标题：Secrecy Analysis and Learning-based Optimization of Cooperative NOMA SWIPT Systems
作者：Jameel, Furqan; Khan, Wali Ullah; Chang, Zheng; Ristaniemi, Tapani; Liu, Ju
作者机构：[Jameel, Furqan; Chang, Zheng; Ristaniemi, Tapani] Univ Jyvaskyla, Fac Informat Technol, FI-40014 Jyvaskyla, Finland.; [Khan, Wali Ullah; Liu, Ju] S 更多
会议名称：IEEE International Conference on Communications (ICC)
会议日期：MAY 20-24, 2019
来源：2019 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS WORKSHOPS (ICC WORKSHOPS)
关键词：Decode-and-forward (DF); Deep learning; Non-orthogonal multiple access; (NOMA); Power-splitting
摘要：Non-orthogonal multiple access (NOMA) is considered to be one of the best candidates for future networks due to its ability to serve multiple users using the same resource block. Although early studies have focused on transmission reliability and energy efficiency, recent works are considering cooperation among the nodes. The cooperative NOMA techniques allow the user with a better channel (near user) to act as a relay between the source and the user experiencing poor channel (far user). This paper considers the link security aspect of energy harvesting cooperative NOMA users. In particular, the near user applies the decode-and-forward (DF) protocol for relaying the message of the source node to the far user in the presence of an eavesdropper. Moreover, we consider that all the devices use power-splitting architecture for energy harvesting and information decoding. We derive the analytical expression of intercept probability. Next, we employ deep learning based optimization to find the optimal power allocation factor. The results show the robustness and superiority of deep learning optimization over conventional iterative search algorithm.