Showing papers on "Beamforming published in 2021"

Ultra-Wideband Antennas and Propagation: For Communications, Radar and Imaging

Abstract: Editors. Prime Contributors. Preface. Acknowledgments. Abbreviations & Acronyms. 1 Introduction to UWB Signals and Systems (Andreas F. Molisch). 1.1 History of UWB. 1.2 Motivation. 1.3 UWB Signals and Systems. 1.4 Frequency Regulation. 1.5 Applications, Operating Scenarios and Standardisation. 1.6 System Outlook. References. Part I Fundamentals. Introduction to Part I (Wasim Q. Malik and David J. Edwards). 2 Fundamental Electromagnetic Theory (Mischa Dohler). 2.1 Introduction. 2.2 Maxwell's Equations. 2.3 Resulting Principles. References. 3 Basic Antenna Elements (Mischa Dohler). 3.1 Introduction. 3.2 Hertzian Dipole. 3.3 Antenna Parameters and Terminology. 3.4 Basic Antenna Elements. References. 4 Antenna Arrays (Ernest E. Okon). 4.1 Introduction. 4.2 Point Sources. 4.3 The Principle of Pattern Multiplication. 4.4 Linear Arrays of n Elements. 4.5 Linear Broadside Arrays with Nonuniform Amplitude Distributions. 4.6 Planar Arrays. 4.7 Design Considerations. 4.8 Summary. References. 5 Beamforming (Ben Allen). 5.1 Introduction. 5.2 Antenna Arrays. 5.3 Adaptive Array Systems. 5.4 Beamforming. 5.5 Summary. References. 6 Antenna Diversity Techniques (Junsheng Liu, Wasim Q. Malik, David J. Edwards and Mohammad Ghavami). 6.1 Introduction. 6.2 A Review of Fading. 6.3 Receive Diversity. 6.4 Transmit Diversity. 6.5 MIMO Diversity Systems. References. Part II Antennas for UWB Communications. Introduction to Part II (Ernest E. Okon). 7 Theory of UWB Antenna Elements (Xiaodong Chen). 7.1 Introduction. 7.2 Mechanism of UWB Monopole Antennas. 7.3 Planar UWB Monopole Antennas. 7.4 Planar UWB Slot Antennas. 7.5 Time-Domain Characteristics of Monopoles 7.6 Summary. Acknowledgements. References. 8 Antenna Elements for Impulse Radio (Zhi Ning Chen). 8.1 Introduction. 8.2 UWB Antenna Classification and Design Considerations. 8.3 Omnidirectional and Directional Designs. 8.4 Summary. References. 9 Planar Dipole-like Antennas for Consumer Products (Peter Massey). 9.1 Introduction. 9.2 Computer Modelling and Measurement Techniques. 9.3 Bicone Antennas and the Lossy Transmission Line Model. 9.4 Planar Dipoles. 9.5 Practical Antenna. 9.6 Summary. Acknowledgements. References. 10 UWB Antenna Elements for Consumer Electronic Applications (Dirk Manteuffel). 10.1 Introduction. 10.2 Numerical Modelling and Extraction of the UWB Characterisation. 10.3 Antenna Design and Integration. 10.4 Propagation Modelling. 10.5 System Analysis. 10.6 Conclusions. References. 11 Ultra-wideband Arrays (Ernest E. Okon). 11.1 Introduction. 11.2 Linear Arrays. 11.3 Null and Maximum Directions for Uniform Arrays. 11.4 Phased Arrays. 11.5 Elements for UWB Array Design. 11.6 Modelling Considerations. 11.7 Feed Configurations. 11.8 Design Considerations. 11.9 Summary. References. 12 UWB Beamforming (Mohammad Ghavami and Kaveh Heidary). 12.1 Introduction. 12.2 Basic Concept. 12.3 A Simple Delay-line Transmitter Wideband Array. 12.4 UWB Mono-pulse Arrays. 12.5 Summary. References. Part III Propagation Measurements and Modelling for UWB Communications. Introduction to Part III (Mischa Dohler and Ben Allen). 13 Analysis of UWB Signal Attenuation Through Typical Building Materials (Domenico Porcino). 13.1 Introduction. 13.2 A Brief Overview of Channel Characteristics. 13.3 The Materials Under Test. 13.4 Experimental Campaign. 13.5 Conclusions. References. 14 Large- and Medium-scale Propagation Modelling (Mischa Dohler, Junsheng Liu, R. Michael Buehrer, Swaroop Venkatesh and Ben Allen). 14.1 Introduction. 14.2 Deterministic Models. 14.3 Statistical-Empirical Models. 14.4 Standardised Reference Models. 14.5 Conclusions. References. 15 Small-scale Ultra-wideband Propagation Modelling (Swaroop Venkatesh, R. Michael Buehrer, Junsheng Liu and Mischa Dohler). 15.1 Introduction. 15.2 Small-scale Channel Modelling. 15.3 Spatial Modelling. 15.4 IEEE 802.15.3a Standard Model. 15.5 IEEE 802.15.4a Standard Model. 15.6 Summary. References. 16 Antenna Design and Propagation Measurements and Modelling for UWBWireless BAN (Yang Hao, Akram Alomainy and Yan Zhao). 16.1 Introduction. 16.2 Propagation Channel Measurements and Characteristics. 16.3 WBAN Channel Modelling. 16.4 UWB System-Level Modelling of Potential Body-Centric Networks. 16.5 Summary. References. 17 Ultra-wideband Spatial Channel Characteristics (Wasim Q. Malik, Junsheng Liu, Ben Allen and David J. Edwards). 17.1 Introduction. 17.2 Preliminaries. 17.3 UWB Spatial Channel Representation. 17.4 Characterisation Techniques. 17.5 Increase in the Communication Rate. 17.6 Signal Quality Improvement. 17.7 Performance Parameters. 17.8 Summary. References. Part IV UWB Radar, Imaging and Ranging. Introduction to Part IV (Anthony K. Brown). 18 Localisation in NLOS Scenarios with UWB Antenna Arrays (Thomas Kaiser, Christiane Senger, Amr Eltaher and Bamrung Tau Sieskul). 18.1 Introduction. 18.2 Underlying Mathematical Framework. 18.3 Properties of UWB Beamforming. 18.4 Beamloc Approach. 18.5 Algorithmic Framework. 18.6 Time-delay Estimation. 18.7 Simulation Results. 18.8 Conclusions. References. 19 Antennas for Ground-penetrating Radar (Ian Craddock). 19.1 Introduction. 19.2 GPR Example Applications. 19.3 Analysis and GPR Design. 19.4 Antenna Elements. 19.5 Antenna Measurements, Analysis and Simulation. 19.6 Conclusions. Acknowledgements. References. 20 Wideband Antennas for Biomedical Imaging (Ian Craddock). 20.1 Introduction. 20.2 Detection and Imaging. 20.3 Waveform Choice and Antenna Design Criteria. 20.4 Antenna Elements. 20.5 Measurements, Analysis and Simulation. 20.6 Conclusions. Acknowledgements. References. 21 UWB Antennas for Radar and Related Applications (Anthony K. Brown). 21.1 Introduction. 21.2 Medium- and Long-Range Radar. 21.3 UWB Reflector Antennas. 21.4 UWB Feed Designs. 21.5 Feeds with Low Dispersion. 21.6 Summary. References. Index.

