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Satellite communications (SatCom) have been viewed as a promising technique to achieve ubiquitous global coverage in next‐generation wireless systems. This article investigates the secure energy efficient downlink transmission for SatCom where an intelligent transmissive surface‐aided transmitter is deployed at the satellite to perform energy efficient beamforming and an intelligent reflecting surface as well as a cooperative jammer are deployed on the ground to enhance the secure performance. The aim is to maximize the secure energy efficiency by jointly designing ITS beamforming, IRS phase shift, jammer precoding vector, and transmit power allocation. To develop a low‐complexity solution,first, an approximated concave lower bound of the non‐concave objective function is derived by utilizing Dinkelbach's method and a novel successive convex approximation technique. Then the reformulated problem is decoupled using alternating optimization algorithm and the subproblems are solved by adopting Riemannian manifold optimization, element‐wise block coordinate descent, Lagrange dual method and Karush–Kuhn–Tucker conditions. At last, simulation results demonstrate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

Summary: Multiple intelligent reflecting surfaces (IRS) in a wireless system are considered to enhance performance, efficiency, and flexibility in wireless networks. In this paper, we analyze outage probability (OP) for multiple IRS panels‐assisted wireless systems over Nakagami‐ m fading channels. We focus on selecting the best IRS panel to maintain the quality of service and enhance the user experience. We derive two closed‐form OP expressions using the central limit theorem and Laguerre series expansion. Additionally, we develop a novel asymptotic OP expression and obtain a novel diversity order. The diversity order of the considered system model depends on the minimum fading parameter (m) between the transmitter‐IRS panel and IRS panel‐receiver links and the number of IRS panels. We thoroughly investigate the impact of system parameters and validate our analytical results with simulations. Our findings emphasize that diversity order depends on the minimum fading parameter (m) between the transmitter‐IRS panel and IRS panel‐receiver links, the number of IRS elements in each panel, and the number of IRS panels. [ABSTRACT FROM AUTHOR]

This paper investigates an unmanned aerial vehicle (UAV)-assisted multi-object offloading scheme for blockchain-enabled Vehicle-to-Everything (V2X) systems. Due to the presence of an eavesdropper (Eve), the system's communication links may be insecure. This paper proposes deploying an intelligent reflecting surface (IRS) on the UAV to enhance the communication performance of mobile vehicles, improve system flexibility, and alleviate eavesdropping on communication links. The links for uploading task data from vehicles to a base station (BS) are protected by IRS-assisted physical layer security (PLS). Upon receiving task data, the computing resources provided by the edge computing servers (MEC) are allocated to vehicles for task execution. Existing blockchain-based computation offloading schemes typically focus on improving network performance, such as minimizing energy consumption or latency, while neglecting the Gas fees for computation offloading and the costs required for MEC computation, leading to an imbalance between service fees and resource allocation. This paper uses a utility-oriented computation offloading scheme to balance costs and resources. This paper proposes alternating phase optimization and power optimization to optimize the energy consumption, latency, and communication secrecy rate, thereby maximizing the weighted total utility of the system. Simulation results demonstrate a notable enhancement in the weighted total system utility and resource utilization, thereby corroborating the viability of our approach for practical applications. [ABSTRACT FROM AUTHOR]

Intelligent reflecting surfaces (IRS) recently gained prominence due to their ability to adapt and tweak their configuration in real-time to create an intelligent wireless environment. Hence, it can elevate wireless connectivity, signal strength, data rate, coverage, and mitigate signal blockage or interference in future wireless networks. A comprehensive review of IRSs has been conveyed in this paper, emphasizing beamforming optimization strategies in the realm of energy harvesting with IRS assistance. The discussion encompasses an overview of IRS hardware design, practical IRS prototypes for hardware design, a summary of related works, and an equivalent RLC circuit model. Additionally, an extensive comparative analysis of IRS architecture, shape, size, advantages, drawbacks, and applications is presented, considering existing research. Further, the paper examines the most pivotal cost and economic aspects of IRS to optimize energy harvesting and coverage enhancement. The paper explores beamforming techniques and examines various optimization methods aimed at maximizing the potential of IRS for energy harvesting. Furthermore, the paper delves into the wide range of potential applications that IRS-assisted wireless communication networks can offer. Despite the significant promises of IRS technology, it faces substantial research challenges in optimization. This paper addresses and highlights these challenges and limitations associated with the IRS, paving the way for future research directions. [ABSTRACT FROM AUTHOR]

