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Rui Zhang - One of the best experts on this subject based on the ideXlab platform.
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enabling smart Reflection in integrated air ground wireless network irs meets uav
arXiv: Information Theory, 2021Co-Authors: Changsheng You, Yong Zeng, Zhenyu Kang, Rui ZhangAbstract:Intelligent reflecting surface (IRS) and unmanned aerial vehicle (UAV) have emerged as two promising technologies to boost the performance of wireless communication networks, by proactively altering the wireless communication channels via smart Signal Reflection and maneuver control, respectively. However, they face different limitations in practice, which restrain their future applications. In this article, we propose new methods to jointly apply IRS and UAV in integrated air-ground wireless networks by exploiting their complementary advantages. Specifically, terrestrial IRS is used to enhance the UAV-ground communication performance, while UAV-mounted IRS is employed to assist in the terrestrial communication. We present their promising application scenarios, new communication design issues as well as potential solutions. In particular, we show that it is practically beneficial to deploy both the terrestrial and aerial IRSs in future wireless networks to reap the benefits of smart Reflections in three-dimensional (3D) space.
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cooperative beam routing for multi irs aided communication
IEEE Wireless Communications Letters, 2021Co-Authors: Weidong Mei, Rui ZhangAbstract:Intelligent reflecting surface (IRS) has been deemed as a transformative technology to achieve smart and reconfigurable environment for wireless communication. This letter studies a new IRS-aided communication system, where multiple IRSs assist in the communication between a multi-antenna base station (BS) and a remote single-antenna user by multi-hop Signal Reflection. Specifically, by exploiting the line-of-sight (LoS) link between nearby IRSs, a multi-hop cascaded LoS link between the BS and user is established where a set of IRSs are selected to successively reflect the BS’s Signal, so that the received Signal power at the user is maximized. To tackle this new problem, we first present the closed-form solutions for the optimal active and cooperative passive beamforming at the BS and selected IRSs, respectively, for a given beam route. Then, we derive the end-to-end channel power, which unveils a fundamental trade-off in the optimal beam routing design between maximizing the multiplicative passive beamforming gain and minimizing the multi-Reflection path loss. To reconcile this trade-off, we recast the IRS selection and beam routing problem as an equivalent shortest simple-path problem in graph theory and solve it optimally. Numerical results show significant performance gains of the proposed algorithm over benchmark schemes and also draw useful insights into the optimal beam routing design.
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intelligent reflecting surface aided multi user communication capacity region and deployment strategy
arXiv: Information Theory, 2020Co-Authors: Shuowen Zhang, Rui ZhangAbstract:Intelligent reflecting surface (IRS) is a new promising technology that is able to reconfigure the wireless propagation channel via smart and passive Signal Reflection. In this paper, we investigate the capacity region of a communication network with two users served by an access point (AP), aided by $M$ IRS reflecting elements. In particular, we consider two practical IRS deployment strategies that lead to different effective channels between the users and AP, namely, the distributed deployment where the $M$ reflecting elements form two IRSs, each deployed in the vicinity of one user, versus the centralized deployment where all the $M$ reflecting elements are deployed in the vicinity of the AP. First, we consider the uplink multiple access channel (MAC) and derive the capacity/achievable rate regions for both deployment strategies under different multiple access schemes. It is shown that the centralized deployment generally outperforms the distributed deployment under symmetric channel setups in terms of achievable user rates. Next, we extend the results to the downlink broadcast channel (BC) by leveraging the celebrated uplink-downlink (or MAC-BC) duality framework, and show that the superior rate performance of centralized over distributed deployment also holds. Numerical results are presented that validate our analysis, and reveal new and useful insights for optimal IRS deployment in wireless networks.
