Performance Analysis of Artificial Noise-Assisted Location-Based Beamforming in Rician Wiretap Channels

Area of Science:

• Wireless communication
• Signal processing
• Information security

Background:

• Location-based beamforming relies on user location for secure transmission.
• Antenna array size impacts beam shape and differentiation between legitimate users and eavesdroppers.
• Artificial noise (AN) can mitigate eavesdropping risks in wireless networks.

Purpose of the Study:

• To investigate the performance of location-based beamforming with artificial noise (AN).
• To develop a secure beamforming scheme that minimizes eavesdropping risk near a legitimate user.
• To analyze the impact of AN on both legitimate users and eavesdroppers.

Main Methods:

• Leveraging AN to reduce the area with eavesdropping risk.
• Deriving closed-form expressions for signal to interference plus noise ratios (SINRs) and bit error rates.
• Proposing a secure beamforming scheme to meet user SINR requirements and degrade eavesdropper SINR.

Main Results:

• AN effectively minimizes the eavesdropping risk area around the user.
• Closed-form expressions for SINR and bit error rates were derived.
• The proposed scheme ensures a minimum SINR for the legitimate user while minimizing the eavesdropper's SINR.

Conclusions:

• The proposed secure beamforming scheme effectively degrades eavesdropper performance, even with a small number of antennas.
• Artificial noise is a viable technique to enhance security in location-based beamforming systems.
• The method provides a practical solution for improving physical layer security in wireless communications.