With the rapid development of Internet of Vehicles (IoV) technology, the data security transmission between vehicles has become particularly important. As a novel technology that can assist wireless communication, intelligent reflecting surface (IRS) can not only change the wireless signal propagation environment, but also has the advantages of easy deployment, low cost and low consumption. In this paper, an IRS is used to assist the physical layer security communication of vehicle to vehicle (V2V) in a multiple input single output (MISO) IoV system. The physical layer security rate maximization problem of V2V link is formulated while satisfying the total power constraint and the IRS phase-shift mode constraint. An alternating optimization algorithm based on the generalized Rayleigh entropy and semidefinite relaxation (SDR) is proposed. Simulation results show that IRS-assisted V2V communication can effectively enhance the physical layer security transmission rate. [ABSTRACT FROM AUTHOR]

5G positioning technology has become deeply integrated into daily life. However, in wireless signal propagation environments, there may exist non-line-of-sight (NLOS) conditions, which lead to signal blockage and subsequently hinder the provision of positioning services. To address this issue, this paper proposes an intelligent reflecting surface (IRS) NLOS time difference of arrival–angle of arrival (TDOA-AOA) localization (INTAL) algorithm. First, the algorithm constructs a system model for 5G IRS localization, effectively overcoming the challenges of positioning in NLOS paths. Then, by applying the multiple signal classification algorithm to estimate the time delay and angle, and using the Chan algorithm to obtain the user's estimated coordinates, an optimization problem is formulated to minimize the distance between the estimated and actual coordinates. The tent–snake optimization algorithm is employed to solve this optimization problem, thereby reducing localization errors. Finally, simulations demonstrate that the INTAL algorithm outperforms the snake optimization (SO) algorithm and the gray wolf optimization (GWO) algorithm under the same conditions, reducing the localization error by 56% and 60% on average, respectively. Additionally, when the signal-to-noise ratio is 30 dB, the localization error of the INTAL algorithm is only 0.2968 m, while the errors for the SO and GWO algorithms are 0.6733 m and 0.7398 m, respectively. This further proves the significant improvement of the algorithm in terms of localization accuracy. [ABSTRACT FROM AUTHOR]

Summary: The future wireless communication networks (beyond 5G) are intended to provide seamless connectivity, higher data rates, and lower latency. The intelligent reflecting surface (IRS) promises extended network coverage. The non‐orthogonal multiple access (NOMA) technique provides higher spectral efficiency and supports a larger number of users. In general, the cell‐edge users far from the base station are affected by severe fading, which may result in an outage. To overcome this issue, we propose an IRS‐aided device‐to‐device (D2D)‐enabled two cells coordinated NOMA system in which a common cell‐edge user acts as D2D receiver. The cell‐edge user receives the signals from near users, IRSs, and both base stations to achieve better diversity. We analyze the outage probability of cell‐edge user, while all the fading channels are assumed Nakagami‐ m and obtain a closed‐form expression at higher signal‐to‐noise ratios. We develop an algorithm to find the ergodic capacity of the cell‐edge user. We validate the mathematical expressions with simulation results and see a substantial improvement in outage performance over the existing systems. [ABSTRACT FROM AUTHOR]

Millimeter-wave (mmWave) communication is able to provide high-speed data rates up to Gbps. However, mmWave communication is susceptible to fading and blockage by obstacles in indoor and urban areas owing to high path loss and directivity. To tackle these issues, the intelligent reflecting surface (IRS) is regarded as an effective technique that provides reflected signals to enhance system performance. However, designing the joint active and passive beamforming is challenging in the IRS-assisted mmWave communication systems owing to the time-varying channels. In this study, we propose a novel adaptive perturbation-based opportunistic beamforming design for IRS-assisted systems (IRS-APOBF) for mmWave channels. The proposed scheme employs adaptive perturbation to select the beamforming and phase-shift vectors that improve the system performance by enhancing the signal-to-noise ratio (SNR) of the received signal. Moreover, the proposed IRS-APOBF scheme can adapt to the time-varying channel conditions of IRS-assisted mmWave systems with the only requirement of SNR feedback from mobile stations, making it suitable for practical scenarios. The simulation outcomes reveal that the system throughput achieved by the IRS-APOBF scheme is significantly higher than that obtained via a conventional IRS-assisted opportunistic beamforming scheme, despite both schemes requiring limited feedback information. [ABSTRACT FROM AUTHOR]

