Realizing RF Wavefront Copying with RIS for Future Extended Reality Applications

Lately a new approach to Extended Reality (XR), denoted as XR-RF, has been proposed which is realized by combining Radio Frequency (RF) Imaging and programmable wireless environments (PWEs). RF Imaging is a technique that aims to detect geometric and material features of an object through RF waves. On the other hand, the PWE focuses on the the conversion of the wireless RF propagation in a controllable, by software, entity through the utilization of Reconfigurable Intelligent Surfaces (RISs), which can have a controllable interaction with impinging RF waves. In that sense, this dynamic synergy leverages the potential of RF Imaging to detect the structure of an object through RF wavefronts and the PWE's ability to selectively replicate those RF wavefronts from one spatial location to wherever an XR-RF mobile user is presently located. Then the captured wavefront, through appropriate hardware, is mapped to the visual representation of the object through machine learning models. As a key aspect of the XR-RF's system workflow is the wavefront copying mechanism, this work introduces a new PWE configuration algorithm for XR-RF. Moreover, it is shown that the waveform replication process inevitably yields imprecision in the replication process. After statistical analysis, based on simulation results, it is shown that this imprecision can be effectively modeled by the gamma distribution.

On the Design of Super Constellations

In the evolving landscape of sixth-generation (6G) wireless networks, which demand ultra high data rates, this study introduces the concept of super constellation communications. Also, we present super amplitude phase shift keying (SAPSK), an innovative modulation technique designed to achieve these ultra high data rate demands. SAPSK is complemented by the generalized polar distance detector (GPD-D), which approximates the optimal maximum likelihood detector in channels with Gaussian phase noise (GPN). By leveraging the decision regions formulated by GPD-D, a tight closed-form approximation for the symbol error probability (SEP) of SAPSK constellations is derived, while a detection algorithm with O(1) time complexity is developed to ensure fast and efficient SAPSK symbol detection. Finally, the theoretical performance of SAPSK and the efficiency of the proposed O(1) algorithm are validated by numerical simulations, highlighting both its superiority in terms of SEP compared to various constellations and its practical advantages in terms of fast and accurate symbol detection.

Energy-aware Trajectory Optimization for UAV-mounted RIS and Full-duplex Relay

In the evolving landscape of sixth-generation (6G) wireless networks, unmanned aerial vehicles (UAVs) have emerged as transformative tools for dynamic and adaptive connectivity. However, dynamically adjusting their position to offer favorable communication channels introduces operational challenges in terms of energy consumption, especially when integrating advanced communication technologies like reconfigurable intelligent surfaces (RISs) and full-duplex relays (FDRs). To this end, by recognizing the pivotal role of UAV mobility, the paper introduces an energy-aware trajectory design for UAV-mounted RISs and UAV-mounted FDRs using the decode and forward (DF) protocol, aiming to maximize the network minimum rate and enhance user fairness, while taking into consideration the available on-board energy. Specifically, this work highlights their distinct energy consumption characteristics and their associated integration challenges by developing appropriate energy consumption models for both UAV-mounted RISs and FDRs that capture the intricate relationship between key factors such as weight, and their operational characteristics. Furthermore, a joint time-division multiple access (TDMA) user scheduling-UAV trajectory optimization problem is formulated, considering the power dynamics of both systems, while assuring that the UAV energy is not depleted mid-air. Finally, simulation results underscore the importance of energy considerations in determining the optimal trajectory and scheduling and provide insights into the performance comparison of UAV-mounted RISs and FDRs in UAV-assisted wireless networks.

