust power control; underlay D2D
Citation
IEEE Transactions on Vehicular Technology, v.70, no.11, pp 12266 - 12271
Pages
6
Indexed
SCIE
SCOPUS
Journal Title
IEEE Transactions on Vehicular Technology
Volume
70
Number
11
Start Page
12266
End Page
12271
URI
https://scholarworks.gnu.ac.kr/handle/sw.gnu/3042
DOI
10.1109/TVT.2021.3113051
ISSN
0018-9545
1939-9359
Abstract
In this paper, a robust transmit power control scheme is proposed for multi-channel underlay device-to-device (D2D) communications with imperfect channel state information (CSI). The transmit power of the D2D user equipment (DUE) on each channel is optimized to maximize the average spectral efficiency (SE) whilst maintaining the quality-of-service (QoS) of the cellular user equipment (CUE) in the presence of errors in the CSI. To this end, we propose a novel deep neural network (DNN) structure and training methodology, in which artificially distorted CSI is used to compensate for the effect of imperfect CSI, such that a robust transmit power control strategy against channel error can be derived. Our simulation results show that even when the CSI is inaccurate, in our proposed scheme the degradation of the average SE can be kept low whilst maintaining negligible QoS violation, thereby confirming its effectiveness and robustness.
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