Intelligent reflecting surface (IRS) is a promising enabler for achieving communication quality of service (QoS) and enhancing sensing QoS in Integrated Sensing and Communication (ISAC) systems. It has been regarded as one of the most attractive solutions for facilitating vehicle applications in internet of vehicles (IoV) by utilizing ISAC technologies. In this paper, the trajectory of target vehicle goes through no obstacle blocking stage and obstacle blocking stage successively in ISAC systems. And the performance trad-off is pursued in the sensing QoS and the communication QoS of the target vehicle. The achievable rate and posterior Cramer-Rao lower bounds (PCRLBs) are defined to reflect communication QoS and sensing QoS, respectively. In this process, the trade-off strategy on QoS for communication and IRS assisted sensing is explored in IoV. Hence, an optimization problem is designed to ensure communication capability of the target while ensuring its sensing ability. The joint semidefinite relaxation (SDR) and alternating optimization (AO) method is proposed to obtain the optimal solution on resource allocation (RA) and IRS phase shift. Simulation results verify the effectiveness of the proposed method in terms of performance trade-off between communication QoS and sensing QoS.

Abstract Satellite communications (SatCom) have been viewed as a promising technique to achieve ubiquitous global coverage in next‐generation wireless systems. This article investigates the secure energy efficient downlink transmission for SatCom where an intelligent transmissive surface‐aided transmitter is deployed at the satellite to perform energy efficient beamforming and an intelligent reflecting surface as well as a cooperative jammer are deployed on the ground to enhance the secure performance. The aim is to maximize the secure energy efficiency by jointly designing ITS beamforming, IRS phase shift, jammer precoding vector, and transmit power allocation. To develop a low‐complexity solution,first, an approximated concave lower bound of the non‐concave objective function is derived by utilizing Dinkelbach's method and a novel successive convex approximation technique. Then the reformulated problem is decoupled using alternating optimization algorithm and the subproblems are solved by adopting Riemannian manifold optimization, element‐wise block coordinate descent, Lagrange dual method and Karush–Kuhn–Tucker conditions. At last, simulation results demonstrate the effectiveness of the proposed scheme.

Non-Orthogonal Multiple Access (NOMA) has already proven to be an effective multiple access scheme for 5th Generation (5G) wireless networks. It provides improved performance in terms of system throughput, spectral efficiency, fairness, and energy efficiency (EE). However, in conventional NOMA networks, performance degradation still exists because of the stochastic behavior of wireless channels. To combat this challenge, the concept of Intelligent Reflecting Surface (IRS) has risen to prominence as a low-cost intelligent solution for Beyond 5G (B5G) networks. In this paper, a modeling primer based on the integration of these two cutting-edge technologies, i.e., IRS and NOMA, for B5G wireless networks is presented. An in-depth comparative analysis of IRS-assisted Power Domain (PD)-NOMA networks is provided through 3-fold investigations. First, a primer is presented on the system architecture of IRS-enabled multiple-configuration PD-NOMA systems, and parallels are drawn with conventional network configurations, i.e., conventional NOMA, Orthogonal Multiple Access (OMA), and IRS-assisted OMA networks. Followed by this, a comparative analysis of these network configurations is showcased in terms of significant performance metrics, namely, individual users' achievable rate, sum rate, ergodic rate, EE, and outage probability. Moreover, for multi-antenna IRS-enabled NOMA networks, we exploit the active Beamforming (BF) technique by employing a greedy algorithm using a state-of-the-art branch-reduce-and-bound (BRB) method. The optimality of the BRB algorithm is presented by comparing it with benchmark BF techniques, i.e., minimum-mean-square-error, zero-forcing-BF, and maximum-ratio-transmission. Furthermore, we present an outlook on future envisioned NOMA networks, aided by IRSs, i.e., with a variety of potential applications for 6G wireless networks. This work presents a generic performance assessment toolkit for wireless networks, focusing on IRS-assisted NOMA networks. This comparative analysis provides a solid foundation for the development of future IRS-enabled, energy-efficient wireless communication systems.

