Joint Transceiver Optimization for Artificial Noise-Aided Anti-Terrorism Emergency Communication with Imperfect CSI

Artificial noise (AN) can degrade eavesdroppers' signal-to-noise ratio (SNR) in anti-terrorism emergency communications to secure tactical data transmissions. However, system secrecy performance depends on licensed receivers' AN cancellation capabilities. Imperfect channel state information (CSI) will induce residual AN at licensed receivers, thereby degrading system secrecy performance. Unlike the previous methods of simply optimizing power allocation at the transmitter, this study proposes a joint transceiver optimization scheme to mitigate the impact of channel estimation error. Firstly, we present an ANaided anti-terrorism emergency communication model and theoretically derive the statistical properties of the channel estimation error and the closed-form expression of the achievable secrecy rate. Then, a joint optimization scheme for power allocation at the transmitter and cancellation factor at the receiver is presented to maximize the achievable secrecy rate. On this basis, the optimal values of power allocation weight and cancellation factor are derived. The simulation and analysis results prove that the proposed optimization scheme can effectively improve the system security performance in the presence of channel estimation error, and its achievable secrecy rate can be improved by about 16% compared with the power allocation alone.