E-grāmata: Intelligent Reflecting Surface-Aided Physical-Layer Security

Contents 1 Intelligent Reflecting Surface-aided Physical-layer Security
Communications.- 1.1 Overview of Physical-layer Security.- 1.2 Overview of
Intelligent Reflecting Surface.- 1.3 Organization of    the Monograph.-
References.- 2 Enhanced Secrecy Rate Maximization for Directional Modulation
Networks via IRS.- 2.1 Introduction.- 2.2 System Model.- 2.3 Proposed
high-performance GAI-based Max-SR method.- 2.3.1 Optimize the beamforming
vectors v1 and v2 given the IRS phase-shift matrix .- 2.3.2 Optimize IRS
phase-shift matrix  given the beamforming vectors.- 2.3.3 Overall
Algorithm.- 2.4 Proposed low-complexity NSP-based Max-SR method.- 2.4.1
Optimization of beamforming vectors given IRS phase-shift matrix .- 2.4.2
Optimization of IRS phase-shift matrix  with given beamforming vectors.-
2.4.3 Overall Algorithm.- 2.5 Simulation and Discussion.- 2.5.1 Impact of the
Number of IRS Phase-shift.- 2.5.2 Impact of the IRS Location.- 2.6
Conclusion..- References.- Contents 3 High-performance Estimation of Jamming
Covariance Matrix for IRS-aided Directional Modulation Network with a
Malicious Attacker.- 3.1 Introduction.- 3.2 System Model.- 3.3 Proposed Three
Estimation Methods.- 3.3.1 Proposed EVD method.- 3.3.2 Proposed PEM-GD
method.- 3.3.3 Proposed PEM-AO method.- 3.3.4 Computational Complexity
Analysis and CRLBs.- 3.4 Simulation results and Discussions.- 3.5
Conclusion.- References.- 4 Beamforming and Power Allocation for
Double-IRS-aided Two-Way Directional Modulation Network.- 4.1 Introduction.-
4.2 System Model and Problem Formulation.- 4.3 Proposed Transmit Beamforming
Methods.- 4.3.1 Proposed GPG Method of Synthesizing the Phase-Shifting
Matrices at Two IRSs.-  4.3.2 Proposed Max-SV Method.- 4.3.3 Generalized
leakage method 4.4 Proposed HICF Power Allocation Strategy.- 4.4.1 Problem
formulation.- 4.4.2 2D-ES and 1D-ES PA strategies.- 4.4.3 Proposed HICF PA
strategy.- 4.5 Simulation Results andDiscussions.- 4.6 Conclusion.- 4.7
Appendix.- References.- 5 Beamforming and Transmit Power Design for
Intelligent Reconfigurable Surface-aided Secure Spatial Modulation.- 5.1
Introduction.- 5.2 System Model.- 5.2.1 IRS-Aided Secure Spatial Modulation
System.- 5.2.2 Problem Formulation.- 5.3 Approximation of the Ergodic Mutual
Information.- 5.3.1 Traditional Approximate Secrecy Rate Expression.- 5.3.2
Proposed Newly Approximate Secrecy Rate Expression.- 5.4 Beamforming Design
for given transmit power based on Approximate expression of SR.- 5.4.1
Proposed Max-NASR-SCA.- 5.4.2 Proposed Max-NASR-DA.- 5.4.3 Proposed
Max-TASR-SDR method.- 5.5 Transmit Power Design for Given Beamforming based
on Approximate Expression of SR.- 5.5.1 Transmit Power Design based on
Proposed NASR.- 5.5.2 Transmit Power Design based on TASR.- 5.6 Complexity
Analysis.- 5.7 Simulation Results and Analysis.- 5.7.1 Rayleigh fading
channel.- 5.7.2 Rayleigh fading channel considering path loss.- 5.8
Conclusion.- References.- 6 IRS-Aided Covert Wireless Communications with
Delay Constraint.- 6.1 Introduction.- 6.2 System Model.- 6.2.1 Considered
Scenario and Assumptions.- 6.2.2 Binary Hypothesis Testing at Willie.- 6.2.3
Transmission from Alice to Bob.- 6.3 Covert Communication Design with Global
Channel State Information.- 6.3.1 Optimization Problem and Perfect Covertness
Condition.- 6.3.2 Joint Transmit Power and Reflect Beamforming Design.- 6.3.3
Low-Complexity Algorithm.- 6.4 Covert Communication Design without Willies
instantaneous CSI.- 6.4.1 Expression for Covertness Constraint.- 6.4.2
Optimal Design without Willies Instantaneous CSI.- 6.5 Numerical Results.-
6.5.1 With Global CSI.- 6.5.2 Without Willies Instantaneous CSI.- 6.6
Conclusion.- 6.7 Appendix.- 6.7.1 Proof of Theorem 6.1.- 6.7.2 Proof of Lemma
6.1.- 6.7.3 Proof of Theorem 6.2.- References.- 7 Intelligent Reflecting
Surface Aided Secure Transmission with Colluding Eavesdroppers.- 7.1
Introduction.- 7.2 System Model and Problem Formulation.- 7.3 Proposed