Copyright of Telecommunication Engineering is the property of Telecommunication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Intelligent reflecting surface (IRS) improves wireless communication efficiency and coverage probability. Existing studies focus on IRS deployment but overlook optimal fading channels. This research aims to identify and analyze the most effective channel fading estimation for the double IRS system model. The coverage probability using two-IRS is derived under different fading channels like Rayleigh and Rician to find the optimal solution in a Single-Input-Single-Output (SISO) system. Additionally, a closed-form expression for the coverage probability using statistical channel state information is derived while assuming no direct path between the transmitter and receiver. The analytical results are validated through simulations. It offers valuable insights into the modeling and analysis of double IRS-assisted wireless communication systems. [ABSTRACT FROM AUTHOR]

This paper proposes a three-step joint rate optimization method for intelligent reflecting surface (IRS)-assisted coal mine wireless communication systems. Different from terrestrial IRS-assisted communication scenarios, in coal mines, IRSs can be installed flexibly on the tops of rectangular tunnels to address the issues of signals being blocked and interfered with by mining equipment. Therefore, it is necessary to optimize the IRS deployment position, the transmit power and IRS phase shifts to achieve the maximum effective achievable rate at user stations equipped with the proposed system. However, due to the complex channel models of coal mines, the optimization problem of IRS deployment position is non-convex. To solve this problem, two auxiliary variables along with logarithmic operations and Taylor approximation are introduced. On this basis, a three-step joint rate optimization involving the transmit power, IRS phase shifts and IRS deployment position is proposed to maximize the effective achievable rates at the user station. The simulation results show that compared with other rate optimization schemes, the effective achievable rates at the user station using the proposed joint rate optimization scheme can be improved by approximately 12.32 % to 54.17 % for different parameter configurations. It is also pointed out that the deployment position of the IRS can converge to the same optimal position independent of the initial deployment position. Moreover, we investigate the effects of the roughness of the tunnel walls in a coal mine on the effective achievable rates at the user station, and the simulation results indicate that the proposed three-step joint rate optimization scheme performs better in the coal mine scenario regardless of the roughness. [ABSTRACT FROM AUTHOR]

By adjusting the propagation environment using reconfigurable reflecting elements, intelligent reflecting surfaces (IRSs) have become potential techniques used to improve the efficiency of wireless communication networks. In IRS-assisted communication systems, accurate channel estimation is crucial for optimizing signal transmission and achieving high spectral efficiency. As mobile data traffic continues to surge and the demand for high-capacity and low-latency wireless connectivity grows, IRSs are becoming pivotal technologies in the development of next-generation communication networks. IRSs offer the potential to revolutionize wireless propagation environments, improving network capacity and coverage, particularly in high-frequency wave scenarios where traditional signals encounter obstacles. Amidst this evolving landscape, machine learning (ML) emerges as a powerful tool to harness the full potential of IRS-assisted communication systems, particularly given the escalating computational complexity associated with deploying and operating IRSs in dynamic environments. This paper presents an overview of preliminary results for IRS-assisted communication using recurrent neural networks (RNNs). We first implement single- and double-layer LSTM, BiLSTM, and GRU techniques for an IRS-based communication system. In the next phase, we explore a hybrid approach, combining different RNN techniques, including LSTM-BiLSTM, LSTM-GRU, and BiLSTM-GRU, as well as their reverse configurations. These RNN algorithms were evaluated with respect to bit error rate (BER) and symbol error rate (SER) for IRS-enhanced communication. According to the experimental results, the BiLSTM double-layer model and the BiLSTM-GRU combination demonstrated the highest BER and SER accuracy compared to other approaches. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Chongqing University of Posts & Telecommunications (Natural Science Edition) is the property of Chongqing University of Posts & Telecommunications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In recent years, the intelligent reflecting surface (IRS) has attracted increasing attention for its capability to intelligently reconfigure the wireless propagation channel. However, most existing works ignore the dynamic power consumption of IRS related to the phase shift configuration. This relationship gets even more intractable for a multi-bit IRS because of its nonlinearity and implicit form. In this paper, we investigate the beamforming optimization for multi-bit IRS-aided systems with the practical phase shift-dependent power consumption (PS-DPC) model, aiming at minimizing the power consumption of the system. To solve the implicit and nonlinear relationship, we introduce a selection matrix to explicitly represent the power consumption and the phase shift matrix of the IRS, respectively. Then, we propose a generalized Benders decomposition-based beamforming optimization algorithm in the single-user scenario. Furthermore, in the multi-user scenario, we design a coordinate descent-based algorithm and a genetic algorithm for the beamforming optimization. The simulation results show that the proposed algorithms significantly decrease the power consumption of the multi-bit IRS-aided systems. [ABSTRACT FROM AUTHOR]

