IRS-enhanced DFRC System Joint Beamforming Optimization Design

With the continuous broadbandization of radar sensing systems and wireless communication systems,the similarity between the two in terms of transmit beamforming design and other aspects is getting higher and higher.The Dual-Function Radar and Communication(DFRC)system can greatly improve the performance by integrating radar equipment and communication equipment into one system which may reduce hardware cost and transmit power.However,when the sensing target is in a crowded area dominated by pathloss,the signal energy will be too small due to excessive attenuation,which will lead to the problem of insufficient radar detection performance.Fortunately,the field of metamaterials has developed by leaps and bounds in recent years.The Intelligent Reflecting Surface(IRS)technology has attracted the attention of scientific researchers because of its ability to intelligently change the characteristics of the wireless channel.Therefore,using IRS to assist DFRC systems to achieve better radar detection performance for sensing targets in crowded areas has become one of the potential solutions,and beamforming design is the key issue.Aiming at the shortcomings of the current IRS-assisted DFRC system model that does not meet the detection target as a clutter source scenario,this thesis proposes an improved model that adds the channel including the reflection path ignored by the current system model.Then,based on the improved model,the radar receiving Signal-Noise Ratio(SNR)is used as the performance index of target estimation,and the transmit beamforming and IRS passive reflection beamforming are jointly optimized,and the proposed method is to ensure the prediction of a single communication user.The study of maximizing target estimates while defining the SNR.By proposing alternate iterative algorithm A and Successive Lower Bound Maximization(SLBM)algorithm A,a stationary solution is obtained.The simulation shows that the proposed model and algorithm indeed improve the radar detection performance,which is about 1d B higher than the traditional non-clutter source model.Besides,with the increase of the number of IRS reflectors,the improvement is greater.Secondly,this thesis further expands to multi-user scenarios.Based on the improved model,the radar received SNR is used as the performance index of target estimation,the transmit beamforming and IRS passive reflection beamforming are jointly optimized,and the target estimation is maximized while ensuring the predefined Signal to Interference plus Noise Ratio(SINR)of multiple communication users.By proposing alternate iteration algorithm B and SLBM algorithm B,a stable solution is obtained.Simulation shows that the proposed model and algorithm do improve the radar detection performance.The simulation shows that the proposed model and algorithm indeed improve the radar detection performance.Compared with the 1d B improvement in the single-user scenario,in order to satisfy the SINR of multiple users at the same time,the radar detection performance decreases slightly,and the more the number of users,the lower the radar detection performance.Finally,this thesis considers a physical layer security scenario,when there is an eavesdropper around the communication user,trying to eavesdrop on the user’s communication,and study the use of beamforming design to achieve user safety communication based on the maximum radar detection performance.The main work includes: based on the improved model,the performance index of radar receiving SNR is used as the target estimation,the transmit beamforming and IRS passive reflection beamforming are jointly optimized,and the research is proposed to maximize the target estimation while ensuring the predefined SNR of a single communication user and suppressing the predefined SNR of eavesdroppers.By proposing alternating iterative algorithm C and SLBM algorithm C,a stable solution is obtained.The simulation shows that the proposed model and algorithm indeed improve the radar detection performance.Compared with the 1d B improvement in the single-user scenario,when the SNR suppression of the eavesdropper is very high,the radar detection performance decreases by about 0.2d B.