This paper investigates a secure energy efficiency (SEE) optimization problemin a multiple-input single-output (MISO) underlay cognitive radio (CR) network.In particular, a multi-antenna secondary transmitter (SU-Tx) simultaneouslysends secured information and energy to a secondary receiver (SU-Rx) and anenergy receiver (ER), respectively, in the presence of a primary receiver(PU-Rx). It is assumed that the SU-Rx, ER and PU-Rx are each equipped with asingle antenna. In addition, the SU-Tx should satisfy constraints on maximuminterference leakage to the PU-Rx and minimum harvested energy at the ER. Inthis CR network, we consider the transmit covariance matrix design with theassumption of perfect channel state information (CSI) at the SU-Tx. Inaddition, it is assumed that the ER is a potential passive eavesdropper due tobroadcast nature of wireless transmission. On the other hand, we consider theworst-case scenario that ER's energy harvesting requirement is only satisfiedwhen it performs only energy harvesting without intercepting or eavesdroppinginformation intended for the SU-Rx. We formulate this transmit covariancematrix design as a SEE maximization problem which is a non-convex problem duethe non-linear fractional objective function. To realize the solution for thisnon-convex problem, we utilize the non-linear fractional programming anddifference of concave (DC) functions approaches to reformulate into a tractableform. Based on these techniques and the Dinkelbach's method, we proposeiterative algorithms to determine the solution for the original SEEmaximization problem. Numerical simulation results are provided to demonstratethe performance of the proposed transmit covariance matrix design andconvergence of the proposed algorithms.
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