We consider a multi-device wireless-powered communication network, where an intelligent reflecting surface (IRS) is deployed to assist the wireless energy transfer (WET) from the power station (PS) to the information transmitter (IT) and the wireless information transfer (WIT) from the IT to the devices. The IRS, IT, and PS belong to different service providers, where the PS receives revenue from the IT for WET and pays fees to its energy source and the IRS, and the IT receives revenue from the devices for WIT and pays fees to the PS and the IRS. We model the interactions between the IT and the PS through a Stackelberg game and aim to achieve a win-win situation between them in terms of utility. Specifically, we solve a follower problem that maximizes the utility of the PS by jointly optimizing the IRS reflection coefficients and the transmit power of the PS, and a leader problem that maximizes the utility of the IT by jointly optimizing the energy price, the transmit power allocation of the IT, and the time allocation as well as the IRS reflection coefficients in the WET and WIT phases. The results show that, by deploying IRS, it is possible to effectively enhance the signal strength and thus increase the revenue of the system, and by using Time Division Multiple Access (TDMA), the performance of the system is greatly improved by coordinating the timing of the reception of the signal by each device. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Jilin University (Science Edition) / Jilin Daxue Xuebao (Lixue Ban) is the property of Zhongguo Xue shu qi Kan (Guang Pan Ban) Dian zi Za zhi She and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The intelligent reflecting surface (IRS) is an emerging technology that can conquer visible light communication's (VLC) dependency on the line-of-sight (LoS) channel by offering additional non-light-of-sight (NLoS) communication links. In this paper, a newly proposed electro-tunable intelligent reflecting metasurface is deployed in dimmable single-input single-output (SISO) VLC systems. We aim to improve the bit error rate (BER) performance by jointly optimizing the transmit constellation and the reflectance of the IRS units. To this end, the optimization problem can be solved in two steps. The minimum distance of the received constellation is firstly maximized by a convex problem, which guarantees the minimum BER. Then, the transmit constellation and the synchronously-tunable reflectance of the IRS units that correspond to the optimal received constellation are determined with an iterative alternate optimization algorithm. Finally, the simulation results show the BER performance improvement and the dimming relaxation benefit of the tunable IRS-aided SISO VLC systems. [ABSTRACT FROM AUTHOR]

To meet the needs of society, the next generation of communication systems will have to learn to juggle multiple responsibilities effectively. This is leading to exponential growth in both circuit complexity and error rates. It is possible to solve these issues by using the intelligent reflecting surface (IRS)-Assisted space shift keying (SSK) modulation technique. IRS is a cutting-edge technology that shows promise for future networks due to its low mistake rates and low-energy consumption. Similarly, SSK modulation is favored due to its preference for simpler hardware. Therefore, integrating IRS with SSK is preferable for minimizing both error rates and circuit complexity. In this article, a new framework is developed to characterize the average bit error rate (ABER) with the help of the moment generating function (MGF) over Nakagami-m fading channels. The ABER is derived by factoring the direct path and IRS reflected path at the receiver and also comparing the performance analysis over the Rayleigh fading channel. The analytical results are validated through Monte-Carlo simulations. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Signal Processing is the property of Journal of Signal Processing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

For 6G communications, the Ultra Massive Multiple Input Multiple Output (UM-MIMO) systems with Intelligent Reflecting Surface (IRS) assistance are capable since they can efficiently get beyond the limitations of restricted blockage and coverage. However, in the far field, a robust THz channel sparsity is unfavorable to spatial multiplexing, whereas excessive UM-MIMO and IRS dimensions extend the near field region. To address these issues, a hybrid beamforming IRS assisted UM-MIMO THz system with Deep Siamese Capsule Network is designed with the cascaded channel. The near and far field codebook-based beamforming is developed to model the proposed communication channel. The channel estimation is done based on the deep siamese capsule adaptive beluga whale neural network. The simulation results of the bit error rate, Normalized Mean Square Error (NMSE), spectral efficiency, sum rate, data rate, normalized channel gain, beamforming gain, and array gain loss shows that the proposed system achieves reliable performances compared with existing techniques. The suggested approach also demonstrates the outstanding adaptability to various network configurations and good scalability. The method provides a better channel estimation accuracy and less complexity which shows an NMSE of − 11.2 dB at an SNR of 10 dB. [ABSTRACT FROM AUTHOR]

In large-scale massive MIMO systems with intelligent reflecting surfaces (IRS), dynamic channel estimation (CE) is essential for optimizing the system performance and ensuring reliable communication. Traditional channel estimation techniques are not suitable for IRS-assisted systems due to the unique characteristics of Intelligent Reflecting Surfaces channels. To address the channel estimation problem in such dynamic environments, this paper introduces two novel channel estimation methods: Khatri-Rao Factorization (KRF) and Bilinear Alternating Least Squares (BALS). The first method uses KRF to efficiently solve rank-1 matrix approximation problems with a closed-form solution. The second method employs an iterative alternating estimation scheme. By disentangling these key channel matrices’ estimates, both methods provide more accurate and robust channel estimation, essential for optimizing communication system performance in challenging environments. The proposed CE-KRF-BALS-MIMO method is evaluated under performance metrics like Bit error rate (BER), Signal Noise Ratio (SNR), Normalized Mean Square Error (NMSE) Spectral Efficiency (SE), and Computational Complexity.

