Channel Modeling using Deep Neural Network with RIS-powered Wireless Communication Systems

On performance of multi-RIS assisted multi-user nonorthogonal multiple access system over Nakagami-[formula omitted] fading channels

RIS-assisted D2D communication in the presence of interference: Outage performance analysis and DNN-based prediction

Recently, reconfigurable intelligent surface (RIS) has drawn much attention due to its capability of improving coverage and communication performance. The development of RIS-assisted communication technology relies on deep understanding of RIS channel characteristics. However, most of the existing investigations focus on the impact of RIS, ignoring the existence of local scatterers in the real propagation environment. The ideal propagation condition limits the accuracy and application of the developed channel model. In this paper, we aim to analyze the channel characteristics of RIS-assisted near-filed communication by considering different conditions of local scatterers. Specifically, we propose a three-dimensional (3D) RIS-assisted multiple-input multiple-output (MIMO) channel model based on a three-dimensional cylinder model, which considers line-of-sight, single-bounced at RIS (SBR) and double-bounced (DB) modes where radio waves reflect from RIS and scatterers near receiver. Based on the proposed channel model, we investigate some key statistical properties for SBR and DB propagation, including the time-frequency-space correlation function and Doppler power spectrum. From the simulation results, it is found that RIS element number, RIS horizontal and vertical locations, distribution of surrounding scatterers, and movement of Rx have significant impacts on channel characteristics. Finally, channel capacities of SBR and DB modes are calculated, where the large size and appropriate locations of RIS significantly improve the channel capacity of RIS-assisted communication. These numerical results and observations can be used for design of RIS-assisted near-field communication systems.

In this paper, we exploit the benefits of full-duplex (FD) transmission and reconfigurable intelligent surfaces (RISs) by considering a bidirectional full-duplex wireless communication system with the support of RISs. Specifically, cooperative communications are applied at two FD terminals in a RISs-assisted bidirectional full-duplex (RIS-FD) system. In this context, we successfully derive the mathematical expressions of the outage probability (OP) and the ergodic capacity (EC) of the RIS-FD system with a direct link between two terminals and multiple reflecting paths created by RISs over the Rayleigh fading channel. Numerical results show that the performance of the considered RIS-FD system depends significantly on the total number of reflecting elements in the RISs. Particularly, when the total number of reflecting elements is small, the OP and EC saturate at a high signal-to-noise ratio (SNR). However, when the total number of reflecting elements is large enough, OP decreases greatly while EC enhances significantly. In addition, the effect of residual self-interference (SI) caused by FD transmission on OP and EC is remarkable, even the residual SI level is very small. On the other hand, the influence of other system parameters such as the number of RISs (N) and the number of reflecting elements (L) are also investigated to fully consider the performance of the RIS-FD system. An important observation is that when current techniques cannot completely eliminate SI in FD transmission, the use of multiple RISs with larger L can indirectly reduce the impact of SI and significantly improve the performance of the proposed RIS-FD system. Finally, the obtained expressions are validated via Monte-Carlo simulations.

In this article, the physical layer security (PLS) is investigated for reconfigurable intelligent surface (RIS)-aided wireless communication systems, where one RIS is deployed to assist the communications between a pair of transmitter (Alice) and receiver (Bob), under a passive eavesdropper (Eve) attack. For the Eve, different from the bounded channel state information uncertainty model, the distribution of the Eve's location is introduced into the wiretap link. In the proposed system, considering that the Eve can overhear signals transmitted from Alice or reflected by the RIS, two scenarios are studied for RIS-aided secure communication systems: one is that the Eve distributes close to Alice without the RIS orientation, and the other is that the Eve locates close to Bob and in the presence of the RIS. After investigating the probability distribution functions of the Eve's location and the wiretap link, the novel cumulative density functions (CDFs) of the received signal-to-noise ratios (SNRs) at the Eves are, respectively, derived for the two considered scenarios, taking into account the effects of RIS reflection coefficients, pathloss, and Eve's location distribution. The closed-form expressions for the probability of the nonzero secrecy capacity and the ergodic secrecy capacity are obtained, providing insights into the impact of the Eve's location uncertainty and the RIS design on the secrecy performance. Moreover, based on the derived CDFs for received SNRs at Eves, the secrecy outage probabilities are, respectively, analyzed. Specifically, under the constraint of the secrecy outage probability, the closed forms of the minimum required SNRs at Bob and the number of RIS elements are also obtained. Simulation and analytical results corroborate the derived expressions and reveal the tradeoff between the system's energy efficiency and the number of RIS elements.

