Secure Uplink Transmission Against Multi-Intelligent Eavesdroppers With Time-Domain Artificial Noise in MIMO IoT Systems

Physical layer security (PLS) has become an intriguing technology to address eavesdropping issues in the Internet of Things (IoT) systems owing to its low complexity and latency. As wireless communication technology and computing capability advance by leaps and bounds, eavesdroppers have enhanced eavesdropping capabilities. They can analyze the environment and move to find better locations for eavesdropping. To mitigate the significant impact of multiple intelligent eavesdroppers extremely close to the device-constrained transmitters in uplink MIMO IoT systems, we exploit time-domain artificial noise (AN) in the PLS design and formulate a game problem against intelligent eavesdroppers. First, we derive the optimal closed-form solution for eavesdroppers and propose a low complexity difference of convex (LCDC) algorithm to obtain the optimal strategy of legitimate users and the access point equipped with a zero-forcing receiver. For general linear receivers, we propose a successive convex approximation (SCA) algorithm for the game problem. Simulations are conducted to verify the convergence and effectiveness of our proposed algorithms. The system secrecy performance of time-domain AN is much better than that of frequency-domain AN with single-antenna transmitters.