Active Reconfigurable Intelligent Surface-Aided Wireless Communications

Abstract: Reconfigurable Intelligent Surface (RIS) is a promising solution to reconfigure the wireless environment in a controllable way. To compensate for the double-fading attenuation in the RIS-aided link, a large number of passive reflecting elements (REs) are conventionally deployed at the RIS, resulting in large surface size and considerable circuit power consumption. In this paper, we propose a new type of RIS, called active RIS, where each RE is assisted by active loads (negative resistance), that reflect and amplify the incident signal instead of only reflecting it with the adjustable phase shift as in the case of a passive RIS. Therefore, for a given power budget at the RIS, a strengthened RIS-aided link can be achieved by increasing the number of active REs as well as amplifying the incident signal. We consider the use of an active RIS to a single input multiple output (SIMO) system. However, it would unintentionally amplify the RIS-correlated noise, and thus the proposed system has to balance the conflict between the received signal power maximization and the RIS-correlated noise minimization at the receiver. To achieve this goal, it has to optimize the reflecting coefficient matrix at the RIS and the receive beamforming at the receiver. An alternating optimization algorithm is proposed to solve the problem. Specifically, the receive beamforming is obtained with a closed-form solution based on linear minimum-mean-square-error (MMSE) criterion, while the reflecting coefficient matrix is obtained by solving a series of sequential convex approximation (SCA) problems. Simulation results show that the proposed active RIS-aided system could achieve better performance over the conventional passive RIS-aided system with the same power budget.

Simultaneously Transmitting And Reflecting (STAR) RIS Aided Wireless Communications

Abstract: The novel concept of simultaneously transmitting and reflecting (STAR) reconfigurable intelligent surfaces (RISs) is investigated, where the incident wireless signal is divided into transmitted and reflected signals passing into both sides of the space surrounding the surface, thus facilitating a full-space manipulation of signal propagation. Based on the introduced basic signal model of ‘STAR’, three practical operating protocols for STAR-RISs are proposed, namely energy splitting (ES), mode switching (MS), and time switching (TS). Moreover, a STAR-RIS aided downlink communication system is considered for both unicast and multicast transmission, where a multi-antenna base station (BS) sends information to two users, i.e., one on each side of the STAR-RIS. A power consumption minimization problem for the joint optimization of the active beamforming at the BS and the passive transmission and reflection beamforming at the STAR-RIS is formulated for each of the proposed operating protocols, subject to communication rate constraints of the users. For ES, the resulting highly-coupled non-convex optimization problem is solved by an iterative algorithm, which exploits the penalty method and successive convex approximation. Then, the proposed penalty-based iterative algorithm is extended to solve the mixed-integer non-convex optimization problem for MS. For TS, the optimization problem is decomposed into two subproblems, which can be consecutively solved using state-of-the-art algorithms and convex optimization techniques. Finally, our numerical results reveal that: 1) the TS and ES operating protocols are generally preferable for unicast and multicast transmission, respectively; and 2) the required power consumption for both scenarios is significantly reduced by employing the proposed STAR-RIS instead of conventional reflecting/transmiting-only RISs.

