# Energy Efficient Secure Communication Model against Cooperative Eavesdropper
## 1 Introduction  
In an indoor wireless communication network (WCN), different types of network devices and sensors are employed within the network to share information for the purpose of automating multiple functions inside an indoor environment. This results in increased signal transmission and energy usage by the WCN [1, 2]. In this article, we consider the presence of multiple eavesdroppers for the purpose of channel estimation and information estimation, and this leads to wiretap channel system models. Therefore, smart indoor WCN requires energy efficient secure communication and, therefore, green communication technologies, such as wireless power transfer (WPT), which can be adapted for physical layer security (PLS) [3]. High power signals can be used for WPT and other signal processing applications such as channel estimation [4, 5] and as a jamming signal [6, 7]. In a wiretap channel, by using artificial noise (AN), the jammer can degrade the signal to interference plus noise ratio (SINR) of the eavesdroppers [3]. In general, thesecrecy rate of legitimate users in a wiretap channel are improved by degrading SINR eavesdroppers, as in [8; 9], and by employing multiple-input and multiple-output (MIMO) system models, as in [10]. Contrary to SINR degradation at eavesdroppers, the jammer avoids SINR degradation at the legitimate receiver by introducing AN in the null space of the legitimate receiver's channel matrix. Therefore, the jammer improves secrecy rate without compromising the quality of the legitimate users' signal [11]. However, this is considered as a challenge in imperfect CSI condition [12]. Eavesdropper can reduce the impact of AN with the knowledge of channel state information (CSI) of the channel between jammer and receiver but, under normal circumstances, it is highly unlikely for the eavesdropper to have the CSI of the receiver to jammer channel link. Therefore, AN can be effectively used against many robust eavesdroppers, as in [13; 14]. In our previous research work [6], the system model was considered to have a passive eavesdropper with high channel correlation to the legitimate receiver, which is considered as a major limitation of jammer in a wiretap channel. It is mitigated by increasing the jamming signal power that amplifies the error due to the difference in CSI between both channels. The increment in jamming signal power can degrade the eavesdropper's signal to noise ratio (SNR), but this can also increase the negative impact of the jammer's precoding error at legitimate receiver. The effect of the jammer's precoding error at a legitimate receiver can be reduced by using the expected jammer's precoding error as additional noise power feedback in the iterative block decision feedback equalization (IBDFE) decoder [6]. Even though the increase in jamming signal power can increase SNR degradation at the eavesdropper, this is not energy efficient and can degrade the performance of legitimate receiver, if there is any channel estimation error or precoding error in the legitimate network. In [6], the passive eavesdropper does not estimate jamming signal and in this research, the idea of cooperative eavesdropper is explored to estimate jamming signal. Therefore, it is necessary to optimize the jamming signal power and explore counter measures for a cooperative eavesdropper scenario. In this research work, we consider that the eavesdropper can estimate the CSI between the eavesdropper and its the nearest node. With this assumption, we explore the limitation of a legitimate network to act against a robust MIMO cooperative eavesdropper network. There are several studies focused on optimum power allocation at jammer nodes and information transmitter nodes [3; 15]. In [15], the power optimization of jamming signal based on CSI of legitimate receiver to save energy and avoid interference to the legitimate receiver based on its CSI. There are few research works that are focused on multiple eavesdropper scenarios in a wire-tap channel [16; 17; 18].