Periodic Reporting for period 1 - IRS-THz (Intelligent Reflecting Surface (IRS) Assisted Ultra-massive MIMO THz Communications for 6G)
Reporting period: 2021-12-01 to 2023-11-30
The project “IRS-THz” worked by Dr. Hao Xu from 01/12/2021 to 30/11/2023 has been successfully completed under the supervision of Prof. Kai-Kit Wong. In addition, Dr. Xu also worked closely with the group of Prof. Giuseppe Caire (Technical University Berlin, Germany) to complete the coding scheme in wiretap channels. Through the four work packages, we systematically study the theoretical modeling, performance analysis, performance optimization, and experimental characterization of intelligent reflecting surface (IRS) or fluid antenna system (FAS) assisted communication. Based on that, this project has resulted in several different designs of FAS that show intriguing performance gains, including much lower outage probability in multi-user networks, greatly enhanced secrecy in wiretap channels, where the eavesdroppers exist, and increased system capacity over the systems using the conventional fixed-position antennas. This project shows successful attempts on the application of FAS in multi-user communication systems, and provides many insightful theoretical and experimental foundations for the future study of FAS. The project combined the expertise of Dr. Xu and the host supervisor in the fundamentals of communication, information theory, and techniques of FAS, and equipped Dr. Xu to conduct cutting-edge research on FAS in various application scenarios.
The specific objectives for the project “IRS-THz” described in the proposal are listed in the following:
RO1: To design hierarchical multi-resolution codebooks and determine the phase-shift matrix of the IRS.
RO2: To design adaptive beam alignment methods and develop an IRS-assisted THz testbed.
RO3: To design extended Kalman filter (EKF) based beam tracking and machine learning (ML) empowered dynamic beam switching methods.
RO4: To design joint resource allocation algorithms for an IRS-assisted multi-UE multi-carrier THz network.
All these research objectives have been achieved.
The specific objectives for the project “IRS-THz” described in the proposal are listed in the following:
RO1: To design hierarchical multi-resolution codebooks and determine the phase-shift matrix of the IRS.
RO2: To design adaptive beam alignment methods and develop an IRS-assisted THz testbed.
RO3: To design extended Kalman filter (EKF) based beam tracking and machine learning (ML) empowered dynamic beam switching methods.
RO4: To design joint resource allocation algorithms for an IRS-assisted multi-UE multi-carrier THz network.
All these research objectives have been achieved.
WP1: Hierarchical multi-resolution codebook and IRS phase-shift matrix design.
In this work package, Dr. Xu designed coding schemes for multi-access wiretap channels under the strong secrecy metric. Different decoding schemes were considered at the legitimate receiver, i.e. joint decoding scheme and independent decoding scheme. Codebooks that involve secret, open, and redundant messages were designed for both cases. It was shown that by allowing users with zero secrecy rate to play different roles, the achievable region in the existing literature can be strictly enlarged. In addition, Dr. Xu also analyzed the outage probability of FAS-assisted systems. By proposing two schemes to approximate the channel model, the computational complexity of the analysis was significantly reduced.
WP2: Adaptive beam alignment methods design and IRS-assisted THz testbed setup.
In this work package, Dr. Xu proposed the coding-enhanced cooperative jamming scheme to enhance the communication secrecy and also developed a novel beamforming approach with extremely low computational complexity. Traditionally, the cooperative jammer transmits Gaussian noise (GN) to enhance the security. However, with this approach, the jamming signal interferes not only with Eve but also with Bob. Therefore, Dr. Xu proposed that besides the GN strategy, the jammer can also choose to use the encoded jammer (EJ) strategy, i.e. instead of GN, it transmits a codeword from an appropriate codebook so that Bob can decode the information and cancel the interference, but Eve cannot. The beamforming problem requires the solution of log-determinant optimizations in each iteration, yielding extremely high complexity. To address the issue, Dr. Xu proposed a novel approach based on matrix simultaneous diagonalization (SD). Using this technique, the beamforming problems associated with different jamming schemes can be efficiently solved with comparable performance (often better) and much less computational complexity than the MM-based method.
WP3: EKF-based beam tracking and ML-empowered dynamic beam switching methods design.
By using the compressed sensing methods, Dr. Xu developed a channel estimation scheme for a multi-user mmWave system, where users apply the fluid antenna technique to communicate with the BS. Taking advantage of the sparse characteristics of the channels, the proposed scheme requires each antenna to move and measure the channel over only a few estimating locations and can reconstruct full CSI with quite low hardware switching and pilot overhead.
WP4: Joint resource allocation for an IRS-assisted multi-UE multi-carrier THz network.
Dr. Xu investigated the capacity of a FAS-assisted MAC system. First, he derived upper bounds and approximations for the capacity, which not only provide valuable insights, but also serve as benchmarks for evaluating the performance of FAS. Then, he maximized the sum capacity by designing the transmit covariance matrices and antenna position vectors of the users. Simulation results have validated the effectiveness of FAS in increasing the system capacity, and also the proposed algorithms over the considered benchmarks.
During this project, Dr. Xu has published 7 papers in high-impact journals and flagship conferences in our research area. Two more papers are still under review.
In this work package, Dr. Xu designed coding schemes for multi-access wiretap channels under the strong secrecy metric. Different decoding schemes were considered at the legitimate receiver, i.e. joint decoding scheme and independent decoding scheme. Codebooks that involve secret, open, and redundant messages were designed for both cases. It was shown that by allowing users with zero secrecy rate to play different roles, the achievable region in the existing literature can be strictly enlarged. In addition, Dr. Xu also analyzed the outage probability of FAS-assisted systems. By proposing two schemes to approximate the channel model, the computational complexity of the analysis was significantly reduced.
