Reconfigurable intelligent surfaces (RISs), also known as intelligent reflecting surfaces (IRSs), or large intelligent surfaces (LISs), 1 have received significant attention for their potential to enhance the capacity and coverage of wireless networks by smartly reconfiguring the wireless propagation environment. Therefore, RISs are considered a promising technology for the sixth-generation (6G) of communication networks. In this context, we provide a comprehensive overview of the state-of-the-art on RISs, with focus on their operating principles, performance evaluation, beamforming design and resource management, applications of machine learning to RIS-enhanced wireless networks, as well as the integration of RISs with other emerging technologies. We describe the basic principles of RISs both from physics and communications perspectives, based on which we present performance evaluation of multiantenna assisted RIS systems. In addition, we systematically survey existing designs for RIS-enhanced wireless networks encompassing performance analysis, information theory, and performance optimization perspectives. Furthermore, we survey existing research contributions that apply machine learning for tackling challenges in dynamic scenarios, such as random fluctuations of wireless channels and user mobility in RIS-enhanced wireless networks. Last but not least, we identify major issues and research opportunities associated with the integration of RISs and other emerging technologies for applications to next-generation networks. 1 Without loss of generality, we use the name of RIS in the remainder of this paper.

https://hal.archives-ouvertes.fr/hal-03357962/document

Reconfigurable Intelligent Surfaces: Principles and Opportunities

Reconfigurable intelligent surfaces (RISs), also known as intelligent reflecting surfaces (IRSs), have received significant attention for their potential to enhance the capacity and coverage of wireless networks by smartly reconfiguring the wireless propagation environment. Therefore, RISs are considered a promising technology for the sixth-generation (6G) communication networks. In this context, we provide a comprehensive overview of the state-of-the-art on RISs, with focus on their operating principles, performance evaluation, beamforming design and resource management, applications of machine learning to RIS-enhanced wireless networks, as well as the integration of RISs with other emerging technologies. We describe the basic principles of RISs both from physics and communications perspectives, based on which we present performance evaluation of multi-antenna assisted RIS systems. In addition, we systematically survey existing designs for RIS-enhanced wireless networks encompassing performance analysis, information theory, and performance optimization perspectives. Furthermore, we survey existing research contributions that apply machine learning for tackling challenges in dynamic scenarios, such as random fluctuations of wireless channels and user mobility in RIS-enhanced wireless networks. Last but not least, we identify major issues and research opportunities associated with the integration of RISs and other emerging technologies for application to next-generation networks.

Providing connectivity to around half of the world population living in rural or underprivileged areas is a tremendous challenge, but, at the same time, a unique opportunity. Access to the Internet would provide the population living in these areas a possibility to progress on the educational, health, environment, and business levels. In this article, a survey of technologies for providing connectivity to rural areas, which can help address this challenge, is provided. Although access/fronthaul and backhaul techniques are discussed in this article, it is noted that the major limitation for providing connectivity to rural and underprivileged areas is the cost of backhaul deployment. In addition, energy requirements and cost-efficiency of the studied technologies are analyzed. In fact, the challenges faced for deploying an electricity network, as a prerequisite for deploying communication networks, are huge in these areas, and they are granted an important share of the discussions in this article. Furthermore, typical application scenarios in rural areas are discussed, and several country-specific use cases are surveyed. The main initiatives by key international players aiming to provide rural connectivity are also described. Moreover, directions for the future evolution of rural connectivity are outlined in this article. Although there is no single solution that can solve all rural connectivity problems, building gradually on the current achievements in order to reach ubiquitous connectivity, while taking into account the particularities of each region and tailoring the solution accordingly, seems to be the most suitable path to follow.

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A Key 6G Challenge and Opportunity—Connecting the Base of the Pyramid: A Survey on Rural Connectivity

Next-generation of the cellular network will attempt to overcome the limitations of the current Fifth Generation (5G) networks and equip itself to address the challenges which become obvious in the future. Currently, academia and industry have focused their attention on the Sixth Generation (6G) network, which is anticipated to be the next big game-changer in the telecom industry. The outbreak of COVID’19 has made the whole world to opt for virtual meetings, live video interactions ranging from healthcare, business to education. However, we miss an immersive experience due to the lack of supporting technology. Experts have anticipated that starting from the post-pandemic age, the performance requirements of technology for virtual and real-time communication, the rise of several verticals such as industrial automation, robotics, and autonomous driving will increase tremendously, and will skyrocket during the next decade. In this manuscript, we study the latest perspectives and future megatrends that are most likely to drive 6G. Initially, we describe the instances that lead us to the vision of 6G. Later, we narrate some of the use cases and the KPIs essential to meet their performance requirement. Further, we highlight the key requirements of 6G based on contemporary research such as UN sustainability goals, business model, edge intelligence, digital divide, and the trends in machine learning for 6G.