Multi-Hop RIS-Empowered Terahertz Communications: A DRL-Based Hybrid Beamforming Design

Abstract: Wireless communication in the TeraHertz band (0.1–10 THz) is envisioned as one of the key enabling technologies for the future sixth generation (6G) wireless communication systems scaled up beyond massive multiple input multiple output (Massive-MIMO) technology. However, very high propagation attenuations and molecular absorptions of THz frequencies often limit the signal transmission distance and coverage range. Benefited from the recent breakthrough on the reconfigurable intelligent surfaces (RIS) for realizing smart radio propagation environment, we propose a novel hybrid beamforming scheme for the multi-hop RIS-assisted communication networks to improve the coverage range at THz-band frequencies. Particularly, multiple passive and controllable RISs are deployed to assist the transmissions between the base station (BS) and multiple single-antenna users. We investigate the joint design of digital beamforming matrix at the BS and analog beamforming matrices at the RISs, by leveraging the recent advances in deep reinforcement learning (DRL) to combat the propagation loss. To improve the convergence of the proposed DRL-based algorithm, two algorithms are then designed to initialize the digital beamforming and the analog beamforming matrices utilizing the alternating optimization technique. Simulation results show that our proposed scheme is able to improve 50% more coverage range of THz communications compared with the benchmarks. Furthermore, it is also shown that our proposed DRL-based method is a state-of-the-art method to solve the NP-hard beamforming problem, especially when the signals at RIS-assisted THz communication networks experience multiple hops.

Deep Reinforcement Learning-Based Intelligent Reflecting Surface for Secure Wireless Communications

Abstract: In this paper, we study an intelligent reflecting surface (IRS)-aided wireless secure communication system, where an IRS is deployed to adjust its reflecting elements to secure the communication of multiple legitimate users in the presence of multiple eavesdroppers. Aiming to improve the system secrecy rate, a design problem for jointly optimizing the base station (BS)’s beamforming and the IRS’s reflecting beamforming is formulated considering different quality of service (QoS) requirements and time-varying channel conditions. As the system is highly dynamic and complex, and it is challenging to address the non-convex optimization problem, a novel deep reinforcement learning (DRL)-based secure beamforming approach is firstly proposed to achieve the optimal beamforming policy against eavesdroppers in dynamic environments. Furthermore, post-decision state (PDS) and prioritized experience replay (PER) schemes are utilized to enhance the learning efficiency and secrecy performance. Specifically, a modified PDS scheme is presented to trace the channel dynamic and adjust the beamforming policy against channel uncertainty accordingly. Simulation results demonstrate that the proposed deep PDS-PER learning based secure beamforming approach can significantly improve the system secrecy rate and QoS satisfaction probability in IRS-aided secure communication systems.

Aerial Intelligent Reflecting Surface: Joint Placement and Passive Beamforming Design With 3D Beam Flattening

Abstract: Intelligent reflecting surface (IRS) is a promising technology to reconfigure wireless channels, which brings a new degree of freedom for the design of future wireless networks. This article proposes a new three-dimensional (3D) wireless system architecture enabled by aerial IRS (AIRS). Compared to the conventional terrestrial IRS, AIRS enjoys more deployment flexibility as well as wider-view signal reflection, thanks to its high altitude and thus more likelihood of establishing line-of-sight (LoS) links with ground source/destination nodes. We aim to maximize the worst-case signal-to-noise ratio (SNR) over all locations in a target area by jointly optimizing the transmit beamforming for the source node, as well as the placement and 3D passive beamforming for the AIRS. The formulated problem is non-convex and difficult to solve. To gain useful insights, we first consider the special case of maximizing the SNR at a given target location, for which the optimal solution is obtained in closed-form. The result shows that the optimal horizontal AIRS placement only depends on the ratio between the source-destination distance and the AIRS altitude. Then for the general case of AIRS-enabled area coverage, we propose an efficient solution by decoupling the AIRS passive beamforming design to maximize the worst-case array gain , from its placement optimization by balancing the resulting angular span and the cascaded channel path loss. Our proposed solution is based on a novel 3D beam broadening and flattening technique, where the passive array of the AIRS is divided into sub-arrays of appropriate size, and their phase shifts are designed to form a flattened beam pattern with adjustable beamwidth catering to the size of the coverage area. Both uniform linear array (ULA)-based and uniform planar array (UPA)-based AIRSs are considered in our design, which enable two-dimensional (2D) and 3D passive beamforming, respectively. Numerical results show that the proposed designs achieve significant performance gains over the benchmark schemes.

Sum Rate Maximization for IRS-Assisted Uplink NOMA

Abstract: An intelligent reflecting surface (IRS) consists of a large number of low-cost reflecting elements, which can steer the incident signal collaboratively by passive beamforming. This way, IRS reconfigures the wireless environment to boost the system performance. In this letter, we consider an IRS-assisted uplink non-orthogonal multiple access (NOMA) system. The objective is to maximize the sum rate of all users under individual power constraint. The considered problem requires a joint power control at the users and beamforming design at the IRS, and is non-convex. To handle it, semidefinite relaxation is employed, which provides a near-optimal solution. Presented numerical results show that the proposed NOMA-based scheme achieves a larger sum rate than orthogonal multiple access (OMA)-based one. Moreover, the impact of the number of reflecting elements on the sum rate is revealed.