Intelligent reflecting surface (IRS)-assisted device-to-device (D2D) communications in heterogeneous cloud radio access network (H-CRAN) were investigated as research background. Resource allocation and Riemannian conjugate gradient (RCG) beamforming optimization were studied, with the objective of system sum rate maximization. System sum rate was formulated as the optimization objective, which was subject to several constraint conditions such as sub-channel reuse coefficient, transmit power threshold, as well as the modulus of the IRS reflection coefficient. To solve the formulated mixed-integer non-linear programming problem, a channel-strength-based deferred acceptance algorithm was proposed to obtain channel reuse indicators. The problem was then decomposed into two subproblems. For transmit power optimization subproblem, successive convex approximation (SCA) was used to solve it. For IRS beamforming optimization subproblem, the beamforming vector constraint was transformed into a complex circular manifold and Riemannian conjugate gradient (RCG) algorithm was implemented to solve it. Simulation results show that, when IRS reflecting elements is 50 and base station maximum transmit power is 46 dBm, compared with the existing channel allocation scheme and random channel allocation scheme, the proposed scheme enhances sum rate performance 5.2 bit/(s·Hz) and 14.6 bit/(s·Hz) respectively. Compared with the communication scenario without IRS, sum rate performance significantly promotes nearly 31.2 bit/(s·Hz) with the deployment of IRS.

To address the issues of frequency switching differences between communication and sensing systems in traditional integrated sensing and communication (ISAC) scenarios, as well as the susceptibility of communication to obstruction by obstacles, the integration of full-duplex (FD) technology and intelligent reflecting surface (IRS) into the ISAC system was studied. The design of FD beamforming assisted by IRS in the ISAC scenario was investigated. An optimization problem for maximizing the user rates of uplink and downlink beamforming was formulated, considering constraints on IRS phase shift, base station receiving beamforming, the maximum transmission power of the base station, the maximum transmission power of uplink users, and the radar sensing threshold. The original non-convex problem was solved by being transformed into a convex optimization problem through the use of alternating optimization, continuous convex approximation, semi-definite relaxation, variable substitution, and semi-definite programming. Simulation results show that the proposed scheme resulted in an 89.02% enhancement under the communication performance indicators considered compared to the corresponding half-duplex scheme and a 70.15% improvement over the random IRS scheme.

Abstract A compact low-profile multi-band millimeter-wave (mm-wave) reflectarray metasurface design is presented for coverage enhancement in 5G and beyond cellular communication. The proposed single-layer metasurface exhibits a stable reflection response under oblique incidence angles of up to 60 $$^\circ$$ ∘ at 24 and 38 GHz, and transmission response at 30 GHz, effectively covering the desired 5G mm-wave frequency bands. The proposed reflectarray metasurface is polarization insensitive and performs equally well under TE and TM polarized incident waves due to the symmetric pattern. In addition, the low profile of the proposed metasurface makes it appropriate for conformal applications. In comparison to the state-of-the-art, the proposed reflectarray metasurface unit cell design is not only compact (3.3 $$\times$$ × 3.3 mm $$^2$$ 2 ) but also offers two reflections and one transmission band based on a single-layer structure. It is easy to reconfigure the proposed metasurface unit cell for any other frequency band by adjusting a few design parameters. To validate the concept of coverage enhancement, a 32 $$\times$$ × x32 unit-cell prototype of the proposed reflectarray metasurface is fabricated and measured under different scenarios. The experimental results demonstrate that a promising signal enhancement of 20–25 dB is obtained over the entire 5G mm-wave n258, n259, and n260 frequency bands. The proposed reflectarray metasurface has a high potential for application in mm-wave 5G networks to improve coverage in dead zones or to overcome obstacles that prevent direct communication linkages.