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intelligent reflecting surface aided wireless communications a tutorial
arXiv: Information Theory, 2020Co-Authors: Shuowen Zhang, Beixiong Zheng, Changsheng You, Rui ZhangAbstract:Intelligent reflecting surface (IRS) is an enabling technology to engineer the radio Signal prorogation in wireless networks. By smartly tuning the Signal Reflection via a large number of low-cost passive reflecting elements, IRS is capable of dynamically altering wireless channels to enhance the communication performance. It is thus expected that the new IRS-aided hybrid wireless network comprising both active and passive components will be highly promising to achieve a sustainable capacity growth cost-effectively in the future. Despite its great potential, IRS faces new challenges to be efficiently integrated into wireless networks, such as Reflection optimization, channel estimation, and deployment from communication design perspectives. In this paper, we provide a tutorial overview of IRS-aided wireless communication to address the above issues, and elaborate its Reflection and channel models, hardware architecture and practical constraints, as well as various appealing applications in wireless networks. Moreover, we highlight important directions worthy of further investigation in future work.
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intelligent reflecting surface practical phase shift model and beamforming optimization
IEEE Transactions on Communications, 2020Co-Authors: Samith Abeywickrama, Rui Zhang, Chau YuenAbstract:Intelligent reflecting surface (IRS) that enables the control of wireless propagation environment has recently emerged as a promising cost-effective technology for boosting the spectral and energy efficiency of future wireless communication systems. Prior works on IRS are mainly based on the ideal phase shift model assuming full Signal Reflection by each of its elements regardless of the phase shift, which, however, is practically difficult to realize. In contrast, we propose in this paper a practical phase shift model that captures the phase-dependent amplitude variation in the element-wise Reflection design. Based on the proposed model and considering an IRS-aided multiuser system with one IRS deployed to assist in the downlink communications from a multi-antenna access point (AP) to multiple single-antenna users, we formulate an optimization problem to minimize the total transmit power at the AP by jointly designing the AP transmit beamforming and the IRS reflect beamforming, subject to the users’ individual Signal-to-interference-plus-noise ratio (SINR) constraints. Iterative algorithms are proposed to find suboptimal solutions to this problem efficiently by utilizing the alternating optimization (AO) as well as penalty-based optimization techniques. Moreover, to draw essential insight, we analyze the asymptotic performance loss of the IRS-aided system that employs practical phase shifters but assumes the ideal phase shift model for beamforming optimization, as the number of IRS elements goes to infinity. Simulation results unveil substantial performance gains achieved by the proposed beamforming optimization based on the practical phase shift model as compared to the conventional ideal model.
Zhang Rui - One of the best experts on this subject based on the ideXlab platform.
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IRS Meets Relaying: Joint Resource Allocation and Passive Beamforming Optimization
2021Co-Authors: Zheng Beixiong, Zhang RuiAbstract:Intelligent reflecting surface (IRS) has recently emerged as a new solution to enhance wireless communication performance via passive Signal Reflection. In this letter, we unlock the potential of IRS controller in relaying information and propose a novel IRS-assisted communication system with both IRS passive Reflection and active relaying. Specifically, we jointly optimize the time allocations for decode-and-forward (DF) relaying by the IRS controller and the IRS passive beamforming to maximize the achievable rate of the proposed system. We also compare the rate performance of the proposed system with the conventional IRS without relaying, and reveal the conditions for one to outperform the other. Simulation results demonstrate that the proposed new design can significantly improve the coverage/rate performance of IRS-assisted systems.Comment: To increase the coverage range without increasing the deployment/hardware cost, we propose a novel IRS-assisted communication system by unlocking the IRS controller for relaying information in addition to its conventional role of tuning the Reflections of IRS elements onl
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Enabling Smart Reflection in Integrated Air-Ground Wireless Network: IRS Meets UAV