Channel Estimation for RIS-Aided mmWave MIMO Systems via Atomic Norm Minimization

Abstract: A reconfigurable intelligent surface (RIS) can shape the radio propagation environment by virtue of changing the impinging electromagnetic waves towards any desired directions, thus, breaking the general Snell’s reflection law. However, the optimal control of the RIS requires perfect channel state information (CSI) of the individual channels that link the base station (BS) and the mobile station (MS) to each other via the RIS. Thereby super-resolution channel (parameter) estimation needs to be efficiently conducted at the BS or MS with CSI feedback to the RIS controller. In this paper, we adopt a two-stage channel estimation scheme for RIS-aided millimeter wave (mmWave) MIMO systems without a direct BS-MS channel, using atomic norm minimization to sequentially estimate the channel parameters, i.e., angular parameters, angle differences, and the products of propagation path gains. We evaluate the mean square error of the parameter estimates, the RIS gains, the average effective spectrum efficiency bound, and average squared distance between the designed beamforming and combining vectors and the optimal ones. The results demonstrate that the proposed scheme achieves super-resolution estimation compared to the existing benchmark schemes, thus offering promising performance in the subsequent data transmission phase.

Energy Efficiency and Spectral Efficiency Tradeoff in RIS-Aided Multiuser MIMO Uplink Transmission

Abstract: The emergence of reconfigurable intelligent surfaces (RISs) enables us to establish programmable radio wave propagation that caters for wireless communications, via employing low-cost passive reflecting units. This work studies the non-trivial tradeoff between energy efficiency (EE) and spectral efficiency (SE) in multiuser multiple-input multiple-output (MIMO) uplink communications aided by a RIS equipped with discrete phase shifters. For reducing the required signaling overhead and energy consumption, our transmission strategy design is based on the partial channel state information (CSI), including the statistical CSI between the RIS and user terminals (UTs) and the instantaneous CSI between the RIS and the base station. To investigate the EE-SE tradeoff, we develop a framework for the joint optimization of UTs’ transmit precoding and RIS reflective beamforming to maximize a performance metric called resource efficiency (RE). For the design of UT's precoding, it is simplified into that of UTs’ transmit powers with the aid of the closed-form solutions of UTs’ optimal transmit directions. To avoid the high complexity in computing the nested integrals involved in the expectations, we derive an asymptotic deterministic objective expression. For the design of the RIS phases, an iterative mean-square error minimization approach is proposed via capitalizing on the homotopy, accelerated projected gradient, and majorization-minimization methods. Numerical results illustrate the effectiveness and rapid convergence rate of our proposed optimization framework.

URLLC Facilitated by Mobile UAV Relay and RIS: A Joint Design of Passive Beamforming, Blocklength, and UAV Positioning

Abstract: Upcoming fifth-generation (5G) networks need to support novel ultrareliable and low-latency (URLLC) traffic that utilizes short packets. This requires a paradigm shift as traditional communication systems are designed to transmit only long data packets based on Shannon’s capacity formula, which poses a challenge for system designers. To address this challenge, this article relies on an unmanned aerial vehicle (UAV) and a reconfigurable intelligent surface (RIS) to deliver short URLLC instruction packets between ground Internet-of-Things (IoT) devices. In this context, we perform passive beamforming of RIS antenna elements as well as nonlinear and nonconvex optimization to minimize the total decoding error rate and find the UAV’s optimal position and blocklength. In this article, a novel, polytope-based method from the class of direct search methods (DSMs) named Nelder–Mead simplex (NMS) is used to solve the optimization problem based on its computational efficiency; in terms of lesser number of required iterations to evaluate objective function. The proposed approach yields better convergence performance than the traditional gradient-descent optimization algorithm and a lower computation time and equivalent performance for the blocklength variable as the exhaustive search. Moreover, the proposed approach allows ultrahigh reliability, which can be attained by increasing the number of antenna elements in RIS as well as increasing the allocated blocklengths. Simulations demonstrate the RIS’s performance gain and conclusively show that the UAV’s position is crucial for achieving ultrahigh reliability in short packet transmission.

Robust Transmission Design for Intelligent Reflecting Surface-Aided Secure Communication Systems With Imperfect Cascaded CSI

Abstract: In this paper, we investigate the design of robust and secure transmission in intelligent reflecting surface (IRS) aided wireless communication systems. In particular, a multi-antenna access point (AP) communicates with a single-antenna legitimate receiver in the presence of multiple single-antenna eavesdroppers, where the artificial noise (AN) is transmitted to enhance the security performance. Besides, we assume that the cascaded AP-IRS-user channels are imperfect due to the channel estimation error. To minimize the transmit power, the beamforming vector at the transmitter, the AN covariance matrix, and the IRS phase shifts are jointly optimized subject to the outage rate probability constraints under the statistical cascaded channel state information (CSI) error model. To handle the resulting non-convex optimization problem, we first approximate the outage rate probability constraints by using the Bernstein-type inequality. Then, we develop a suboptimal algorithm based on alternating optimization, the penalty-based and semidefinite relaxation methods. Simulation results reveal that the proposed scheme significantly reduces the transmit power compared to other benchmark schemes.

