Robust Transmit Power Control With Imperfect CSI Using a Deep Neural Network
- Authors
- Lee, Woongsup; Lee, 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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