2021Co-Authors: You Changsheng, Kang Zhenyu, Zeng Yong, Zhang RuiAbstract:Intelligent reflecting surface (IRS) and unmanned aerial vehicle (UAV) have emerged as two promising technologies to boost the performance of wireless communication networks, by proactively altering the wireless communication channels via smart Signal Reflection and maneuver control, respectively. However, they face different limitations in practice, which restrain their future applications. In this article, we propose new methods to jointly apply IRS and UAV in integrated air-ground wireless networks by exploiting their complementary advantages. Specifically, terrestrial IRS is used to enhance the UAV-ground communication performance, while UAV-mounted IRS is employed to assist in the terrestrial communication. We present their promising application scenarios, new communication design issues as well as potential solutions. In particular, we show that it is practically beneficial to deploy both the terrestrial and aerial IRSs in future wireless networks to reap the benefits of smart Reflections in three-dimensional (3D) space.Comment: In this article, we propose new methods to jointly apply IRS and UAV in integrated air-ground wireless networks by exploiting their complementary advantage
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Double-IRS Assisted Multi-User MIMO: Cooperative Passive Beamforming Design
2021Co-Authors: Zheng Beixiong, You Changsheng, Zhang RuiAbstract:Intelligent reflecting surface (IRS) has emerged as an enabling technology to achieve smart and reconfigurable wireless communication environment cost-effectively. Prior works on IRS mainly consider its passive beamforming design and performance optimization without the inter-IRS Signal Reflection, which thus do not unveil the full potential of multi-IRS assisted wireless networks. In this paper, we study a double-IRS assisted multi-user communication system with the \emph{cooperative} passive beamforming design that captures the multiplicative beamforming gain from the inter-IRS channel. Under the general channel setup with the co-existence of both double- and single-Reflection links, we jointly optimize the (active) receive beamforming at the base station (BS) and the cooperative (passive) reflect beamforming at the two distributed IRSs (deployed near the BS and users, respectively) to maximize the minimum Signal-to-interference-plus-noise ratio (SINR) of all users. Moreover, for the single-user and multi-user setups, we analytically show the superior performance of the double-IRS cooperative system over the conventional single-IRS system in terms of the maximum Signal-to-noise ratio (SNR) and multi-user effective channel rank, respectively. Simulation results validate our analytical results and show the practical advantages of the proposed double-IRS system with cooperative passive beamforming designs.Comment: Early access in IEEE TWC (https://ieeexplore.ieee.org/document/9362274). We answer the following fundamental question: whether partitioning the IRS elements/subsurfaces into distributed but cooperative IRSs is superior to combining them as one single IRS or not. Efficient channel estimation (arXiv:2010.06155) and (arXiv:2011.00738
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Intelligent Reflecting Surface Aided Multi-User Communication: Capacity Region and Deployment Strategy
2021Co-Authors: Zhang Shuowen, Zhang RuiAbstract:Intelligent reflecting surface (IRS) is a new promising technology that is able to reconfigure the wireless propagation channel via smart and passive Signal Reflection. In this paper, we investigate the capacity region of a two-user communication network with one access point (AP) aided by $M$ IRS elements for enhancing the user-AP channels, where the IRS incurs negligible delay, thus the user-AP channels via the IRS follow the classic discrete memoryless channel model. In particular, we consider two practical IRS deployment strategies that lead to different effective channels between the users and AP, namely, the distributed deployment where the $M$ elements form two IRSs, each deployed in the vicinity of one user, versus the centralized deployment where all the $M$ elements are deployed in the vicinity of the AP. First, we consider the uplink multiple-access channel (MAC) and derive the capacity/achievable rate regions for both deployment strategies under different multiple access schemes. It is shown that the centralized deployment generally outperforms the distributed deployment under symmetric channel setups in terms of achievable user rates. Next, we extend the results to the downlink broadcast channel (BC) by leveraging the celebrated uplink-downlink (or MAC-BC) duality framework, and show that the superior rate performance of centralized over distributed deployment also holds. Numerical results are presented that validate our analysis, and reveal new and useful insights for optimal IRS deployment in wireless networks.Comment: To appear in IEEE Transactions on Communications. arXiv admin note: text overlap with arXiv:2002.0709
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Two-timescale Beamforming Optimization for Intelligent Reflecting Surface Aided Multiuser Communication with QoS Constraints