Max-Min Fairness in IRS-Aided Multi-Cell MISO Systems With Joint Transmit and Reflective Beamforming

Abstract: This paper investigates an intelligent reflecting surface (IRS)-aided multi-cell multiple-input single-output (MISO) network with a set of multi-antenna base stations (BSs) each communicating with multiple single-antenna users, in which an IRS is dedicatedly deployed for assisting the wireless transmission and suppressing the inter-cell interference. Under this setup, we jointly optimize the coordinated transmit beamforming vectors at the BSs and the reflective beamforming vector (with both reflecting phases and amplitudes) at the IRS, for the purpose of maximizing the minimum weighted signal-to-interference-plus-noise ratio (SINR) at the users, subject to the individual maximum transmit power constraints at the BSs and the reflection constraints at the IRS. To solve the non-convex min-weighted-SINR maximization problem, we first present an exact -alternating-optimization approach to optimize the transmit and reflective beamforming vectors in an alternating manner, in which the transmit and reflective beamforming optimization subproblems are solved exactly in each iteration by using the techniques of second-order-cone program (SOCP) and semi-definite relaxation (SDR), respectively. However, the exact-alternating-optimization approach has high computational complexity, and may lead to compromised performance due to the uncertainty of randomization in SDR. To avoid these drawbacks, we further propose an inexact -alternating-optimization approach, in which the transmit and reflective beamforming optimization subproblems are solved inexactly in each iteration based on the principle of successive convex approximation (SCA). In addition, to further reduce the computational complexity, we propose a low-complexity inexact-alternating-optimization design, in which the reflective beamforming optimization subproblem is solved more inexactly . Via numerical results, it is shown that the proposed three designs achieve significantly increased min-weighted-SINR values, as compared with benchmark schemes without the IRS or with random reflective beamforming. It is also shown that the inexact-alternating-optimization design outperforms the exact-alternating-optimization one in terms of both the achieved min-weighted-SINR value and the computational complexity, while the low-complexity inexact-alternating-optimization design has much lower computational complexity with slightly compromised performance. Furthermore, we show that our proposed design can be applied to the scenario with unit-amplitude reflection constraints, with a negligible performance loss.

Millimeter Wave and Sub-Terahertz Spatial Statistical Channel Model for an Indoor Office Building

Abstract: Millimeter-wave (mmWave) and sub-Terahertz (THz) frequencies are expected to play a vital role in 6G wireless systems and beyond due to the vast available bandwidth of many tens of GHz. This paper presents an indoor 3-D spatial statistical channel model for mmWave and sub-THz frequencies based on extensive radio propagation measurements at 28 and 140 GHz conducted in an indoor office environment from 2014 to 2020. Omnidirectional and directional path loss models and channel statistics such as the number of time clusters, cluster delays, and cluster powers were derived from over 15,000 measured power delay profiles. The resulting channel statistics show that the number of time clusters follows a Poisson distribution and the number of subpaths within each cluster follows a composite exponential distribution for both LOS and NLOS environments at 28 and 140 GHz. This paper proposes a unified indoor statistical channel model for mmWave and sub-Terahertz frequencies following the mathematical framework of the previous outdoor NYUSIM channel models. A corresponding indoor channel simulator is developed, which can recreate 3-D omnidirectional, directional, and multiple input multiple output (MIMO) channels for arbitrary mmWave and sub-THz carrier frequency up to 150 GHz, signal bandwidth, and antenna beamwidth. The presented statistical channel model and simulator will guide future air-interface, beamforming, and transceiver designs for 6G and beyond.

Double-IRS Assisted Multi-User MIMO: Cooperative Passive Beamforming Design

Abstract: 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 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.

Intelligent Reflecting Surface Enhanced Wireless Networks: Two-Timescale Beamforming Optimization

Abstract: Intelligent reflecting surface (IRS) has drawn a lot of attention recently as a promising new solution to achieve high spectral and energy efficiency for future wireless networks. By utilizing massive low-cost passive reflecting elements, the wireless propagation environment becomes controllable and thus can be made favorable for improving the communication performance. Prior works on IRS mainly rely on the instantaneous channel state information (I-CSI), which, however, is practically difficult to obtain for IRS-associated links due to its passive operation and large number of reflecting elements. To overcome this difficulty, we propose in this paper a new two-timescale (TTS) transmission protocol to maximize the achievable average sum-rate for an IRS-aided multiuser system under the general correlated Rician channel model. Specifically, the passive IRS phase shifts are first optimized based on the statistical CSI (S-CSI) of all links, which varies much slowly as compared to their I-CSI; while the transmit beamforming/precoding vectors at the access point (AP) are then designed to cater to the I-CSI of the users’ effective fading channels with the optimized IRS phase shifts, thus significantly reducing the channel training overhead and passive beamforming design complexity over the existing schemes based on the I-CSI of all channels. Besides, for ease of practical implementation, we consider discrete phase shifts at each reflecting element of the IRS. For the single-user case, an efficient penalty dual decomposition (PDD)-based algorithm is proposed, where the IRS phase shifts are updated in parallel to reduce the computational time. For the multiuser case, we propose a general TTS stochastic successive convex approximation (SSCA) algorithm by constructing a quadratic surrogate of the objective function, which cannot be explicitly expressed in closed-form. Simulation results are presented to validate the effectiveness of our proposed algorithms and evaluate the impact of S-CSI and channel correlation on the system performance.

