Impact of Frequency Offset on Artificial Noise Suppression in SIMO Physical Layer Security Systems

Abstract

Artificial noise (AN) is an effective physical security measure against eavesdropping in wireless communication. In previous literatures, AN is generally analyzed in multiple transmit antenna systems and is suppressed by zero-forcing algorithm, which is implemented by using the spatial degrees of freedom. In this paper, an AN suppression model under single-input multi-output (SIMO) systems is presented, and the impact of imperfect frequency synchronization on the AN suppressed performance is analyzed. Specifically, we first analyze the AN suppression performance of single branch with imperfect frequency synchronization. Then the output signal to interference plus noise ratio (SINR) after multi-branch merging is derived. Finally, the secrecy capacity of AN based on SIMO systems is extracted on the basis of the obtained SINR. Theoretical and simulation results show that imperfect frequency synchronization reduces the SINR of each branch, and thus degrades both the output SINR and secrecy capacity in SIMO systems. Moreover, when the residual AN power is greater than noise power, no diversity gain will be achieved by multi-branch merging.