2021Co-Authors: Zhao Ming-min, An Liu, Wan Yubo, Zhang RuiAbstract:Intelligent reflecting surface (IRS) is an emerging technology that is able to reconfigure the wireless channel via tunable passive Signal Reflection and thereby enhance the spectral and energy efficiency of wireless networks cost-effectively. In this paper, we study an IRS-aided multiuser multiple-input single-output (MISO) wireless system and adopt the two-timescale (TTS) transmission to reduce the Signal processing complexity and channel training overhead as compared to the existing schemes based on the instantaneous channel state information (I-CSI), and at the same time, exploit the multiuser channel diversity in transmission scheduling. Specifically, the long-term passive beamforming is designed based on the statistical CSI (S-CSI) of all links, while the short-term active beamforming is designed to cater to the I-CSI of all users' reconfigured channels with optimized IRS phase shifts. We aim to minimize the average transmit power at the access point (AP), subject to the users' individual quality of service (QoS) constraints. The formulated stochastic optimization problem is non-convex and difficult to solve since the long-term and short-term design variables are complicatedly coupled in the QoS constraints. To tackle this problem, we propose an efficient algorithm, called the primal-dual decomposition based TTS joint active and passive beamforming (PDD-TJAPB), where the original problem is decomposed into a long-term problem and a family of short-term problems, and the deep unfolding technique is employed to extract gradient information from the short-term problems to construct a convex surrogate problem for the long-term problem. The proposed algorithm is proved to converge to a stationary solution of the original problem almost surely. Simulation results are presented which demonstrate the advantages and effectiveness of the proposed algorithm as compared to benchmark schemes.Comment: 16 pages, 10 figures, accepted by IEEE Transactions on Wireless communication
Chau Yuen - One of the best experts on this subject based on the ideXlab platform.
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intelligent reflecting surface practical phase shift model and beamforming optimization
IEEE Transactions on Communications, 2020Co-Authors: Samith Abeywickrama, Rui Zhang, Chau YuenAbstract:Intelligent reflecting surface (IRS) that enables the control of wireless propagation environment has recently emerged as a promising cost-effective technology for boosting the spectral and energy efficiency of future wireless communication systems. Prior works on IRS are mainly based on the ideal phase shift model assuming full Signal Reflection by each of its elements regardless of the phase shift, which, however, is practically difficult to realize. In contrast, we propose in this paper a practical phase shift model that captures the phase-dependent amplitude variation in the element-wise Reflection design. Based on the proposed model and considering an IRS-aided multiuser system with one IRS deployed to assist in the downlink communications from a multi-antenna access point (AP) to multiple single-antenna users, we formulate an optimization problem to minimize the total transmit power at the AP by jointly designing the AP transmit beamforming and the IRS reflect beamforming, subject to the users’ individual Signal-to-interference-plus-noise ratio (SINR) constraints. Iterative algorithms are proposed to find suboptimal solutions to this problem efficiently by utilizing the alternating optimization (AO) as well as penalty-based optimization techniques. Moreover, to draw essential insight, we analyze the asymptotic performance loss of the IRS-aided system that employs practical phase shifters but assumes the ideal phase shift model for beamforming optimization, as the number of IRS elements goes to infinity. Simulation results unveil substantial performance gains achieved by the proposed beamforming optimization based on the practical phase shift model as compared to the conventional ideal model.
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intelligent reflecting surface practical phase shift model and beamforming optimization
International Conference on Communications, 2020Co-Authors: Samith Abeywickrama, Rui Zhang, Chau YuenAbstract:Intelligent reflecting surface (IRS) that enables the control of the wireless propagation environment has been looked upon as a promising technology for boosting the spectrum and energy efficiency in future wireless communication systems. Prior works on IRS are mainly based on the ideal phase shift model assuming the full Signal Reflection by each of the elements regardless of its phase shift, which, however, is practically difficult to realize. In contrast, we propose in this paper a practical phase shift model that captures the phase-dependent amplitude variation in the element-wise Reflection coefficient. Applying this new model to an IRS-aided wireless system, we formulate a problem to maximize its achievable rate by jointly optimizing the transmit beamforming and the IRS reflect beamforming. The formulated problem is non-convex and difficult to be optimally solved in general, for which we propose a low-complexity suboptimal solution based on the alternating optimization (AO) technique. Simulation results unveil a substantial performance gain achieved by the joint beamforming optimization based on the proposed phase shift model as compared to the conventional ideal model.