Efficient Channel Estimation for Double-IRS Aided Multi-User MIMO System

Abstract: To achieve the more significant passive beamforming gain in the double-intelligent reflecting surface (IRS) aided system over the conventional single-IRS counterpart, channel state information (CSI) is indispensable in practice but also more challenging to acquire, due to the presence of not only the single- but also double-reflection links that are intricately coupled and also entail more channel coefficients for estimation. In this paper, we propose a new and efficient channel estimation scheme for the double-IRS aided multi-user multiple-input multiple-output (MIMO) communication system to resolve the cascaded CSI of both its single- and double-reflection links. First, for the single-user case, the single- and double-reflection channels are efficiently estimated at the multi-antenna base station (BS) with both the IRSs turned ON (for maximal signal reflection), by exploiting the fact that their cascaded channel coefficients are scaled versions of their superimposed lower-dimensional CSI. Then, the proposed channel estimation scheme is extended to the multi-user case, where given an arbitrary user’s cascaded channel (estimated as in the single-user case), the other users’ cascaded channels can also be expressed as lower-dimensional scaled versions of it and thus efficiently estimated at the BS. Simulation results verify the effectiveness of the proposed channel estimation scheme and joint training reflection design for double IRSs, as compared to various benchmark schemes.

Joint Waveform Design and Passive Beamforming for RIS-Assisted Dual-Functional Radar-Communication System

Abstract: Dual-functional radar-communication (DFRC) technique has been viewed as a promising component in the emerging platforms. When synthesizing the desired transmit beampattern, the degrees of freedom of waveform design is limited, which introduces high multi-user interference (MUI), thus degrading the communication performance. Inspired by the applications of the Reconfigurable Intelligent Surface (RIS) in mitigating MUI, in this paper, we investigate joint waveform design and passive beamforming in RIS-assisted DFRC system. We first study the minimization of MUI under the strict beampattern constraint by jointly optimizing DFRC waveform and RIS phase shift matrix. To deal with the coupled variables, we propose an alternating algorithm based on manifold optimization. Subsequently, the trade-off between radar and communication performances is investigated. Simulation results show that for both cases of strict beampattern and trade-off design, with the help of RIS, the system throughput can be significantly improved. Moreover, compared with the scenario where no RIS is employed, the obtained beampattern matches with the target transmit beampattern better.

Reconfigurable Intelligent Surface-Assisted Non-Orthogonal Multiple Access

Abstract: Reconfigurable intelligent surface (RIS) is a revolutionary technology to achieve spectrum-, energy-, and cost-efficient wireless networks. This paper considers an RIS-assisted downlink non-orthogonal-multiple-access (NOMA) system. To optimize the rate performance and ensure user fairness, we maximize the minimum decoding signal-to-interference-plus-noise-ratio (equivalently the rate) of all users, by jointly optimizing the (active) transmit beamforming at the base station (BS) and the phase shifts (i.e., passive beamforming) at the RIS. A combined-channel-strength based user-ordering scheme for NOMA decoding is first proposed to decouple the user-ordering design and the joint beamforming design. Efficient algorithms are further proposed to solve the non-convex problem, by leveraging the block coordinated descent and semidefinite relaxation (SDR) techniques. For the single-antenna BS setup, the optimal power allocation at the BS and the asymptotically optimal phase shifts at the RIS are obtained in closed forms. For the multiple-antenna BS setup, it is shown that the rank of the SDR solution of the transmit beamforming design is upper bounded by two. Also, the proposed algorithms are analyzed in terms of convergence and complexity. Simulation results show that the RIS-assisted NOMA system can enhance the rate performance significantly, compared to traditional NOMA without RIS and traditional orthogonal multiple access with/without RIS.

Beamforming Through Reconfigurable Intelligent Surfaces in Single-User MIMO Systems: SNR Distribution and Scaling Laws in the Presence of Channel Fading and Phase Noise

Abstract: We consider a fading channel in which a multi-antenna transmitter communicates with a multi-antenna receiver through a reconfigurable intelligent surface (RIS) that is made of ${N}$ reconfigurable passive scatterers impaired by phase noise. The beamforming vector at the transmitter, the combining vector at the receiver, and the phase shifts of the ${N}$ scatterers are optimized in order to maximize the signal-to-noise-ratio (SNR) at the receiver. By assuming Rayleigh fading (or line-of-sight propagation) on the transmitter-RIS link and Rayleigh fading on the RIS-receiver link, we prove that the SNR is a random variable that is equivalent in distribution to the product of three (or two) independent random variables whose distributions are approximated by two (or one) gamma random variables and the sum of two scaled non-central chi-square random variables. The proposed analytical framework allows us to quantify the robustness of RIS-aided transmission to fading channels. For example, we prove that the amount of fading experienced on the transmitter-RIS-receiver channel linearly decreases with ${N}~\gg ~1.$ This proves that RISs of large size can be effectively employed to make fading less severe and wireless channels more reliable.

Intelligent Omni-Surfaces: Ubiquitous Wireless Transmission by Reflective-Refractive Metasurfaces

Abstract: Intelligent reflecting surfaces (IRSs), which are capable of adjusting the propagation conditions by controlling the phase shifts of the reflected waves that impinge on the surface, have been widely analyzed for enhancing the performance of wireless systems. However, the reflective properties of widely studied IRSs restrict the service coverage to only one side of the surface. In this paper, to extend the wireless coverage of communication systems, we introduce the concept of intelligent omni-surface (IOS)-assisted communication. More precisely, an IOS is an important instance of a reconfigurable intelligent surface (RIS) that can provide service coverage to the mobile users (MUs) in a reflective and a refractive manner. We consider a downlink IOS-assisted communication system, where a multi-antenna small base station (SBS) and an IOS jointly perform beamforming, for improving the received power of multiple MUs on both sides of the IOS, through different reflective/refractive channels. To maximize the sum-rate, we formulate a joint IOS phase shift design and SBS beamforming optimization problem, and propose an iterative algorithm to efficiently solve the resulting non-convex program. Both theoretical analysis and simulation results show that an IOS significantly extends the service coverage of the SBS when compared to an IRS.