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6G Ecosystem: Current Status and Future Perspective

We are on the cusp of a new era of connected autonomous vehicles with unprecedented user experiences, tremendously improved road safety and air quality, highly diverse transportation environments and use cases, as well as a plethora of advanced applications. Realizing this grand vision requires a significantly enhanced vehicle-to-everything (V2X) communication network which should be extremely intelligent and capable of concurrently supporting hyper-fast, ultra-reliable, and low-latency massive information exchange. It is anticipated that the sixth-generation (6G) communication systems will fulfill these requirements of the next-generation V2X. In this article, we outline a series of key enabling technologies from a range of domains, such as new materials, algorithms, and system architectures. Aiming for truly intelligent transportation systems, we envision that machine learning will play an instrumental role for advanced vehicular communication and networking. To this end, we provide an overview on the recent advances of machine learning in 6G vehicular networks. To stimulate future research in this area, we discuss the strength, open challenges, maturity, and enhancing areas of these technologies.

6G for Vehicle-to-Everything (V2X) Communications: Enabling Technologies, Challenges, and Opportunities

The interference caused by a narrowband system on another system that transmits wideband or spectrally spread signals is, in general, a known problem in wireless communications. However, analyses found in the literature often model the signal of interest as a generic transport channel whose subcarriers convey information of the same kind. This does not reflect the specific structure and application nature of signals conveyed through the different physical channels of the Long Term Evolution (LTE) standard. Having the candidacy of wavelets as adequate means to mitigate narrowband interference (NBI) in both the user and control planes of LTE previously confirmed in Miranda et al. (Narrowband Interference Suppression in Long Term Evolution Systems, pp. 707–711, 2014), in this chapter we extend our analysis to different wavelet types and operation conditions. Biorthogonal, Coiflets, Daubechies, and Haar wavelets are put to the test with respect to their ability to suppress NBI in the LTE downlink. Our simulations suggest that an optimized wavelet-based NBI suppression process calls for different wavelet types, the choice of which being dependent on the LTE physical channel considered. Daubechies are shown to be most convenient for synchronization channels, while Coiflets are found to be the best option when it comes to data shared channels.

Wavelet-Based Narrowband Interference Suppression in Long Term Evolution Physical Channels

Collaborative cognitive mesh networks (CCMN) are a potential technology to be adopted in next-generation wireless networks, as it meets key requirements of 5G application scenarios, such as high flexibility and efficient spectrum usage. CCMN is composed of regular cognitive mechanisms and components, such as energy detection-based sensing, and has the ability to switch the data channel to take advantage of any available channels on a given spectrum band. Several cognitive mesh network architectures employ a common control channel (CCC) to perform dynamic channel allocation. Therefore, the multichannel–single interface manager (MC-SIM) algorithm aims to maximize channel usage with a system that does not depend on any CCC. The MC-SIM algorithm was tested in a real scenario and results showed enhanced throughput levels that are 29.5% greater.

5G Cognitive Wireless Mesh Network Without Common Control Channel

The main problems of multiple carriers that pass through non-linear devices are: a Nonlinear AM / AM conversion, a Nonlinear AM / PM conversion, and inter-modulation. These problems are usually present in satellite transmissions, where high-power amplifiers (HPAs) and nonlinear transponders are used, as well as in terrestrial broadcasting systems where, in order to enlarge the service area (geographical area in which the service is offered) High-power amplifiers operating in their Nonlinear region are used. The multi-carrier transmission called OFDM, which is widely used in wireless networks as WiMAX and LTE, falls in this context. In order to alleviate the effects of Nonlinear channels on OFDM signals, the present study suggests the use of a pre-distortion system, which is mathematically described through a complex power series. The Strategy is focused in determine the parameters of the pre-distortion system, which is based on the reduction of the inter-modulation power sum associated to inter-modulation products of any specified order. Analysis of configurations based on this strategy is presented with numerical results involving situations of specific interest.

Reduction of intermodulation products of superior order generated by Nonlinear systems over OFDM signals using a pre-distortion technique

This paper investigates the possibility of building the Energy Internet via a packetized management of non-industrial loads. The proposed solution is based on the cyber-physical implementation of energy packets where flexible loads send use requests to an energy server. Based on the existing literature, we explain how and why this approach could scale up to interconnected micro-grids, also pointing out the challenges involved in relation to the physical deployment of electricity network. We then assess how machine-type wireless communications, as part of 5G and beyond systems, will achieve the low latency and ultra reliability needed by the micro-grid protection while providing the massive coverage needed by the packetized management. This more distributed grid organization also requires localized governance models. We cite few existing examples as local markets, energy communities and micro-operator that support such novel arrangements. We close the paper by providing an overview of ongoing activities that support the proposed vision and possible ways to move forward.

Dick Carrillo

Papers

Wavelet-Based Narrowband Interference Suppression in Long Term Evolution Physical Channels

5G Cognitive Wireless Mesh Network Without Common Control Channel

Reduction of intermodulation products of superior order generated by Nonlinear systems over OFDM signals using a pre-distortion technique

Energy Internet via Packetized Management: Enabling Technologies and Deployment Challenges