Large Intelligent Surface Research Articles

Enhancing wireless communication systems through large intelligent surfaces: a performance analysis of LIS-assisted NOMA networks

The integration of large intelligent surfaces (LIS) with non-orthogonal multiple access (NOMA) networks has emerged as a promising solution to enhance the capacity and coverage of wireless communication systems. In this study, we analyse the performance of a NOMA network with the assistance of LIS. We propose a system model where a base station (BS) equipped with a LIS serves multiple users. The LIS consists of many passive elements that can influence the wireless channel by adjusting the reflection coefficients. We consider a downlink scenario where the BS transmits to multiple users simultaneously using NOMA, and the LIS helps to improve the signal quality and coverage. We additionally evaluate the efficiency of the suggested LIS-assisted NOMA network. In addition, we evaluate the efficiency of the LIS-assisted NOMA network in comparison to conventional NOMA systems that do not utilize LISs. The findings indicate that the LIS has a notable impact on enhancing the system's performance in terms of diversity gain, probability of error, and pairwise error probability (PEP). Moreover, the suggested LIS-assisted NOMA network is shown to be superior to conventional NOMA systems through comparison. These findings offer useful insights into the performance analysis of LIS-assisted NOMA networks. They also serve as inspiration and motivation for future research and development in this new subject, with the potential to revolutionize wireless communication systems.

Multi-user directional modulation with reconfigurable holographic surfaces

Large intelligent surfaces arise as an emerging technology and critical building block for sixth-generation (6G) wireless networks. Reconfigurable holographic surfaces (RHSs) have been attracting significant attention recently as active antenna arrays with the capability of forming narrow beams at low cost and complexity. This paper introduces the directional modulation (DM) concept for RHS, where a large number of elements are exploited to control not only the signal’s power at the receiver but also its phase. Thus, a novel DM algorithm is proposed for RHS enables modulating a carrier wave to transmit information toward specific directions while broadcasting arbitrary signals toward other directions. Error vector magnitude results are reported for multiple users, where the directions of two users with respect to the RHS are varied. Mutual information result is also provided for 6 users to demonstrate the application of RHS for the physical layer security. Results are highly promising for future low-cost and secure spatially multiplexed communications.

Cramér-Rao Lower Bound Analysis of Positioning With Planar Large Intelligent Surfaces Under Rician Channel

Cramér-Rao Lower Bound Analysis of Positioning With Planar Large Intelligent Surfaces Under Rician Channel

Secrecy Analysis of a Mu-MIMO LIS-Aided Communication Systems under Nakagami-m Fading Channels.

This study evaluates the performance of large intelligent surface (LIS) technology in the context of a multi-user MIMO mobile communication system (Mu-MIMO) proposed for the sixth generation (6G). LIS employs digitally controlled reflectors to enhance Signal-to-Interference plus Noise Ratio (SINR) and establish line of sight (LoS) connectivity in non-LoS environments, improving transmission security. Analytical expressions are derived to assess LIS performance metrics, including distribution parameters, bit error probability, and secrecy outage probability, considering the presence of eavesdroppers and environmental fading. The study highlights the potential of LIS technology to enhance the confidentiality and reliability of digital communication systems in next-generation networks.

On the Performance of Partial LIS for 6G Systems

One of the key technologies of 6G communications relies on large intelligent surfaces (LIS), which can be viewed as a near-field beamformer that is supportive of extremely high symbol rates and enables a high level of interference avoidance. This article focuses on LIS systems, analysing the impact of the use of a whole LIS system or a subset of an antenna array. We analyse an LIS system associated with a single carrier with frequency domain equalization (SC-FDE), and with different receiver types of varying complexities. Because it is a function of the number of antennas, the computational complexity decreases when antenna elements that are closer to the user equipment are used instead of the whole LIS. Moreover, with a partial LIS, a reduction of energy consumption is achieved, and mitigation of the interference levels is obtained, allowing a performance very close to that obtained with the whole LIS system.

