This paper proposes a resource allocation strategy for multi-channel underlay cognitive radio (CR) systems by means of an ensemble deep learning framework. The transmit power of secondary users (SUs) allocated to each channel is determined to maximize the overall spectral efficiency (SE), whilst meeting the interference constraint on the primary user (PU). To this end, a deep neural network (DNN) structure is developed, in which multiple DNN units are jointly utilized, to obtain the diversity over different DNNs. Our simulation results confirm that the proposed scheme can achieve near-optimal performance with a low computation time of less than 1.5 ms.
|Publication status||Accepted/In press - 2022|
Bibliographical noteFunding Information:
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2021R1F1A1046932 ).
© 2022 The Authors
All Science Journal Classification (ASJC) codes
- Information Systems
- Hardware and Architecture
- Computer Networks and Communications
- Artificial Intelligence