In this paper, we consider a multi-user multiple-input multiple-output (MIMO) system aided by multiple intelligent reflecting surfaces (IRSs) that are deployed to increase the coverage and, possibly, the rank of the channel. We propose an optimization algorithm to configure the IRSs, which is aimed at maximizing the network sum-rate by exploiting only the statistical characterization of the locations of the mobile users. As a consequence, the proposed approach does not require the estimation of either instantaneous channel state information (CSI) or second-order channel statistics for IRS optimization, thus significantly relaxing (or even avoiding) the need of frequently reconfiguring the IRSs, which constitutes one of the most critical issues in IRS-assisted systems. Numerical results confirm the validity of the proposed approach. It is shown, in particular, that IRS-assisted wireless systems that are optimized based on statistical position information still provide large performance gains as compared to the baseline scenarios in which no IRSs are deployed.

We study a multi-user multiple-input multiple-output interference network in the presence of multiple reconfigurable intelligent surfaces (RISs). The entire system is described by using a circuit-based model for the transmitters, receivers, and RISs. This is obtained by leveraging the electromagnetic tool of mutual impedances, which accounts for the signal propagation and the mutual coupling among closely-spaced scattering elements. An iterative and provably convergent optimization algorithm that maximizes the sum-rate of RIS-assisted multi-user interference channels is introduced. Numerical results show that the sum-rate is enhanced if the mutual coupling among the RIS elements is accounted for at the optimization stage.

In this paper, a pervasive monitoring system to be deployed in underground environments is presented. The system has been specifically designed for the so-called “Bottini”, i.e., the medieval aqueducts dug beneath the Centre of Siena, Italy. The results of a measurement campaign carried out in the deployment scenario show that the transmission range of LoRa (Long Range) technology is limited to a maximum of 200 m, thus, making the adoption of a classical star topology impossible. Hence, a Linear Sensor Network topology is proposed based on multi-hop LoRa chain-type communications. In this scenario, an ad-hoc transmission scheme is presented that optimally evaluates the wake-up time of all nodes with the aim of minimizing the average energy dissipation deriving from clock offsets. Numerical results show that the proposed wake-up time optimization leads in the best case to a 50% reduction in power dissipation with respect to a scheme that evaluates the wake-up time in a non-optimal way.

In this paper, we propose a novel framework that aims to jointly design the reflection coefficients of multiple reconfigurable intelligent surfaces (RISs) and the precoding strategy of a single base station (BS) to optimize the self-tracking of the position and the velocity of a single multi-antenna user equipment (UE) that moves either in the far- or near-field region. Differently from the literature, and to keep the overall complexity affordable, we assume that RIS optimization is performed less frequently than localization and precoding adaptation. The proposed procedure leads to minimize the inverse of the received power in the UE position uncertainty area between two subsequent optimization steps. The optimal RIS and precoder strategy is compared with the classic beam focusing strategy and with a scheme that maximizes the communication rate. It is shown that if the RISs are optimized for communications, their configuration is suboptimal when used for tracking purposes. Numerical results show that in typical indoor environments with only one BS and a few RISs operating on millimeter waves, high location accuracy in the range of less than half a meter can be achieved.

This paper describes a wireless sensor network (WSN) used to monitor the health state of architectural heritage in real-time. The WSN has been deployed and tested on the “Rognosa” tower in the medieval village of San Gimignano, Tuscany, Italy. This technology, being non-invasive, mimetic, and long lasting, is particularly well suited for long term monitoring and on-line diagnosis of the conservation state of heritage buildings. The proposed monitoring system comprises radio-equipped nodes linked to suitable sensors capable of monitoring crucial parameters like: temperature, humidity, masonry cracks, pouring rain, and visual light. The access to data is granted by a user interface for remote control. The WSN can autonomously send remote alarms when predefined thresholds are reached.

We propose two novel distributed resource allocation (RA) schemes for the uplink of a cellular multi-carrier multi-format system based on the message passing (MP) technique. In the proposed approaches each transmitter iteratively sends and receives information messages to/from the base station with the goal of achieving an optimal RA strategy. The exchanged messages are the solution of small distributed allocation problems. Hence, despite the NP-hardness of the original RA problem, they distribute the computational effort in the cell among all the transmitters and the base station. Specifically, the first algorithm combines MP with a dynamic programming formula solved at each step, while the second method initially solves to optimality a simplified single-format RA via MP, and eventually performs format allocation to satisfy the rate constraints. Compared to alternatives, numerical results assess the validity of MP-based schemes both in terms of efficiency and complexity.