In this paper, we propose a cooperative approach to improve the security ofboth primary and secondary systems in cognitive radio multicast communications.During their access to the frequency spectrum licensed to the primary users,the secondary unlicensed users assist the primary system in fortifying securityby sending a jamming noise to the eavesdroppers, while simultaneously protectthemselves from eavesdropping. The main objective of this work is to maximizethe secrecy rate of the secondary system, while adhering to all individualprimary users' secrecy rate constraints. In the case of active eavesdroppersand perfect channel state information (CSI) at the transceivers, the utilityfunction of interest is nonconcave and the involved constraints are nonconvex,and thus, the optimal solutions are troublesome. To solve this problem, wepropose an iterative algorithm to arrive at least to a local optimum of theoriginal nonconvex problem. This algorithm is guaranteed to achieve aKarush-Kuhn-Tucker solution. Then, we extend the optimization approach to thecase of passive eavesdroppers and imperfect CSI knowledge at the transceivers,where the constraints are transformed into a linear matrix inequality andconvex constraints, in order to facilitate the optimal solution.
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