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intelligent reflecting surface practical phase shift model and beamforming optimization
arXiv: Signal Processing, 2019Co-Authors: Samith Abeywickrama, Rui Zhang, Chau YuenAbstract:Intelligent reflecting surface (IRS) that enables the control of wireless propagation environment has recently emerged as a promising cost-effective technology for boosting the spectrum and energy efficiency in future wireless communication systems. Prior works on IRS are mainly based on the ideal phase shift model assuming the full Signal Reflection by each of the elements regardless of its phase shift, which, however, is practically difficult to realize. In contrast, we propose in this paper the practical phase shift model that captures the phase-dependent amplitude variation in the element-wise Reflection coefficient. Based on the proposed model and considering an IRS-aided multiuser system with an IRS deployed to assist in the downlink communications from a multi-antenna access point (AP) to multiple single-antenna users, we formulate an optimization problem to minimize the total transmit power at the AP by jointly designing the AP transmit beamforming and the IRS reflect beamforming, subject to the users' individual Signal-to-interference-plus-noise ratio (SINR) constraints. Iterative algorithms are proposed to find suboptimal solutions to this problem efficiently by utilizing the alternating optimization (AO) or penalty-based optimization technique. Moreover, we analyze the asymptotic performance loss of the IRS-aided system that employs practical phase shifters but assumes the ideal phase shift model for beamforming optimization, as the number of IRS elements goes to infinity. Simulation results unveil substantial performance gains achieved by the proposed beamforming optimization based on the practical phase shift model as compared to the conventional ideal model.
Masanobu Shimada - One of the best experts on this subject based on the ideXlab platform.
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model based polarimetric sar calibration method using forest and surface scattering targets
International Geoscience and Remote Sensing Symposium, 2011Co-Authors: Masanobu ShimadaAbstract:This paper proposes a new polarimetric Synthetic Aperture Radar (PolSAR) calibration method that applies an incoherent decomposition model to the uncalibrated covariance data measured for the forest and surface, and determines the polarimetric distortion matrix (PDM). The Freeman-Durden model [1] is used to express the polarization dependent Signal Reflection from and penetration through the forest. Non-linear equations built for uncalibrated PolSAR data are solved iteratively. This method is applicable to the lower frequency SAR that associates with the polarization dependent Signal penetration through forest canopies. Using the time series Phased Array Type L-band SAR (PALSAR) data acquired for the Amazon rainforest for around 3 years, we confirm that the proposed method succeeds the PDM estimation and that the calibrated data preserve the polarimetric performance on HH-VV orthogonality, low cross-talks, and ideal polarimetric signature for the corner reflector.
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model based polarimetric sar calibration method using forest and surface scattering targets
IEEE Transactions on Geoscience and Remote Sensing, 2011Co-Authors: Masanobu ShimadaAbstract:This paper proposes a new polarimetric synthetic aperture radar (SAR) (PolSAR) calibration method that applies an incoherent decomposition model to the uncalibrated covariance data measured for the forest and surface and determines the polarimetric distortion matrix (PDM). The Freeman-Durden model is used to express the polarization-dependent Signal Reflection from and penetration through the forest. Nonlinear equations built for uncalibrated PolSAR data are solved iteratively. This method is applicable to the lower frequency SAR that associates with the polarization-dependent Signal penetration through forest canopies. Using the time series Phased-Array-Type L-band SAR (PALSAR) data acquired from the Amazon rainforest for around three years, we confirm that the proposed method succeeds in the PDM estimation and that the calibrated data preserve the polarimetric performance on HH-VV orthogonality, low crosstalks, and ideal polarimetric signature for the corner reflector. This paper also investigates the Signal-penetration properties of the forest associated with the L-band SAR.
Samith Abeywickrama - One of the best experts on this subject based on the ideXlab platform.