Zero-Energy Reconfigurable Intelligent Surfaces (zeRIS)

A primary objective of the forthcoming sixth generation (6G) of wireless networking is to support demanding applications, while ensuring energy efficiency. Programmable wireless environments (PWEs) have emerged as a promising solution, leveraging reconfigurable intelligent surfaces (RISs), to control wireless propagation and deliver exceptional quality-ofservice. In this paper, we analyze the performance of a network supported by zero-energy RISs (zeRISs), which harvest energy for their operation and contribute to the realization of PWEs. Specifically, we investigate joint energy-data rate outage probability and the energy efficiency of a zeRIS-assisted communication system by employing three harvest-and-reflect (HaR) methods, i) power splitting, ii) time switching, and iii) element splitting. Furthermore, we consider two zeRIS deployment strategies, namely BS-side zeRIS and UE-side zeRIS. Simulation results validate the provided analysis and examine which HaR method performs better depending on the zeRIS placement. Finally, valuable insights and conclusions for the performance of zeRISassisted wireless networks are drawn from the presented results.

An Open Platform for Simulating the Physical Layer of 6G Communication Systems with Multiple Intelligent Surfaces

Reconfigurable Intelligent Surfaces (RIS) constitute a promising technology that could fulfill the extreme performance and capacity needs of the upcoming 6G wireless networks, by offering software-defined control over wireless propagation phenomena. Despite the existence of many theoretical models describing various aspects of RIS from the signal processing perspective (e.g., channel fading models), there is no open platform to simulate and study their actual physical-layer behavior, especially in the multi-RIS case. In this paper, we develop an open simulation platform, aimed at modeling the physical-layer electromagnetic coupling and propagation between RIS pairs. We present the platform by initially designing a basic unit cell, and then proceeding to progressively model and simulate multiple and larger RISs. The platform can be used for producing verifiable stochastic models for wireless communication in multi-RIS deployments, such as vehicle-to-everything (V2X) communications in autonomous vehicles and cybersecurity schemes, while its code is freely available to the public.

Performance Analysis of Synergetic UAV-RIS Communication Networks

The effective integration of unmanned aerial vehicles (UAVs) in future wireless communication systems depends on the conscious use of their limited energy, which constrains their flight time. Reconfigurable intelligent surfaces (RISs) can be used in combination with UAVs with the aim to improve the communication performance without increasing complexity at the UAVs' side. In this paper, we propose a synergetic UAV-RIS communication system, utilizing a UAV with a directional antenna aiming to the RIS. Also, we present the link budget analysis and closed-form expressions for the outage probability as well as for an important second order statistical parameter of the proposed synergetic UAV-RIS communication system, the average outage duration. Finally, numerical results illustrate the effectiveness of the proposed synergetic system.

On the Distribution of the Sum of Double-Nakagami-m Random Vectors and Application in Reconfigurable Intelligent Surfaces

Reconfigurable intelligent surfaces (RISs) intend to improve significantly the performance of future wireless networks, by controlling the wireless propagation medium through elements that can shift the phase of the reflected signals. Although ideally the signals reflected from a RIS are added coherently at the receiver, this is very challenging in practice due to the requirement for perfect channel state information (CSI) at the RIS and phase control. To facilitate the performance analysis of more practical RIS-assisted systems, first, we present novel closed-form expressions for the probability density function, the cumulative distribution function, the moments, and the characteristic function of the distribution of the sum of double-Nakagami-m random vectors, whose amplitudes follow the double-Nakagami-m distribution, i.e., the distribution of the product of two random variables following the Nakagami-m distribution, and phases are circular uniformly distributed. We also consider a special case of this distribution, namely the distribution of the sum of Rayleigh-Nakagami-m random vectors. Then, we exploit these expressions to investigate the performance of the RIS-assisted composite channel, assuming that the two links undergo Nakagami-m fading and the equivalent phase follows the uniform distribution, which corresponds to the case where CSI is not available at the RIS and leads to a lower bound of the performance of a system with CSI. Closed-form expressions for the outage probability, the average received signal-to-noise ratio, the ergodic capacity, the bit error probability, the amount of fading, and the channel quality estimation index are provided to evaluate the performance of the considered system. These metrics are also derived for the practical special case where one of the two links undergoes Rayleigh fading.