For the intelligent reflecting surface (IRS)-assisted multiple input single output (MISO) simultaneous wireless information and power transfer (SWIPT) system, the beam forming vector at the base station and the reflected beam forming vector of the IRS were jointly optimized, by considering the maximum transmit power of the base station, the unit modulus constraint of the IRS reflection phase shift matrix, and the minimum energy constraint of the energy receiver. The object was to maximize the spectrum efficiency. To solve the non-convex optimization problem, a deep deterministic policy gradient (DDPG) algorithm based on deep reinforcement learning was proposed. Simulation results show that the average reward of the DDPG algorithm is related to the learning rate. Under the condition of selecting the appropriate learning rate, the DDPG algorithm can obtain an average mutual information similar to that of the traditional optimization algorithm, but the running time is significantly lower than that of the traditional non-convex optimization algorithm. Even if the number of antennas and the number of reflective units are increased, the DDPG algorithm can still converge in a short period of time. This indicates that the DDPG algorithm can effectively improve the computational efficiency and is suitable for communication services with high real-time requirements.

Abstract The metasurface is a promising technology that can help next-generation wireless communication systems not only improve the signal-to-noise ratio (SNR), but also increase security and mitigate interference. Further, introducing dual polarization (DP) in a metasurface can enhance its capabilities with polarization diversity, polarization multiplexing, and polarization-switched modulation. In this paper, we study a DP-metasurface-assisted single-user wireless communication system and propose a novel scheme that can improve the spectral efficiency (SE) and bit-error-rate (BER) performance compared to those of conventional schemes by exploiting the orthogonal property of dual-polarized waves. We employ the DP metasurface to increase the SNR at the receiver and create a specific phase difference between the polarized signals by controlling the transmit precoder and the phases of the metasurface reflecting elements representing some modulated bits. At the receiver, we use the recovered phase information to realign the modulated symbols in both polarizations, which are then added coherently. The simulation results demonstrate that the proposed scheme achieves significantly higher SE and BER performance than those of some closely related works.

Enhancing spectral efficiency in non-line-of-sight (NLoS) environments is essential as 5G networks evolve, surpassing 4G systems with high information rates and minimal interference. Instead of relying on traditional Orthogonal Multiple Access (OMA) systems to tackle issues caused by NLoS, advanced wireless networks adopt innovative models like Non-Orthogonal Multiple Access (NOMA), cooperative relaying, Multiple Input Multiple Output (MIMO), and intelligent reflective surfaces (IRSs). Therefore, this study comprehensively analyzes these techniques for their potential to improve communication reliability and spectral efficiency in NLoS scenarios. Specifically, it encompasses an analysis of cooperative relaying strategies for their potential to improve reliability and spectral efficiency in NLoS environments through user cooperation. It also examines various MIMO configurations to address NLoS challenges via spatial diversity. Additionally, it investigates IRS settings, which can alter signal paths to enhance coverage and reduce interference and analyze the role of Unmanned Aerial Vehicles (UAVs) in establishing flexible communication infrastructure in difficult environments. This paper also surveys effective energy harvesting (EH) strategies that can be integrated with NOMA for efficient and reliable energy-communication networks. Our findings show that incorporating these technologies with NOMA not only enhances connectivity and spectral efficiency but also promotes a stable and environmentally sustainable data communication system. [ABSTRACT FROM AUTHOR]

A compact low-profile multi-band millimeter-wave (mm-wave) reflectarray metasurface design is presented for coverage enhancement in 5G and beyond cellular communication. The proposed single-layer metasurface exhibits a stable reflection response under oblique incidence angles of up to 60 ∘ at 24 and 38 GHz, and transmission response at 30 GHz, effectively covering the desired 5G mm-wave frequency bands. The proposed reflectarray metasurface is polarization insensitive and performs equally well under TE and TM polarized incident waves due to the symmetric pattern. In addition, the low profile of the proposed metasurface makes it appropriate for conformal applications. In comparison to the state-of-the-art, the proposed reflectarray metasurface unit cell design is not only compact (3.3 × 3.3 mm 2 ) but also offers two reflections and one transmission band based on a single-layer structure. It is easy to reconfigure the proposed metasurface unit cell for any other frequency band by adjusting a few design parameters. To validate the concept of coverage enhancement, a 32 × x32 unit-cell prototype of the proposed reflectarray metasurface is fabricated and measured under different scenarios. The experimental results demonstrate that a promising signal enhancement of 20–25 dB is obtained over the entire 5G mm-wave n258, n259, and n260 frequency bands. The proposed reflectarray metasurface has a high potential for application in mm-wave 5G networks to improve coverage in dead zones or to overcome obstacles that prevent direct communication linkages. [ABSTRACT FROM AUTHOR]

