Abstract
This paper presents an optically transparent 2-bit unit-cell for reflective intelligent surface applications in Wi-Fi 6E. The unit-cell is based on a metalmesh and can be reconfigured electronically by adjusting the voltage applied to a varactor diode. The performance of the RIS is demonstrated through simulation, which shows that the results are in good agreement with the theoretical predictions.

Abstract
This paper presents a 1-bit graphene-based reflective reconfigurable intelligent surface (RIS), namely a reflectarray antenna, that operates in the Ka-band (27 - 31 GHz). The reflectarray unit-cell features a simple structure with one metal layer, a Rogers RT5880 substrate and a Graphene Sandwich Structure (GSS) on top. The GSS comprises two layers of graphene separated by a diaphragm paper and a thin PVC layer to enhance its durability. The reflectarray can ensure a 1-bit phase shift resolution, by alternating the bias voltage applied to the graphene. The unit-cell simulation shows that the losses are around 3 dB over the studied band for both unit-cell states. An equivalent circuit model is presented to facilitate the analysis and design of GSS-based unit-cells. The full-wave simulation results of a 32x32 reflectarray indicate a gain of 25 dBi for a steering angle of 10 deg., displaying a 1 dB gain bandwidth of 15%, confirming the promise of the graphene-based radiating elements.

Abstract
Unmanned Aerial Vehicles (UAVs) are versatile platforms for carrying communications nodes such as Wi-Fi Access Points and cellular Base Stations. Flying Networks (FNs) offer on-demand wireless connectivity where terrestrial networks are impractical or unsustainable. However, managing communications resources in FNs presents challenges, particularly in optimizing UAV placement to maximize Quality of Service (QoS) for Ground Users (GUs) while minimizing energy consumption, given the UAVs' limited battery life. Existing multi-UAV placement solutions primarily focus on maximizing coverage areas, assuming static UAV positions and uniform GU distribution, overlooking energy efficiency and heterogeneous QoS requirements. We propose the Sustainable multi-UAV Performance-aware Placement (SUPPLY) algorithm, which defines and optimizes UAV trajectories to reduce energy consumption while ensuring QoS based on Signal-to-Noise Ratio (SNR) in the links with GUs. Additionally, we introduce the Multi-UAV Energy Consumption (MUAVE) simulator to evaluate energy consumption. Using both MUAVE and ns-3 simulators, we evaluate SUPPLY in typical and random networking scenarios, focusing on energy consumption and network performance. Results show that SUPPLY reduces energy consumption by up to 25% with minimal impact on throughput and delay.

Abstract
Unmanned Aerial Vehicles (UAVs) are increasingly used as wireless communications nodes, serving as Wi-Fi Access Points and Cellular Base Stations. To enable energy-efficient access networks, we previously introduced the Sustainable multi-UAV Performance-aware Placement (SUPPLY) algorithm, which focuses on the energy-efficient placement of UAVs as Flying Access Points (FAPs) to serve Ground Users (GUs). However, SUPPLY did not address the backhaul link. This paper presents the Simple Gateway Positioning (SGWP) solution, which optimizes the position of a Gateway (GW) UAV to ensure backhaul connectivity in a two-tier network. We integrate SUPPLY for FAP positioning with SGWP for GW placement and evaluate their combined performance under various scenarios involving different GUs' Quality of Service (QoS) requirements and positions. Our results demonstrate that SUPPLY and SGWP can be used jointly in a two-tier network with minimal performance degradation.

Abstract
The 6G paradigm and the massive usage of interconnected wireless devices introduced the need for flexible wireless networks. A promising approach lies in employing Mobile Robotic Platforms (MRPs) to create communications cells on-demand. The challenge consists in positioning the MRPs to improve the wireless connectivity offered. This is exacerbated in millimeter wave (mmWave), Terahertz (THz), and visible light-based networks, which imply the establishment of short-range, Line of Sight (LoS) wireless links to take advantage of the ultra-high bandwidth channels available. This paper proposes a solution to enable the obstacle-aware, autonomous positioning of MRPs and provide LoS wireless connectivity to communications devices. It consists of 1) a Vision Module that uses video data gathered by the MRP to determine the location of obstacles, wireless devices and users, and 2) a Control Module, which autonomously positions the MRP based on the information provided by the Vision Module. The proposed solution was validated in simulation and through experimental testing, showing that it is able to position an MRP while ensuring LoS wireless links between a mobile communications cell and wireless devices or users.

Abstract
Reconfigurable Intelligent Surfaces (RIS) are an enabling technology widely investigated towards 6G. The viability of large active metasurfaces is constrained by the RF performance, cost, and power consumption. The number of switches per unit cell is a key design parameter that designers aim to minimize following cost and power consumption drivers. However, an efficient use of the aperture is ultimately required and although a one-to-one correspondence between number of switches and phase-quantization bits seems intuitive, one may question its impact. Here we present a full-wave evaluation of a 30x30 1-bit reflective RIS, implemented considering two pin diodes per unit cell. The RIS allows scanning up to 60 degrees from 28 to 29 GHz with a maximum aperture efficiency of 22%. This superior performance provides tantalizing evidence that the multiple switches per bit approach should not be discarded a priori due to its apparent higher complexity.