Secrecy energy efficiency optimization for artificial noise aided physical-layer security in cognitive radio networks

In this paper, the artificial noise (AN) is used to improve the secrecy energy efficiency (SEE) for underlay cognitive radio networks (CRNs). A joint zero-forcing (ZF) beamforming and power allocation problem is formulated to maximize the SEE under the constraints of the total transmit power, the secrecy rate (SR) of cognitive user (CU) and the quality-of-service (QoS) requirement of primary user (PU). As a consequence, we firstly transform the formulated non-convex optimization problem in fractional form into an equivalent one in subtractive form, and use the difference of two-convex functions (D.C.) approximation method to obtain an equivalent convex problem. Then, a power allocation algorithm is presented to obtain the optimal solution. Simulation results show the advantage ofthe proposed scheme.