In this paper, we have studied a model of a relay radio network system using Reconfigurable Intelligent Surface (RIS). Specifically, we used a relay network that uses RIS when there is an extra direct link from the Source (S) to the Destination (D). Next, an approximate closed-form expressions of the Outage Probability (OP) and Ergodic Capacity (EC) are considered. Based on the simulation results of OP and EC, the results show that our proposed system is more optimal than the system using supported RIS without direct link and the system without using RIS. In addition, changing the number of the RIS reflecting elements and the RIS’s location near (S) or (D) has a significant impact on the performance of the system. The analytical expression match the simulation results through the Monte Carlo simulation method. Furthermore, the simulation results of energy efficiency (EE) also show that when the target spectral efficiency (SE), Rth, is high (more than 5.45 b/s/Hz), the system using supported RIS with direct link will help reduce the transmit power and optimize the most energy compared to the other two systems.

Energy efficiency (EE) is one of the most important metrics for the beyond fifth generation (B5G) and the future sixth generation (6G) wireless networks. Reconfigurable intelligent surface (RIS) has been widely focused on EE enhancement for wireless networks because it is power-saving, programmable, and easy to be deployed. However, RIS is generally passive and thus difficult to obtain corresponding full channel state information (CSI), which severely impacts the EE enhancement of RIS-assisted wireless communications. To solve this problem, in this paper we propose the new single-active-antenna combined RIS transmitter structure, which can replace traditional multiple antennas to reduce hardware cost and power consumption. Based on the single-active-antenna combined RIS structure, we develop the Dumb RIS-Assisted Random Beamforming (Darb)-based Joint RIS-Elements and Transmit-power optimizAtion (Jeta) scheme, where dumb RIS randomly changes its phase shift according to isotropic distribution only depending on the CSI feedback from users to RIS-assisted transmitter. Then, we jointly design the number of RIS elements and optimize the transmit power to maximize the EE of RIS-assisted wireless communications. Simulation results show that compared with the traditional multi-antenna system, our developed Darb-based-Jeta scheme can significantly increase the EE without the full CSI.

In future wireless networks, device-to-device (D2D) communications are expected to play an important role to support a plethora of applications. To meet the target quality of service while ensuring high reliability, and high spectral and energy efficiencies, manipulation of the radio waves by reconfigurable intelligent surfaces (RIS) will be critical. In this context, leveraging concepts of polarization, this paper proposes a framework for bidirectional D2D communications, where the data exchange between a central node and devices operating in distinct polarization states, is multiple-input multiple-output in nature and takes place via a dual-polarized RIS, in the presence of hardware impairments and imperfect interference cancellation, as well as impairments caused by the spatial correlation and cross-polarization. Performance evaluation of such a framework is conducted in terms of key metrics, namely, bit error rate, outage probability, channel capacity, and energy efficiency, for which closed-form expressions are obtained considering transmissions over Nakagami fading channels. An asymptotic analysis is also conducted to evaluate the achievable diversity gains, by approximating the Nakagami model with a tractable Gamma model. Further, the impact of imperfect channel estimation on performance is also investigated. Comparative numerical results are provided, and the effects of the main system parameters on performance are analyzed. The proposed framework is shown to provide significant performance improvements as compared to D2D communications via non-polarized RIS.

