Beamforming With Artificial Noise for Secure MISOME Cognitive Radio Transmissions

Abstract

In this paper, we consider multiple-input single-output multi-eavesdropper cognitive radio networks (MISOME-CRNs), where a secondary user (SU) aims to transmit confidential information to a legitimate SU receiver in the presence of a primary user (PU) and a multi-antenna passive eavesdropper in fast fading environments. For this system setting, we study beamforming with artificial noise (AN) for the SU to achieve confidential communications. We consider designing an AN-assisted optimal beamforming scheme, denoted cognitive beamforming (CB), which maximizes the ergodic secrecy rate. Moreover, we propose two suboptimal beamforming schemes, namely, scaled beamforming (SB) and projected beamforming (PB). We develop an analytical framework to assess the performance of the proposed schemes in a unified manner. First, we analyze the achievable ergodic secrecy rate of the three schemes. Second, we derive the optimal power allocation for the information and AN signals that maximizes the achievable ergodic secrecy rate in the large-antenna regime. Third, we study the performance of the three schemes in terms of the secrecy outage probability. Using numerical simulations, we validate our analytical results and show that CB achieves the best performance among the three proposed schemes. In addition, we provide insights into the effect of various system parameters on the secrecy performance. In particular, we show that the interference threshold at the PU plays an important role in the beamforming design. Show more