Scheduling of Industrial Control Traffic for Dynamic RAN Slicing with Distributed Massive MIMO

Industry 4.0, with its focus on flexibility and customizability, is pushing in the direction of wireless communication in future smart factories, in particular, massive multiple-input-multiple-output (MIMO) and its future evolution of large intelligent surfaces (LIS), which provide more reliable channel quality than previous technologies. At the same time, network slicing in 5G and beyond systems provides easier management of different categories of users and traffic, and a better basis for providing quality of service, especially for demanding use cases such as industrial control. In previous works, we have presented solutions for scheduling industrial control traffic in LIS and massive MIMO systems. We now consider the case of dynamic slicing in the radio access network, where we need to not only meet the stringent latency and reliability requirements of industrial control traffic, but also minimize the radio resources occupied by the network slice serving the control traffic, ensuring resources are available for lower-priority traffic slices. In this paper, we provide mixed-integer programming optimization formulations for radio resource usage minimization for dynamic network slicing. We tested our formulations in numerical experiments with varying traffic profiles and numbers of nodes, up to a maximum of 32 nodes. For all problem instances tested, we were able to calculate an optimal schedule within 1 s, making our approach feasible for use in real deployment scenarios.

Capacity Optimization of Large Intelligent Surface With Hardware Impairment Based on Meta-Deep Learning

Capacity Optimization of Large Intelligent Surface With Hardware Impairment Based on Meta-Deep Learning

Design of Near-Field Beamforming for Large Intelligent Surfaces

Design of Near-Field Beamforming for Large Intelligent Surfaces

Multi-user communications for line-of-sight large intelligent surface systems

In this paper, we propose a new interference-suppression beamformer design and a Direction-of-Arrival (DoA) estimation method for Line-of-Sight (LoS) multi-user communication systems with circular Large Intelligent Surfaces (LISs). This symmetrical circular-shaped LIS allows signals defined on it to be formed by combining Fourier and Bessel series. The Fourier harmonics are orthogonal along the rotational direction and the Bessel functions constituting the Bessel series are orthogonal along the radial direction. Synthesizing basis functions from these two series results in the proposed interference-suppression beamformer, with their coefficients designed to cancel inter-user interference. Also by exploiting signal structure of a circular LIS communicating with Mobile Stations (MSs), we devise a DoA estimation method to obtain directional information of incoming signals. Under LoS channel, the DoA corresponds to elevation and Azimuth angles of MSs relative to the LIS. This method is numerically demonstrated to have promising performance with high-frequency carriers.

An Evaluation of the Signal to Noise Ratio (SNR) of Next Generation Wireless Communication Systems using Large Intelligent Surfaces: Deep Learning Approach

The existing data rate must be greatly increased in order to support the numerous applications of the next generation communication systems. Using Large Intelligent Surfaces (LIS), which are a panel with mounted reflective components, is one way to address this problem. Their primary function is to divert the electromagnetic signal to the intended user. As a result, the received signal's strength and reception quality both improve, improving the Quality of Service (QoS). Machine Learning algorithms have been used to implement LIS in a number of ways, including channel estimation and the calculation of phase shifts (discrete), to mention a few. Here, it is suggested that the Signal to Noise Ratio (SNR) for a LIS-supported communication system be assessed using a Deep Learning (DL) model. On the DL model, the effects of the SGD, Adam RMSProp Adadelta and Adamax optimizers are investigated. The Mean Squared Error (MSE) loss function is taken into account. The Adam optimizer offers the highest level of precision, making it preferable to other optimizers. The SNR for 10 users is measured using the suggested DL model with Adam Optimizer. The outcomes of this work is contrasted with the SNR estimate by an existing technique that calculates SNR based on LIS size and the location of transmitter and receiver with an accuracy of 93.5%. The simulation results indicate that the accuracy is increased to 96% using the suggested DL model which attains an average error of 3.6.