WP2: Adaptive beam alignment methods design and IRS-assisted THz testbed setup.
In this work package, Dr. Xu proposed the coding-enhanced cooperative jamming scheme to enhance the communication secrecy and also developed a novel beamforming approach with extremely low computational complexity. Traditionally, the cooperative jammer transmits Gaussian noise (GN) to enhance the security. However, with this approach, the jamming signal interferes not only with Eve but also with Bob. Therefore, Dr. Xu proposed that besides the GN strategy, the jammer can also choose to use the encoded jammer (EJ) strategy, i.e. instead of GN, it transmits a codeword from an appropriate codebook so that Bob can decode the information and cancel the interference, but Eve cannot. The beamforming problem requires the solution of log-determinant optimizations in each iteration, yielding extremely high complexity. To address the issue, Dr. Xu proposed a novel approach based on matrix simultaneous diagonalization (SD). Using this technique, the beamforming problems associated with different jamming schemes can be efficiently solved with comparable performance (often better) and much less computational complexity than the MM-based method.
WP3: EKF-based beam tracking and ML-empowered dynamic beam switching methods design.
By using the compressed sensing methods, Dr. Xu developed a channel estimation scheme for a multi-user mmWave system, where users apply the fluid antenna technique to communicate with the BS. Taking advantage of the sparse characteristics of the channels, the proposed scheme requires each antenna to move and measure the channel over only a few estimating locations and can reconstruct full CSI with quite low hardware switching and pilot overhead.
WP4: Joint resource allocation for an IRS-assisted multi-UE multi-carrier THz network.
Dr. Xu investigated the capacity of a FAS-assisted MAC system. First, he derived upper bounds and approximations for the capacity, which not only provide valuable insights, but also serve as benchmarks for evaluating the performance of FAS. Then, he maximized the sum capacity by designing the transmit covariance matrices and antenna position vectors of the users. Simulation results have validated the effectiveness of FAS in increasing the system capacity, and also the proposed algorithms over the considered benchmarks.
During this project, Dr. Xu has published 7 papers in high-impact journals and flagship conferences in our research area. Two more papers are still under review.
Impact on Dr. Hao Xu’s career:
The opportunities provided by this fellowship are extremely important for Dr. Hao Xu's academic career. During the two years of the project, Dr. Xu has successfully become an internationally leading young researcher in the field of IRS and FAS. Dr. Xu has great potential for the "Outstanding Young Scholars of China" project in 2024. As expected, he has gained extensive skills in theoretical modeling, analysis, optimization and experimental characterization of IRS from the "IRS-THz" project. The project has greatly enhanced his knowledge and experience in communications, information theory, and electrical engineering. With such a strong background, he will become an excellent leading researcher in the research field.
Impact of applicant’s activity on European Society:
The European society has benefited from the research results on IRS and FAS obtained in this project. This project has introduced both new theoretical and experimental tools for the analysis and characterization of FAS. New methodologies and fundamental insights in this field could have a significant economic and environmental impact. Recently, FAS has become a popular topic and addressed wide attention. Unlike massive multiple-input multiple-output (MIMO) or antenna selection techniques that require many RF chains over fixed antennas, FAS can help reduce hardware costs while still taking full advantage of the spatial channel variation in a given region. However, many aspects of FAS are still unknown such as how to estimate the CSI, what are the outage probability and capacity performance like, how to further optimize the performance, etc. In the project, Dr. Xu has proposed low-complexity channel estimation schemes to estimate the CSI of FAS, and has also proposed different approaches to approximate the channel model such that the outage probability of the system can be computed in a more efficient way. Moreover, he has also studied the resource allocation problems in FAS-assisted system such that the capacity and secrecy performance can be greatly enhanced. These results could have a significant economic and environmental impact.
The opportunities provided by this fellowship are extremely important for Dr. Hao Xu's academic career. During the two years of the project, Dr. Xu has successfully become an internationally leading young researcher in the field of IRS and FAS. Dr. Xu has great potential for the "Outstanding Young Scholars of China" project in 2024. As expected, he has gained extensive skills in theoretical modeling, analysis, optimization and experimental characterization of IRS from the "IRS-THz" project. The project has greatly enhanced his knowledge and experience in communications, information theory, and electrical engineering. With such a strong background, he will become an excellent leading researcher in the research field.
Impact of applicant’s activity on European Society:
The European society has benefited from the research results on IRS and FAS obtained in this project. This project has introduced both new theoretical and experimental tools for the analysis and characterization of FAS. New methodologies and fundamental insights in this field could have a significant economic and environmental impact. Recently, FAS has become a popular topic and addressed wide attention. Unlike massive multiple-input multiple-output (MIMO) or antenna selection techniques that require many RF chains over fixed antennas, FAS can help reduce hardware costs while still taking full advantage of the spatial channel variation in a given region. However, many aspects of FAS are still unknown such as how to estimate the CSI, what are the outage probability and capacity performance like, how to further optimize the performance, etc. In the project, Dr. Xu has proposed low-complexity channel estimation schemes to estimate the CSI of FAS, and has also proposed different approaches to approximate the channel model such that the outage probability of the system can be computed in a more efficient way. Moreover, he has also studied the resource allocation problems in FAS-assisted system such that the capacity and secrecy performance can be greatly enhanced. These results could have a significant economic and environmental impact.