2017/07/07 by Van‐Dinh Nguyen, Trung Q. Duong, Nguyen, Van-Dinh +7
Computer Science · Engineering · #Advanced MIMO Systems Optimization #Cognitive Radio Networks and Spectrum Sensing #FOS: Computer and information sciences #Information Theory (cs.IT) #Wireless Communication Security Techniques
paper · pdf · doi:10.48550/arxiv.1707.02380
openalex publication_date 2017/07/07 · openalex created_date 2022/10/03 · openalex updated_date 2026/07/28
In this paper, we propose a cooperative approach to improve the security of\nboth primary and secondary systems in cognitive radio multicast communications.\nDuring their access to the frequency spectrum licensed to the primary users,\nthe secondary unlicensed users assist the primary system in fortifying security\nby sending a jamming noise to the eavesdroppers, while simultaneously protect\nthemselves from eavesdropping. The main objective of this work is to maximize\nthe secrecy rate of the secondary system, while adhering to all individual\nprimary users' secrecy rate constraints. In the case of active eavesdroppers\nand perfect channel state information (CSI) at the transceivers, the utility\nfunction of interest is nonconcave and the involved constraints are nonconvex,\nand thus, the optimal solutions are troublesome. To solve this problem, we\npropose an iterative algorithm to arrive at least to a local optimum of the\noriginal nonconvex problem. This algorithm is guaranteed to achieve a\nKarush-Kuhn-Tucker solution. Then, we extend the optimization approach to the\ncase of passive eavesdroppers and imperfect CSI knowledge at the transceivers,\nwhere the constraints are transformed into a linear matrix inequality and\nconvex constraints, in order to facilitate the optimal solution.\n