Toward 6G Holographic Localization: Enabling Technologies and Perspectives

In the last years, we have experienced the evolution of wireless localization from being a simple add-on feature for enabling specific applications to becoming an essential characteristic of wireless cellular networks, as for sixth generation (6G) cellular networks. This paper illustrates the importance of radio localization and its role in almost all cellular generations. Also, it speculates on the idea of holographic localization where the characteristics of electromagnetic (EM) waves, including the spherical wavefront in the near-field, are fully controlled and exploited to achieve better wireless localization. Along this line, we briefly overview possible technologies, such as large intelligent surfaces, and challenges to realize holographic localization. To corroborate our vision, we also include a numerical example that confirms the potentialities of holographic localization.

Microwave characterization of two Ba 0.6Sr 0.4TiO 3 dielectric thin films with out-of-plane and in-plane electrode structures

Ferroelectric thin films have recently attracted renewed interest in research due to their great potential for designing novel tunable electromagnetic devices such as large intelligent surfaces (LIS). However, the mechanism of how the polar structure in the ferroelectric thin films contributes to the desired tunable performance, especially at the microwave frequency range which is the most widely used frequency range of electromagnetics, has not been illustrated clearly. In this paper, we described several straightforward and cost-effective methods to fabricate and characterize Ba_0.6Sr_0.4TiO₃ (BST) thin films at microwave frequencies. The prepared BST thin films here exhibit homogenous structures and great tunability in a wide frequency and temperature range when the applied field is in the out-of-plane direction. The high tunability can be attributed to the high concentration of polar nanoclusters. Their response to the applied DC field was directly visualized using a novel non-destructive near field scanning microwave microscope (NSMM) technique. Our results have provided some intriguing insight into the application of ferroelectric thin films for future programmable high-frequency devices and systems.

Twelve Scientific Challenges for 6G: Rethinking the Foundations of Communications Theory

The research in the sixth generation of wireless networks needs to tackle new challenges in order to meet the requirements of emerging applications in terms of high data rate, low latency, high reliability, and massive connectivity. To this end, the entire communication chain needs to be optimized, including the channel and the surrounding environment, as it is no longer sufficient to control the transmitter and/or the receiver only. Investigating large intelligent surfaces, ultramassive multiple-input-multiple-output, and smart constructive environments will ultimately contribute to this direction. In addition, to allow the exchange of high dimensional sensing data between connected intelligent devices, semantic and goaloriented communications need to be considered for a more efficient and context-aware information encoding. In particular, for multi-agent systems, where agents are collaborating together to achieve a complex task, emergent communication, instead of hard-coded communication, can be learned for more efficient task execution and communication resources use. Moreover, new physical phenomena, such as the thermodynamics of communication and the interaction between information theory and electromagnetism should be exploited to better understand the physical limitations of different technologies, e.g., holographic communications. Another new communication paradigm is to consider the end-to-end communication system optimization instead of block-by-block optimization, which requires exploiting machine learning theory, non-linear signal processing theory, and non-coherent communications theory. Within this context, we identify and investigate twelve scientific challenges for rebuilding the theoretical foundation of communications. Furthermore, we present an overview of each of the challenges, along with their respective research opportunities and associated challenges.