In this paper, we explore the communication performance of vehicle-to-vehicle (V2V) networks assisted by a reconfigurable intelligent surface (RIS) and a simultaneous transmitting and reflecting intelligent omni-surface (STAR-IOS) under non-orthogonal multiple access (NOMA) and orthogonal multiple access (OMA) schemes. In particular, we consider that the RIS is close to the transmitter vehicle while the STAR-IOS is near the receiver vehicles. In addition, it is assumed that the STAR-IOS exploits the energy-splitting (ES) protocol for communication and the fading channels between the RIS and STAR-IOS follow composite Fisher-Snedecor <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathcal {F}$</tex-math></inline-formula> distribution. Under such assumptions, we first use the central limit theorem (CLT) to derive the PDF and the CDF of equivalent channels at receiver vehicles, and then, we derive the closed-form expression of outage probability (OP) under NOMA/OMA scenarios. Additionally, by exploiting Jensen's inequality, we propose an upper bound of the ergodic capacity (EC) and subsequently develop an analytical expression of the energy efficiency (EE) for both NOMA and OMA cases. Further, our analytical results, which are double-checked with the Monte-Carlo simulation, reveal that applying RIS/STAR-RIS in V2V communications significantly enhances the communication performance of intelligent transportation systems (ITS). Besides, the results indicate that considering the NOMA scheme provides better performance in terms of the OP, EC, and EE as compared with the OMA case for the considered V2V communication system.

Reconfigurable intelligent surface (RIS) can serve as a passive relay to maintain communication between a transceiver in severe scenarios of no direct link between them. In addition, harvesting energy from radio frequency (RF) signals can meliorate significantly energy efficiency. In this research, we propose RIS-aided communication systems with energy harvesting (RISwEH) which combine both RIS and RF energy harvesting to improve energy efficiency as well as communication reliability. To evaluate realistically and quickly the performance of the RISwEH, we propose the explicit formulas of the system throughput and the outage probability under the realistic scenario of Nakagami-m fading and imperfect channel state information (CSI). Moreover, we propose an optimization algorithm relied upon a Golden section search to attain the optimum value of the time splitting factor of energy harvester to obtain the best system performance. Various results corroborate the theoretical derivations, confirm the efficacy of the proposed optimization algorithm, and illustrate the influence of innumerable system settings on the system performance. Particularly, the imperfect CSI deteriorates considerably the system performance. Nonetheless, the performance of the RISwEH can be enhanced by accreting the quantity of the elements of the RIS as well as with the lower fading severity. Furthermore, the time splitting factor also impacts dramatically the outage performance of the RISwEH and its optimal value mitigates significantly the outage probability.

The reconfigurable intelligent surface (RIS)-assisted wireless communication system is studied in this paper, where two full-duplex (FD) users simultaneously communicate with each other. The reception at each user is facilitated through a dedicated RIS. Owing to the geometry and placements of meta-atoms, the analysis incorporates spatial-correlation among the channels related to RIS. Using moment-matching approach, a new analytical framework is presented for spatially-correlated channels considering the optimal phase-shifts from RIS meta-atoms. The effects of residual self-interference (RSI), self-reflections and interference from the RIS of transmitting user are considered in the analysis. The expressions are derived for the outage probability and ergodic capacity for infinite block-length transmission, and for finite block-length transmission, the expressions are obtained for block-error rate (BLER), ergodic capacity and system goodput. To gain further insights, the expression for the asymptotic outage probability is also derived. The finding of this paper confirms the ability of RIS-assisted communication to counter the detrimental effects of self-interference in FD scenario, even in presence of spatial-correlation. The derived expressions are validated using the Monte-Carlo simulations.

