In this article, we present two datasets that we make publicly available for research. The data is collected in a testbed comprised of a custom-made reconfigurable intelligent surface (RIS) prototype and two regular orthogonal frequency-division multiplexing (OFDM) transceivers within an anechoic chamber. First, we discuss the details of the testbed and equipment used, including insights about the design and implementation of our RIS prototype. We further present the methodology we employ to gather measurement samples, which consists of letting the RIS electronically steer the signal reflections from an OFDM transmitter toward a specific location. To this end, we evaluate a suitably designed configuration codebook and collect measurement samples of the received power with an OFDM receiver. Finally, we present the resulting datasets, their format, and examples of exploiting this data for research purposes.

In this paper, we share our experience in designing, prototyping, and empirically characterizing RF Switch-based Reconfigurable Intelligent Surfaces (RIS). Our RIS design consists of arrays of patch antennas, delay lines, and programmable radio-frequency (RF) switches, enabling 3D beamforming passively, without active RF components. Our design introduces two key innovations: (i) a modular structure that provides scalability for sustainable deployments, and (ii) the support for 3-bit phase shifters, enabling high-spatial resolution codebooks. We realized this design through PCB technology and affordable electronic components, then rigorously validated our prototype in a controlled setting. With this paper, we make a comprehensive characterization of our RIS publicly available via a large dataset, to promote further empirical-driven research on this topic. Finally, we present a cost analysis of our design, which underscores the importance of sustainable practices in shaping the future of wireless technologies.

Reconfigurable Intelligent Surfaces (RISs) are expected to be massively deployed in future beyond-5th generation wireless networks, thanks to their ability to programmatically alter the propagation environment, inherent low-cost and low-maintenance nature. Indeed, they are envisioned to be implemented on the facades of buildings or on moving objects. However, such an innovative characteristic may potentially turn into an involuntary negative behavior that needs to be addressed: an undesired signal scattering. In particular, RIS elements may be prone to experience failures due to lack of proper maintenance or external environmental factors. While the resulting Signal-to-Noise-Ratio (SNR) at the intended User Equipment (UE) may not be significantly degraded, we demonstrate the potential risks in terms of unwanted spreading of the transmit signal to non-intended UEs. In this regard, we consider the problem of mitigating such undesired effectby proposing two simple yet effective algorithms, which are based on maximizing the Signal-to-Leakage-and-Noise-Ratio (SLNR) over a predefined two-dimensional (2D) area and are applicable in the case of perfect channel-state-information (CSI) and partial CSI, respectively. Numerical and full-wave simulations demonstrate the added gains compared to leakage-unaware and reference schemes.

In this paper, we present our experience designing, prototyping, and empirically characterizing RF Switch-based Reconfigurable Intelligent Surfaces (RIS). Our RIS design comprises arrays of patch antennas, delay lines and programmable radio-frequency (RF) switches that enable almost-passive 3D beamforming, i.e., without active RF components. We implement this design using PCB technology and low-cost electronic components, and thoroughly validate our prototype in a controlled environment with high spatial resolution codebooks. Finally, we make available a large dataset with a complete characterization of our RIS and present the costs associated with reproducing our design.

In this paper, we pioneer a novel mechanism that jointly enforces intra-cell and inter-cell resource allocation for future green 5G networks. Our proposal, namely TOMRAN, efficiently coordinates the activity of base stations in small dense cell deployments by means of the ABSF standard tool for inter-cell interference coordination. Additionally, TOMRAN applies intra-cell offloading of the cellular traffic through resource-limited outband D2D relay communications, using, e.g., 802.11-based connectivity. We take advantage of this tailwind to show that our approach offers significant performance gain while imposing minor network protocol modifications. Indeed, through an exhaustive simulation campaign, we prove that outband D2D relay communications not only reduce the complexity of interference coordination operations, but also greatly boost the energy efficiency of future green 5G networks.

The emergence of popular wireless technologies such as LTE and WiFi, and the exponential growth in the usage of these technologies, has led to extremely dense wireless networks. There are many proposals for coping with such densification. In particular, we evaluate the compound effect of inter-cell interference schemes and spectrum efficient intra-cell relay techniques, which have been individually proposed recently as separate solutions. We provide a jointly coordinated intracell and inter-cell resource allocation mechanism that opportunistically exploits network density as a resource. We show that intracell opportunistic relay, based on WiFi communications, reduces the complexity of Inter-Cell Interference Coordination (ICIC) and boosts the efficiency of ICIC in LTE. The superiority of the proposed solution to the legacy cellular network operation is proven via simulations.

The significant growth in mobile data traffic and the ever- increasing user's demand for high-speed, always connected networks continue challenging network providers and lead research towards solutions to enable faster, scalable and more flexible networks. In this paper we present the CROWD approach, a networking framework providing mechanisms to tackle the high densification and heterogeneity of wireless networks. The goal of CROWD is to design protocols and algorithms for very dense and heterogeneous wireless networks, which we call DenseNets. The mechanisms we propose include energy efficiency, MAC enhancements, connectivity management and backhaul configuration to contribute to the next generation of networks considering density as a resource instead of as an obstacle.