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Copyright of Telecommunications Science is the property of Beijing Xintong Media Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Telecommunications Science is the property of Beijing Xintong Media Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Chongqing University of Technology (Natural Science) is the property of Chongqing University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Summary: The intelligent reflecting surface (IRS) has recently become the most promising technology to achieve maximum beam‐forming gain with a simultaneous wireless information and power transfer (SWIPT) system. Many existing studies perform a single IRS deployment or utilize space division multiple access (SDMA) and non‐orthogonal multiple access (NOMA) schemes. However, the existing schemes face high time complexity and block signal transmission for larger indoor communications. Hence, this article introduces a dual IRS‐aided multiuser SWIPT system by implementing rate‐splitting multiple access (RSMA) systems. To enhance the minimum achievable rate and ensure the minimum harvesting energy (HE), this study proposes a joint successive convex approximation with an integrated optimization algorithm (SCA‐IOA). The proposed algorithm jointly optimizes the reflecting beam forming and power splitting (PS) coefficient of all the users effectively. The simulation results demonstrate the effectiveness of the proposed techniques and produce an outstanding performance for deploying dual IRS and implementing RSMA compared to traditional SDMA and NOMA systems. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Signal Processing is the property of Journal of Signal Processing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The metasurface is a promising technology that can help next-generation wireless communication systems not only improve the signal-to-noise ratio (SNR), but also increase security and mitigate interference. Further, introducing dual polarization (DP) in a metasurface can enhance its capabilities with polarization diversity, polarization multiplexing, and polarization-switched modulation. In this paper, we study a DP-metasurface-assisted single-user wireless communication system and propose a novel scheme that can improve the spectral efficiency (SE) and bit-error-rate (BER) performance compared to those of conventional schemes by exploiting the orthogonal property of dual-polarized waves. We employ the DP metasurface to increase the SNR at the receiver and create a specific phase difference between the polarized signals by controlling the transmit precoder and the phases of the metasurface reflecting elements representing some modulated bits. At the receiver, we use the recovered phase information to realign the modulated symbols in both polarizations, which are then added coherently. The simulation results demonstrate that the proposed scheme achieves significantly higher SE and BER performance than those of some closely related works. [ABSTRACT FROM AUTHOR]

In this paper, a downlink energy efficiency maximization problem is investigated in an intelligent reflective surface (IRS)-assisted visible light communication system. In order to extend wireless communication coverage of the onshore base station, an IRS mounted on a unmanned aerial vehicle (UAV) is introduced to assist an onshore lighthouse with simultaneously providing remote ship users wireless communication services and illumination. Aiming to maximizing the energy efficiency of the proposed system, a resource allocation problem is formulated as the ratio of the achievable system sum rate to the total power consumption under the constraints of the user's data requirement and transmit power budget. Due to the non-convexity of the proposed problem, the Dinkelbach method and mean-square error (MSE) method are adopted to turn the non-convex origin problem into two equivalent problems, namely transmit beamforming and reflected phase shifting. The Lagrangian method and semidefinite relaxation technique are used to obtain the closed-form solutions of these two subproblems. Accordingly, an alternative optimization-based resource allocation scheme is proposed to obtain the optimal system energy efficiency. The simulation results show that the proposed scheme performs better in terms of energy efficiency over benchmark schemes. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Guangdong University of Technology is the property of Journal of Guangdong University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To improve the robustness and reduce the energy consumption of non-orthogonal multiple access (NOMA) networks, based on hardware impairments (HWI) of transceiver and non-perfect channel state information (CSI), an intelligent reflecting surface (IRS) assisted transmission power minimization algorithm for NOMA networks was proposed.The joint optimization problem of active beam assignment at the base station and passive beam assignment at the IRS was modeled based on HWI and non-perfect CSI.The system considered the user quality of service (QoS) constraint, the serial interference cancellation constraint and the reflection phase shift constraint of the IRS.To solve this nonconvex optimization problem, the QoS constraints were firstly transformed using linear approximation and S-Procedure methods.Then the optimization problem was decomposed into two subproblems.The active beam assignment subproblem was solved using the successive convex approximation (SCA) method.The passive beam assignment subproblem was solved using the penalized convex-concave process algorithm.Finally, the final solution was obtained by iterating the subproblems alternately using alternating optimization.The simulation results show that the proposed algorithm reduces 17.05% compared to the or thogonal multiple access robust algorithm in terms of transmitted power.In terms of system robustness, the proposed algorithm improves by 20.69% and 31.14% compared to the HWI robust algorithm and the CSI robust algorithm, respectively.