A High-Efficiency and Versatile Reconfigurable Intelligent Surface Design Paradigm with Novel Topological Representation

Chapter 3 of the monograph meticulously presents the methodology used for integrating Artificial Intelligence (AI) with Reconfigurable Intelligent Surfaces (RIS) into urban infrastructure, forming a comprehensive framework for implementing and assessing these technologies. This chapter delineates the systematic approach taken from the technical setup and configuration of AI and RIS systems to the sophisticated analytical techniques used to evaluate their effectiveness. The technical implementation details the strategic placement and integration of RIS panels throughout urban environments, particularly in areas plagued by poor connectivity or where high usage demands more robust infrastructure. AI systems are finely tuned to manage these panels, dynamically adjusting to real-time data concerning environmental changes, network traffic, and specific urban events, ensuring optimal performance. This section highlights the complex coordination required with existing city infrastructure and the adaptable, scalable nature of the technology to fit within the evolving urban landscape. Furthermore, the methodology encompasses advanced analytical tools and models to rigorously assess the impact of AI-enhanced RIS on urban infrastructure. Employing software like MATLAB and Python, along with GIS for spatial analysis, the study intricately models how RIS modifies electromagnetic fields to improve network performance across varied urban settings. Additionally, machine learning algorithms are employed to refine RIS behavior continuously, illustrating a practical application of AI in managing city-scale communication networks. The chapter also introduces a case study approach that provides real-world insights into the deployment of these technologies, offering a detailed examination of their application across different urban scenarios. This approach not only illustrates the practical challenges and successes encountered but also reinforces theoretical models with empirical evidence, enhancing the credibility and reliability of the research. Overall, Chapter 3 lays down a solid foundation of the methodologies employed, emphasizing the blend of technical precision and analytical rigor required to advance AI and RIS integration in urban infrastructures. It underscores the potential of these technologies to significantly enhance urban connectivity and adaptability, setting a benchmark for future implementations and studies in the field. &nbsp; 3.1 Implementation Framework The implementation framework for integrating Artificial Intelligence (AI) with Reconfigurable Intelligent Surfaces (RIS) in urban infrastructure projects is a cornerstone of this monograph, setting the foundation for understanding how these technologies are applied in real-world settings. The framework delineates the technical setups and configurations necessary to harness the full potential of AI-enhanced RIS, ensuring that the technology not only fits within the existing urban infrastructure but also optimally performs its intended functions.

With a broad scope of exploration and utilization of marine resources, the field of underwater wireless communication (UWC) is attracting the growing interest of researchers. Due to the highly complex and changing underwater environment, achieving minimal Doppler Effect, extensive communication range, maintaining link reliability, and high channel efficiency is challenging. Underwater information transfer can utilize various communication techniques, including Acoustic, Optical, Radio Frequency (RF), and Magnetic Induction (MI)-based communication. Accurate channel modelling is essential for optimizing UWC’s overall performance. Each underwater communication technique has its strengths and weaknesses. This review article discusses the detailed channel modelling of Acoustic, Optical, MI, and RF communications, comparing them across parameters such as path loss, channel capacity, channel error control protocols, bit error rate (BER), the impact of reconfigurable intelligent surface (RIS), and outage probability are briefly discussed. Additionally, critical unresolved issues related to the channel modelling of UWC techniques are highlighted. This review article will assist researchers in identifying research gaps and conducting further research in the field.

In recent years, reconfigurable intelligent surfaces (RISs) have attracted significant attention from both academia and industry due to their ability to manipulate electromagnetic waves in wireless communication. In particular, the characteristics of wireless channels incorporating RISs offer substantial research value. Several previous studies have investigated the path loss characteristics of RIS-assisted wireless channels in practical scenarios. However, these pioneering studies ignore the effect of RIS array gain on path loss. This paper proposes a floating-intercept (FI) path loss model that includes the array gain of the RIS, the distance between the transmitter and the RIS, and the distance between the receiver and the RIS. In this RIS-FI model, the RIS array gain component is related to the reflection coefficients of all the unit cells of RIS. The proposed model can effectively characterize path loss in both the far-field and near-field regions of the RIS. A fabricated 512-element RIS and a vector network analyzer (VNA) are utilized to set up the channel measurement system. The proposed RIS-FI path loss model is validated by using measurement data collected from multiple scenarios, including outdoor square, indoor corridor, and classroom. Compared to other RIS path loss models, the experimental results show that the proposed model offers better accuracy in describing path loss in the near-field region of the RIS. The RIS-FI path loss model presented in this paper may pave the way for further research on RIS-assisted wireless channels.