Abstract
In a wiretap channel system model, the jammer node adopts the energy-harvesting signal as artificial noise (jamming signal) against the cooperative eavesdroppers. There are two eavesdroppers in the wiretap channel: eavesdropper E1 is located near the transmitter and eavesdropper E2 is located near the jammer. The eavesdroppers are equipped with multiple antennas and employ the iterative block decision feedback equalization decoder to estimate the received signal, i.e., information signal at E1 and jamming signal at E2. It is assumed that E1 has the channel state information (CSI) of the channel between transmitter and E1, and similarly, E2 has the CSI of channel between jammer and E2. The eavesdroppers establish communication link between them and cooperate with each other to reduce the information signal interference at E2 and jamming signal interference at E1. The performance of decoders depends on the signal to interference plus noise ratio (SINR) of the received signal. The power of information signal is fixed and the power of the jamming signal is adjusted to improve the SINR of the received signal. This research work is solely focused on optimizing the jamming signal power to degrade the performance of cooperative eavesdroppers. The jamming signal power is optimized for the given operating SINR with the support of simulated results. The jamming signal power optimization leads to better energy conservation and degrades the performance of eavesdroppers.
Highlights
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
If J reduces the transmit power of jamming signal to reduce the signal to interference plus noise ratio (SINR) at E2, this will reduce the interference of XJ at E1 but, at the same time, the quality of jamming signal estimate will reduce at E2
For the sake of simplicity, the passive eavesdroppers that are used for estimating A to E1, and J to E2 channel links are not mentioned in the system model. )
Summary
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. 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. In our work, we consider that the MIMO eavesdropper is closer to the jammer and detects the jamming signal and cooperates with the eavesdropper nearer to the transmitter to estimate information. Under these special circumstances, the research work is focused on hardware configuration and optimum power allocation for the jammer node. X , Xand Xdenote sample, hard decision and soft decision, respectively, and the appropriate Identity matrix of X is denoted as IN
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