Solutions.- 7.3.1 SDR-Based Method.- 7.3.2 Proposed LC-AO Algorithm.- 7.4
Simulation Results.- 7.5 Conclusion.- References.- 8 Secure Multigroup
Multicast Communication Systems via Intelligent Reflecting Surface.- 8.1
Introduction.- 8.2 System Model.- 8.3 SDR-based Alternating Optimization
Method.- 8.3.1 Optimization with respect to {W, Q}.- 8.3.2 Optimization
with respect to U.- 8.3.3 Overall Algorithm and Complexity Analysis.- 8.4
Low-complexity SOCP-based Algorithm.- 8.4.1 Optimization with respect to
beamforming vector and AN.- 8.4.2 Optimization with respect to phase shifts.-
8.4.3 Overall Algorithm and Complexity Analysis.- 8.5 Simulation and
analysis.- 8.6 Conclusion.- References.- 9 Beamforming Design for IRS-aided
Decode-and-Forward Relay Wireless Network.- 9.1 Introduction.- 9.2 System
Model.- 9.3 Proposed Three High-Performance Beamforming Schemes.- 9.3.1
Proposed AIS-based Max-RP Method.- 9.3.2 Proposed NSP-based Max-RP plus MRC
Method.- 9.3.3 Proposed IRSES-based Max-RP plus MRC Method.- 9.4 Numerical
Results.- 9.5 Conclusion.- References.- 10 Performance Analysis of Wireless
Network Aided by Discrete[ 1]Phase-Shifter IRS.- 10.1 Introduction..- 10.2
System Model.- 10.3 Performance Loss Derivation and Analysis in the LoS
Channels.- 10.3.1 Derivation of Performance Loss in LoS Channels.- 10.3.2
Performance Loss of SNR at Bob.- 10.3.3 Performance Loss of Achievable Rate
at Bob.- 10.3.4 Performance Loss of BER at Bob.- 10.4 Performance Loss
Derivation and Analysis in the Rayleigh Channels.- 10.4.1 Derivation of
Performance Loss in the Rayleigh Channels.- 10.4.2 Performance Loss of SNR at
Bob.- 10.4.3 Performance Loss of Achievable Rate at Bob.- 10.4.4 Performance
Loss of BER at Bob.- 10.5 Simulation Results and Discussions.- 10.6
Conclusion.- References.- 11 Conclusions and Future Research Directions.

Feng Shu received the Ph.D. degree in Information and Communication Engineering from Southeast University, China, in 2002.  From September 2009 to September 2010, he was a Visiting Post-doctor with the University of Texas at Dallas, Richardson, TX, USA. From October 2005 to November 2020, he was with the School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, where he was promoted from Associate Professor to a Full Professor of supervising Ph.D. students in 2013. Since December 2020, he has been with the School of Information and Communication Engineering, Hainan University, Haikou, China, where he is currently a Professor and supervisor of Ph.D. and graduate students. His research interests include wireless networks, wireless location, and array signal processing. He is awarded with the Leading-talent Plan of Hainan Province in 2020, Fujian hundred-talent plan of Fujian Province in 2018, and Mingjian Scholar Chair Professor in 2015. He has authored or coauthored more than 300 in archival journals with more than 120 papers on IEEE Journals and 200 SCI-indexed papers. His citations are 4386. He holds thirty Chinese patents and also are PI or CoPI for seven national projects. He was an IEEE Transactions on Communications Exemplary Reviewer for 2020. He is currently the Editor of IEEE Wireless Communications Letters and was an editor for the IEEE Systems Journal. Jiangzhou Wang is a professor with the University of Kent, U.K. He has published more than 400 papers and four books. His research focuses on mobile communications. He was a recipient of the 2022 IEEE Communications Society Leonard G. Abraham Prize and IEEE Globecom2012 Best Paper Award. He was the Technical Program Chair of the 2019 IEEE International Conference on Communications (ICC2019), Shanghai, Executive Chair of the IEEE ICC2015, London, and Technical Program Chair of the IEEE WCNC2013. He is/was the editor of a number of international journals, including IEEE Transactions on Communications from 1998 to 2013. Professor Wang is a Fellow of the Royal Academy of Engineering, U.K., Fellow of the IEEE, and Fellow of the IET