Reconfigurable Intelligent Surfaces With Reflection Pattern Modulation: Beamforming Design and Performance Analysis

Abstract: Recent research on reconfigurable intelligent surfaces (RISs) suggests that RISs can perform passive beamforming and information transfer (PBIT) simultaneously via smart reflections. In this paper, we propose an RIS-enhanced multiple-input single-output system with reflection pattern modulation (RPM) to achieve PBIT, where the joint active and passive beamforming is carefully designed by taking into account the communication outage probability. We formulate an optimization problem to maximize the average received signal power by jointly optimizing the active beamforming at the access point (AP) and passive beamforming at the RIS under the assumption that the RIS’s state information is statistically known by the AP, and propose a high-quality suboptimal solution based on the alternating optimization technique. Moreover, a closed-form expression for the asymptotic outage probability of the proposed scheme in Rician fading is derived. The achievable rate of the proposed scheme is also investigated under the assumption that the transmitted symbols are drawn from a finite constellation. Simulation results validate the effectiveness of the proposed scheme and reveal the effect of various system parameters on the achievable rate. It is shown that the proposed scheme outperforms, in terms of achievable rate, the conventional RIS-assisted system without information transfer.

Beyond Cell-Free MIMO: Energy Efficient Reconfigurable Intelligent Surface Aided Cell-Free MIMO Communications

Abstract: Cell-free systems can effectively eliminate the inter-cell interference by enabling multiple base stations (BSs) to cooperatively serve users without cell boundaries at the expense of high costs of hardware and power sources due to the large-scale deployment of BSs. To tackle this issue, the low-cost reconfigurable intelligent surface (RIS) can serve as a promising technique to improve the energy efficiency of cell-free systems. In this article, we consider an RIS aided cell-free MIMO system where multiple RISs are deployed around BSs and users to create favorable propagation conditions via reconfigurable reflections in a low-cost way, thereby enhancing cell-free MIMO communications. To maximize the energy efficiency, a hybrid beamforming (HBF) scheme consisting of the digital beamforming at BSs and the RIS-based analog beamforming is proposed. The energy efficiency maximization problem is formulated and an iterative algorithm is designed to solve this problem. The impact of the transmit power, the number of RIS, and the RIS size on energy efficiency are investigated. Both theoretical analysis and simulation results reveal that the optimal energy efficiency depends on the numbers of RISs and the RIS size. Numerical evaluations also show that the proposed system can achieve a higher energy efficiency than conventional ones.

Robust and Secure Communications in Intelligent Reflecting Surface Assisted NOMA Networks

Abstract: This letter investigates secure transmission in an intelligent reflecting surface (IRS) assisted non-orthogonal multiple access (NOMA) network. Consider a practical eavesdropping scenario with imperfect channel state information of the eavesdropper, we propose a robust beamforming scheme using artificial noise to guarantee secure NOMA transmission with the IRS. A joint transmit beamforming and IRS phase shift optimization problem is formulated to minimize the transmit power. Since the problem is non-convex and challenging to resolve, we develop an effective alternating optimization (AO) algorithm to obtain stationary point solutions. Simulation results validate the security advantage of the robust beamforming scheme and the effectiveness of the AO algorithm.

Terahertz Multi-User Massive MIMO With Intelligent Reflecting Surface: Beam Training and Hybrid Beamforming

Abstract: Terahertz (THz) communications open a new frontier for the wireless network thanks to their dramatically wider available bandwidth compared to the current micro-wave and forthcoming millimeter-wave communications. However, due to the short length of THz waves, they also suffer from severe path attenuation and poor diffraction. To compensate for the THz-induced propagation loss, this paper proposes to combine two promising techniques, viz., massive multiple input multiple output (MIMO) and intelligent reflecting surface (IRS), in THz multi-user communications, considering their significant beamforming and aperture gains. Nonetheless, channel estimation and low-cost beamforming turn out to be two main obstacles to realizing this combination, due to the passivity of IRS for sending/receiving pilot signals and the large-scale use of expensive RF chains in massive MIMO. In view of these limitations, this paper first develops a cooperative beam training scheme to facilitate the channel estimation with IRS. In particular, we design two different hierarchical codebooks for the proposed training procedure, which are able to balance between the robustness against noise and searching complexity. Based on the training results, we further propose two cost-efficient hybrid beamforming (HB) designs for both single-user and multi-user scenarios, respectively. Simulation results demonstrate that the proposed joint beam training and HB scheme is able to achieve close performance to the optimal fully digital beamforming which is implemented even under perfect channel state information (CSI).

