Enhancement of PLS Model of Massive MIMO by Detecting Eavesdrop Attacks and Improving the Secrecy Capacity of the System Based on Optimization Strategy

Physical layer security (PLS) is becoming an interesting subject since it guarantees to deliver the most consistent and secure communication in wireless systems in both present and future scenarios. The security can be obtained without considering any assumption over the computational power of eavesdroppers. The massive MIMO that can render high power and spectrum effectiveness are discussed in detail in this work. The artificial noise injection zero-forcing pre-coding scheme is proposed to improve PLS of Massive MIMOs. The artificial noise is injected into the ZF pre-coder to destroy the eavesdropper’s performance. In addition, the detection of eavesdrop attack is analyzed based on hypothesis condition ( H 0 : no active attack present, H 1 : presence of active attack). The secrecy capacity of the system is improved by the intrusion of a game based optimization strategy. Here, the enhancement of secrecy rate is improved by the channel amplitude. The performance of the suggested model is evaluated in terms of secrecy rate, secrecy outage probability, and bit error rate and compared to existing approaches to enhance the efficacy of the suggested model.