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intelligent reflecting surface practical phase shift model and beamforming optimization
IEEE Transactions on Communications, 2020Co-Authors: Samith Abeywickrama, Rui Zhang, Chau YuenAbstract:Intelligent reflecting surface (IRS) that enables the control of wireless propagation environment has recently emerged as a promising cost-effective technology for boosting the spectral and energy efficiency of future wireless communication systems. Prior works on IRS are mainly based on the ideal phase shift model assuming full Signal Reflection by each of its elements regardless of the phase shift, which, however, is practically difficult to realize. In contrast, we propose in this paper a practical phase shift model that captures the phase-dependent amplitude variation in the element-wise Reflection design. Based on the proposed model and considering an IRS-aided multiuser system with one IRS deployed to assist in the downlink communications from a multi-antenna access point (AP) to multiple single-antenna users, we formulate an optimization problem to minimize the total transmit power at the AP by jointly designing the AP transmit beamforming and the IRS reflect beamforming, subject to the users’ individual Signal-to-interference-plus-noise ratio (SINR) constraints. Iterative algorithms are proposed to find suboptimal solutions to this problem efficiently by utilizing the alternating optimization (AO) as well as penalty-based optimization techniques. Moreover, to draw essential insight, we analyze the asymptotic performance loss of the IRS-aided system that employs practical phase shifters but assumes the ideal phase shift model for beamforming optimization, as the number of IRS elements goes to infinity. Simulation results unveil substantial performance gains achieved by the proposed beamforming optimization based on the practical phase shift model as compared to the conventional ideal model.
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intelligent reflecting surface practical phase shift model and beamforming optimization
International Conference on Communications, 2020Co-Authors: Samith Abeywickrama, Rui Zhang, Chau YuenAbstract:Intelligent reflecting surface (IRS) that enables the control of the wireless propagation environment has been looked upon as a promising technology for boosting the spectrum and energy efficiency in future wireless communication systems. Prior works on IRS are mainly based on the ideal phase shift model assuming the full Signal Reflection by each of the elements regardless of its phase shift, which, however, is practically difficult to realize. In contrast, we propose in this paper a practical phase shift model that captures the phase-dependent amplitude variation in the element-wise Reflection coefficient. Applying this new model to an IRS-aided wireless system, we formulate a problem to maximize its achievable rate by jointly optimizing the transmit beamforming and the IRS reflect beamforming. The formulated problem is non-convex and difficult to be optimally solved in general, for which we propose a low-complexity suboptimal solution based on the alternating optimization (AO) technique. Simulation results unveil a substantial performance gain achieved by the joint beamforming optimization based on the proposed phase shift model as compared to the conventional ideal model.
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intelligent reflecting surface practical phase shift model and beamforming optimization
arXiv: Signal Processing, 2019Co-Authors: Samith Abeywickrama, Rui Zhang, Chau YuenAbstract:Intelligent reflecting surface (IRS) that enables the control of wireless propagation environment has recently emerged as a promising cost-effective technology for boosting the spectrum and energy efficiency in future wireless communication systems. Prior works on IRS are mainly based on the ideal phase shift model assuming the full Signal Reflection by each of the elements regardless of its phase shift, which, however, is practically difficult to realize. In contrast, we propose in this paper the practical phase shift model that captures the phase-dependent amplitude variation in the element-wise Reflection coefficient. Based on the proposed model and considering an IRS-aided multiuser system with an IRS deployed to assist in the downlink communications from a multi-antenna access point (AP) to multiple single-antenna users, we formulate an optimization problem to minimize the total transmit power at the AP by jointly designing the AP transmit beamforming and the IRS reflect beamforming, subject to the users' individual Signal-to-interference-plus-noise ratio (SINR) constraints. Iterative algorithms are proposed to find suboptimal solutions to this problem efficiently by utilizing the alternating optimization (AO) or penalty-based optimization technique. Moreover, we analyze the asymptotic performance loss of the IRS-aided system that employs practical phase shifters but assumes the ideal phase shift model for beamforming optimization, as the number of IRS elements goes to infinity. Simulation results unveil substantial performance gains achieved by the proposed beamforming optimization based on the practical phase shift model as compared to the conventional ideal model.