Joint Beamforming Design in Multi-Cluster MISO NOMA Reconfigurable Intelligent Surface-Aided Downlink Communication Networks

Abstract: Considering reconfigurable intelligent surfaces (RISs), we study a multi-cluster multiple-input-single-output (MISO) non-orthogonal multiple access (NOMA) downlink communication network. In the network, RISs assist the communication from the base station (BS) to all users by passive beamforming. Our goal is to minimize the total transmit power by jointly optimizing the active beamforming matrices at the BS and the reflection coefficient vector at the RISs. Because of the constraints on the RIS reflection amplitudes and phase shifts, the formulated quadratically constrained quadratic problem is highly non-convex. For the aforementioned problem, the conventional semidefinite programming (SDP) based algorithm has prohibitively high computational complexity and deteriorating performance. Here, we propose an effective second-order cone programming (SOCP)-alternating direction method of multipliers (ADMM) based algorithm to obtain the locally optimal solution. To reduce the computational complexity, we also propose a low-complexity zero-forcing based suboptimal algorithm. It is shown through simulation results that our proposed SOCP-ADMM based algorithm achieves significant performance gain over the conventional SDP based algorithm. Furthermore, when the target transmission rates of central and cell-edge users are 0.5 bps/Hz, our proposed NOMA RIS-aided system with 32 RIS elements has about 2.5 dB performance gain over the conventional massive multiple-input-multiple-output system with 64 transmit antennas.

Intelligent Reflecting Surface Assisted Anti-Jamming Communications: A Fast Reinforcement Learning Approach

Abstract: Malicious jamming launched by smart jammers can attack legitimate transmissions, which has been regarded as one of the critical security challenges in wireless communications. With this focus, this paper considers the use of an intelligent reflecting surface (IRS) to enhance anti-jamming communication performance and mitigate jamming interference by adjusting the surface reflecting elements at the IRS. Aiming to enhance the communication performance against a smart jammer, an optimization problem for jointly optimizing power allocation at the base station (BS) and reflecting beamforming at the IRS is formulated while considering quality of service (QoS) requirements of legitimate users. As the jamming model and jamming behavior are dynamic and unknown, a fuzzy win or learn fast-policy hill-climbing (WoLF–CPHC) learning approach is proposed to jointly optimize the anti-jamming power allocation and reflecting beamforming strategy, where WoLF–CPHC is capable of quickly achieving the optimal policy without the knowledge of the jamming model, and fuzzy state aggregation can represent the uncertain environment states as aggregate states. Simulation results demonstrate that the proposed anti-jamming learning-based approach can efficiently improve both the IRS-assisted system rate and transmission protection level compared with existing solutions.

Beamforming Optimization for IRS-Aided Communications With Transceiver Hardware Impairments

Abstract: In this paper, we focus on intelligent reflecting surface (IRS) assisted multi-antenna communications with transceiver hardware impairments encountered in practice. In particular, we aim to maximize the received signal-to-noise ratio (SNR) taking into account the impact of hardware impairments, where the source transmit beamforming and the IRS reflect beamforming are jointly designed under the proposed optimization framework. To circumvent the non-convexity of the formulated design problem, we first derive a closed-form optimal solution to the source transmit beamforming. Then, for the optimization of IRS reflect beamforming, we obtain an upper bound to the optimal objective value via solving a single convex problem. A low-complexity minorization-maximization (MM) algorithm was developed to approach the upper bound. Simulation results demonstrate that the proposed beamforming design is more robust to the hardware impairments than that of the conventional SNR maximized scheme. Moreover, compared to the scenario without deploying an IRS, the performance gain brought by incorporating the hardware impairments is more evident for the IRS-aided communications.

Secure Beamforming for Cognitive Satellite Terrestrial Networks With Unknown Eavesdroppers

Abstract: This article proposes a beamforming (BF) scheme for a cognitive satellite terrestrial network, where the base station (BS) and a cooperative terminal (CT) are exploited as green interference resources to enhance the system security performance in the presence of unknown eavesdroppers. Different from the related works, we assume that only imperfect channel information of the mobile user (MU) and earth station (ES) is available. Specifically, we formulate an optimization problem with the objective to degrade the possible wiretap channels within the private signal beampattern region, while imposing constraints on the signal-to-interference-plus-noise ratio (SINR) at the MU, the interference level of the ES and the total transmit power budget of the BS and CT. To solve this mathematically intractable problem, we propose a joint artificial noise generation and cooperative jamming BF scheme to suppress the interception. Finally, the effectiveness and superiority of the proposed BF scheme are confirmed through computer simulations.

IRS-Assisted Wireless Powered NOMA: Do We Really Need Different Phase Shifts in DL and UL?

Abstract: Intelligent reflecting surface (IRS) is a promising technology to improve the performance of wireless powered communication networks (WPCNs) due to its capability to reconfigure signal propagation environments via smart reflection. In particular, the high passive beamforming gain promised by IRS can significantly enhance the efficiency of both downlink wireless power transfer (DL WPT) and uplink wireless information transmission (UL WIT) in WPCNs. Although adopting different IRS phase shifts for DL WPT and UL WIT, i.e., dynamic IRS beamforming , is in principle possible but incurs additional signaling overhead and computational complexity, it is an open problem whether it is actually beneficial. To answer this question, we consider an IRS-assisted WPCN where multiple devices employ a hybrid access point (HAP) to first harvest energy and then transmit information using non-orthogonal multiple access (NOMA). Specifically, we aim to maximize the sum throughput of all devices by jointly optimizing the IRS phase shifts and the resource allocation. To this end, we first prove that dynamic IRS beamforming is not needed for the considered system, which helps reduce the number of IRS phase shifts to be optimized. Then, we propose both joint and alternating optimization based algorithms to solve the resulting problem. Simulation results demonstrate the effectiveness of our proposed designs over benchmark schemes and also provide useful insights into the importance of IRS for realizing spectrum and energy efficient WPCNs.