IRS, LIS, and Radio Stripes-Aided Wireless Communications: A Tutorial

This is a tutorial on current techniques that use a huge number of antennas in intelligent reflecting surfaces (IRS), large intelligent surfaces (LIS), and radio stripes (RS), highlighting the similarities, differences, advantages, and drawbacks. A comparison between IRS, LIS, and RS is performed in terms of the implementation and capabilities, in the form of a tutorial. We begin by introducing the IRS, LIS, and RS as promising technologies for 6 G wireless technology. Then, we will look at how the three notions are applied in wireless networks. We discuss various performance indicators and methodologies for characterizing and improving the performance of IRS, LIS, and RS-assisted wireless networks. We cover rate maximization, power consumption reduction, and cost implementation concerns in order to take advantage of the performance increase. Furthermore, we extend the discussion to some cases of emerging use. In the description of the three concepts, IRS-assisted communication was introduced as a passive system, considering the capacity/data rate, with power optimization being an advantage, while channel estimation was a challenge. LIS is an active component that goes beyond massive MIMO; a recent study found that channel estimation issues in IRS had improved. In comparison to IRS, capacity enhancement is a highlight, and user interference showed a trend of decreasing. However, power consumption due to utilizing power amplifiers has restrictions. The third technique for increasing coverage is cell-free massive MIMO with RS, with easy deployment in communication network structures. It is demonstrated to have suitable energy efficiency and power consumption. Finally, for future work, we further propose expanding the conversation to include some cases of new uses, such as complexity reduction; design and simulation with LDPC code could be a solution to decreasing complexity.

Editorial

Reconfigurable Intelligent Surface (RIS), also known as intelligent reflecting surface or large intelligent surface, is an emerging new physical-layer technology in the field of wireless communications. The basic idea of RIS is to deploy a reconfigurable passive array in the environment to manipulate the propagation of electron-magnetic waves. RIS promises a new design paradigm for wireless communications, where the wireless propagation environment can be dynamically controlled, which is substantially different from the conventional design that focuses only on the transmitter and receiver. For RIS-aided wireless communications, some of the current methodologies in conventional communication systems need to be revised, and some novel solutions are required to realize the potential benefits of the RIS. Although the number of publications about RIS has recently sharply increased, there are still many challenging issues to be extensively investigated, such as the RIS channel modeling, fundamental performance limits, the system design, joint optimization of the RIS and the transceivers, channel state information acquisition, and interdisciplinary applications. The goal of this Special Issue on “Reconfigurable Intelligent Surface Aided Wireless Communications” of Intelligent and Converged Networks (ICN) is to attract high-quality papers of original research on RIS-aided wireless communications. The response from the community to the call has been overwhelming. Many of the submissions are from the most well known research groups in the field. After a strict review process, we decided to accept 8 papers, which were selected based on the technical relevance and merits.

Distributed and Scalable Uplink Processing for LIS: Algorithm, Architecture, and Design Trade-Offs

The Large Intelligent Surface (LIS) is a promising technology in the areas of wireless communication, remote sensing and positioning. It consists of a continuous radiating surface located in the proximity of the users, with the capability to communicate by transmission and reception (replacing base stations). Despite its potential, there are numerous challenges from an implementation point of view, with the interconnection data-rate, computational complexity, and storage the most relevant ones. In order to address these challenges, hierarchical architectures with distributed processing techniques are envisioned to be relevant for this task, while ensuring scalability. In this work we perform algorithm-architecture codesign to propose two distributed interference cancellation algorithms, and a tree-based interconnection topology for uplink processing. We also analyze the performance, hardware requirements, and architecture trade-offs for a discrete LIS, in order to provide concrete case studies and guidelines for efficient implementation of LIS systems.

Deployment Strategies for Large Intelligent Surfaces

Beyond 5G communication systems must be able to meet the requirements imposed by the ever-increasing demand in capacity, while guaranteeing robustness, reliability, low latency, security, as well as spectral and power efficiencies. Large intelligent surfaces (LIS) as an evolution of massive MIMO have drawn considerable attention among researchers, being already considered as one of the key technologies to be included in beyond 5G communication systems. Due to the massive number of antennas, it also brings several challenges namely in terms of computational complexity. In this paper, we intend to provide guidelines for the LIS practical implementation and configuration by specifying system parameters and their consequent relationship for a panel-based LIS. In particular, the interplay between the number of baseband outputs per square metre, the fraction of activated area, the panel size and terminal density is summarised by an empirical law under the assumption that all terminals experience reasonable quality of service. Furthermore, performance results show that, in general, moderate panel sizes offer the best rates, highlighting that there is no need to activate a large fraction of LIS to provide an acceptable minimum terminal rate. However, such fractions may require more baseband outputs per panel, leading to a higher number of baseband outputs per square metre, translating into higher implementation complexity. Finally, it is observed that the implicit rate loss of using sparse static panel deployments instead of contiguous panel deployments that are dynamically activated/deactivated is not so significant, omitting the complexity involved in managing the set of activated panels.

