Reconfigurable intelligent surfaces (RISs) have the potential of realizing the emerging concept of smart radio environments by leveraging the unique properties of metamaterials and large arrays of inexpensive antennas. In this article, we discuss the potential applications of RISs in wireless networks that operate at high-frequency bands, e.g., millimeter wave (30–100 GHz) and sub-millimeter wave (greater than 100 GHz) frequencies. When used in wireless networks, RISs may operate in a manner similar to relays. The present paper, therefore, elaborates on the key differences and similarities between RISs that are configured to operate as anomalous reflectors and relays. In particular, we illustrate numerical results that highlight the spectral efficiency gains of RISs when their size is sufficiently large as compared with the wavelength of the radio waves. In addition, we discuss key open issues that need to be addressed for unlocking the potential benefits of RISs for application to wireless communications and networks.

When fully implemented, sixth generation (6G) wireless systems will constitute intelligent wireless networks that enable not only ubiquitous communication but also high-accuracy localization services. They will be the driving force behind this transformation by introducing a new set of characteristics and service capabilities in which location will coexist with communication while sharing available resources. To that purpose, this survey investigates the envisioned applications and use cases of localization in future 6G wireless systems, while analyzing the impact of the major technology enablers. Afterwards, system models for millimeter wave, terahertz and visible light positioning that take into account both line-of-sight (LOS) and non-LOS channels are presented, while localization key performance indicators are revisited alongside mathematical definitions. Moreover, a detailed review of the state of the art conventional and learning-based localization techniques is conducted. Furthermore, the localization problem is formulated, the wireless system design is considered and the optimization of both is investigated. Finally, insights that arise from the presented analysis are summarized and used to highlight the most important future directions for localization in 6G wireless systems.

The introduction of millimeter wave (mm-wave) frequency bands for cellular communications with significantly larger bandwidths compared to their sub-6GHz counterparts, the resulting densification of network deployments and the introduction of antenna arrays with beamforming result in major increases in fronthaul capacity required for 5G networks. As a result, a radical re-design of the radio access network is required since traditional fronthaul technologies are not scaleable. In this article the use of analog radio over fiber (ARoF) is proposed and demonstrated as a viable alternative which, combined with space division multiplexing in the optical distribution network as well as photonic integration of the required transceivers, shows a path to a scaleable fronthaul solution for 5G. The trade-off between digitized and analog fronthaul is discussed and the ARoF architecture proposed by blueSPACE is introduced. Two options for the generation of ARoF two-tone signals for mm-wave generation via optical heterodyning are discussed in detail, including designs for the implementation in photonic integrated circuits as well as measurements of their phase noise performance. The proposed photonic integrated circuit designs include the use of both InP and SiN platforms for ARoF signal generation and optical beamforming respectively, proposing a joint design that allows for true multi-beam transmission from a single antenna array. Phase noise measurements based on laboratory implementations of ARoF generation based on a Mach-Zehnder modulator with suppressed carrier and with an optical phase-locked loop are presented and the suitability of these transmitters is evaluated though phase noise simulations. Finally, the viability of the proposed ARoF fronthaul architecture for the transport of high-bandwidth mm-wave 5G signals is proven with the successful implementation of a real-time transmission link based on an ARoF baseband unit with full real-time processing of extended 5G new radio signals with 800MHz bandwidth, achieving transmission over 10km of 7-core single-mode multi-core fiber and 9m mm-wave wireless at 25.5GHz with bit error rates below the limit for a 7% overhead hard decision forward error correction.

This work discusses the optimal reconfigurable intelligent surface placement in highly-directional millimeter wave links. In particular, we present a novel system model that takes into account the relationship between the transmission beam footprint at the RIS plane and the RIS size. Subsequently, based on the model we derive the end-to-end expression of the received signal power and, furthermore, provide approximate closed-form expressions in the case that the RIS size is either much smaller or at least equal to the transmission beam footprint. Moreover, building upon the expressions, we derive the optimal RIS placement that maximizes the end-to-end signal-to-noise ratio. Finally, we substantiate the analytical findings by means of simulations, which reveal important trends regarding the optimal RIS placement according to the system parameters.

In the current contribution, we examine the feasibility of fully-energy-autonomous operation of reconfigurable intelligent surfaces (RIS) through wireless energy harvesting (EH) from incident information signals. Towards this, we first identify the main RIS energy-consuming components and present a suitable and accurate energy-consumption model that is based on the recently proposed integrated controller architecture and includes the energy consumption needed for channel estimation. Building on this model, we introduce a novel RIS architecture that enables EH through RIS unit-cell (UC) splitting. Subsequently, we introduce an EH policy, where a subset of the UCs is used for beamsteering, while the remaining UCs absorb energy. In particular, we formulate a subset al.ocation optimization problem that aims at maximizing the signal-to-noise ratio (SNR) at the receiver without violating the RIS’s energy consumption demands. As a problem solution, we present low-complexity heuristic algorithms. The presented numerical results reveal the feasibility of the proposed architecture and the efficiency of the presented algorithms with respect to both the optimal and very high-complexity brute-force approach and the one corresponding to random subset selection. Furthermore, the results reveal how important the placement of the RIS as close to the transmitter as possible is, for increasing the harvesting effectiveness.

Satellite communications (SatComs) have recently been through a renaissance, both technologically and entrepreneurially. Ambitious plans have already come into fruition with the operation of low-Earth orbit (LEO) constellations including thousands of satellites and supported by state of the art but proprietary technologies, such as active antenna arrays and intersatellite links (ISLs). In this context, this article aims to provide a forward-looking vision of use cases and a deep dive into technological enablers that will be prominent in space communications beyond 2030. In parallel, it motivates how open standards can play a role in delivering affordable communication services in space. Starting from the 5G plans for nonterrestrial networks, we provide a survey and roadmap toward artificial intelligence (AI)-supported satellite systems, space-enabled quantum networks, and joint communications and positioning (JCAP) for space missions and interplanetary exploration.