A Unified Rate-Splitting Framework for Secure Spectrum Sharing via Joint Precoding Optimization

Li, D.; Yang, Z.; Zhao, N.; Chen, Y.; Wu, Z.; Li, Y.

Abstract

To handle the security problem of cognitive radio (CR) systems, secondary users (SUs) are able to be designed to assist the primary user (PU) in secure transmission. To realize the spectrum sharing among CR users, we adopt the rate-splitting multiple access (RSMA) properly, with non-orthogonal multiple access (NOMA) and space division multiple access (SDMA) as its special cases. In this paper, we set up a unified ratesplitting framework to guarantee the safe spectrum sharing through multiple multi-access strategies, without the knowledge of wiretap channels. The precoding vectors at the transmitter are conjointly designed to boost the transmission of common stream, which is from both PU and SU. Besides, the private stream of the downlink CR system can be well secreted in the high-power common signal. As for NOMA and SDMA, when the message of SU is regarded as the friendly jamming signal, the security transmission requirement of PU can be similarly guaranteed via precoding design. Simulations validate that the rate-splitting framework we established can be effective in ensuring the spectrum sharing security for the secure users through RSMA, and the security for NOMA and SDMA is also able to be promoted through adjusting our designed framework.

Citation

Li, D., Yang, Z., Zhao, N., Chen, Y., Wu, Z., & Li, Y. (2023). A Unified Rate-Splitting Framework for Secure Spectrum Sharing via Joint Precoding Optimization. IEEE Systems Journal, 17(4), 5580-5591. https://doi.org/10.1109/jsyst.2023.3254603

• Journal Article Type: Article
• Acceptance Date: Mar 6, 2023
• Online Publication Date: Mar 22, 2023
• Publication Date: 2023-12
• Deposit Date: Mar 10, 2023
• Publicly Available Date: Mar 10, 2023
• Journal: IEEE Systems Journal
• Print ISSN: 1932-8184
• Electronic ISSN: 1937-9234
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 17
• Issue: 4
• Pages: 5580-5591
• DOI: https://doi.org/10.1109/jsyst.2023.3254603
• Public URL: https://durham-repository.worktribe.com/output/1178650