Beyond 5G Without Obstacles: mmWave-over-Fiber Distributed Antenna Systems

Beyond-5G wireless systems require significant improvement to enable the Internet of Everything, offering ultra-reliability, ultra-low-latency and high data-rates for holographic telepresence, immersive augmented and virtual reality, and cyber-physical systems in Industry 4.0. The mmWave frequency band (30–300 GHz) provides the required bandwidths, but very challenging propagation conditions exist. Conventional co-located multi-antenna systems counter higher path loss, but are insufficient in challenging real-life scenarios with frequent non-line-of-sight conditions. For distributed massive MIMO systems or large intelligent surfaces, we advocate optically-enabled distributed antenna systems (DAS) to alleviate these issues. To ensure tight synchronization and scalability, we propose a mmWave-over-fiber based architecture with low-complexity high-performance remote antenna units (RAUs). Strategically distributing and integrating RAUs in the user equipments' environment yield high throughput and reliable coverage. We demonstrate a mmWave-over-fiber DAS yielding multi-Gb/s mmWave communication in a harsh indoor environment with non-line-of-sight conditions, measuring wireless data rates up to 24 Gb/s, by selecting the RAU yielding the best link quality, and up to 48 Gb/s, by leveraging distributed MIMO techniques.

Mobility Support for Millimeter Wave Communications: Opportunities and Challenges

Millimeter-wave (mmWave) communication technology offers a potential and promising solution to support 5G and B5G wireless networks in dynamic scenarios and applications. However, mobility introduces many challenges as well as opportunities to mmWave applications. To address these problems, we conduct a survey of the opportunities and technologies to support mmWave communications in mobile scenarios. Firstly, we summarize the mobile scenarios where mmWave communications are exploited, including indoor wireless local area network (WLAN) or wireless personal area network (WPAN), cellular access, vehicle-to-everything (V2X), high speed train (HST), unmanned aerial vehicle (UAV), and the new space-air-ground-sea communication scenarios. Then, to address users’ mobility impact on the system performance in different application scenarios, we introduce several representative mobility models in mmWave systems, including human mobility, vehicular mobility, high speed train mobility and ship mobility. Next we survey the key challenges and existing solutions to mmWave applications, such as channel modeling, channel estimation, anti-blockage, and capacity improvement. Lastly, we discuss the open issues concerning mobility-aware mmWave communications that deserve further investigation. In particular, we highlight future heterogeneous mobile networks, dynamic resource management, artificial intelligence (AI) for mobility and integration of geographical information, deployment of large intelligent surface and reconfigurable antenna technology, and finally, the evolution to Terahertz (THz) communications.

Large Intelligent Surface-Based Generalized Index Modulation

Novel communication technology based on large intelligent surface (LIS), which manipulates the phase of the incident waves to enhance the communication quality, has been proposed as a promising candidate for future wireless communication systems and standards. In order to improve the spectral efficiency, the concept of LIS assisted communications has been introduced into the realm of index modulation (IM) recently. In this letter, a practical LIS based generalized spatial modulation (LIS-GSM) scheme is proposed by modulating the transmit signals through both transmitter and LIS jointly while designing the pattern of receive antennas in a more flexible way. Furthermore, a unified framework for the derivation of the theoretical average bit error rate (ABER) based on the maximum likelihood detector is also presented. Simulation results demonstrate that LIS-GSM is more robust in terms of ABER as well as receive antenna pattern compared with conventional LIS-SM.