In this paper, a random access scheme is introduced, which relies on the combination of packet erasure correcting codes and successive interference cancellation (SIC). The scheme is named coded slotted ALOHA. A bipartite graph representation of the SIC process, resembling iterative decoding of generalized low-density parity-check codes over the erasure channel, is exploited to optimize the selection probabilities of the component erasure correcting codes through a density evolution analysis. The capacity (in packets per slot) of the scheme is then analyzed in the context of the collision channel without feedback. Moreover, a capacity bound is developed, and component code distributions tightly approaching the bound are derived.

This work investigates a multibeam system for joint sensing and communication (JSC) based on multiple-input multiple-output (MIMO) 5G new radio (NR) waveforms. In particular, we consider a base station (BS) acting as a monostatic sensor that estimates the range, speed, and direction of arrival (DoA) of multiple targets via beam scanning using a fraction of the transmitted power. The target position is then obtained via range and DoA estimation. We derive the sensing performance in terms of probability of detection and root mean squared error (RMSE) of position and velocity estimation of a target under line-of-sight (LOS) conditions. Furthermore, we evaluate the system performance when multiple targets are present, using the optimal sub-pattern assignment (OSPA) metric. Finally, we provide an in-depth investigation of the dominant factors that affect performance, including the fraction of power reserved for sensing.

Precise localization and tracking of moving objects is of great interest for a variety of emerging applications including the Internet-of-Things (IoT). The localization and tracking tasks are challenging in harsh wireless environments, such as indoor ones, especially when objects are not equipped with dedicated tags (noncollaborative). The problem of detecting, localizing, and tracking noncollaborative objects within a limited area has often been undertaken by exploiting a network of radio sensors, scanning the zone of interest through wideband radio signals to create a radio image of the objects. This paper presents a sensor network for radio imaging (sensor radar) along with all of the signal processing steps necessary to achieve highaccuracy objects tracking in harsh propagation environments. The described sensor radar is based on the impulse radio (IR) ultrawideband (UWB) technology, entailing the transmission of very short duration pulses. Experimental results with actual UWB signals in indoor environments confirm the sensor radar’s potential in IoT applications.

Nowadays, high expectations are set for a digitally enabled circular economy (CE), to enhance resource efficiency. Tracing, tracking, and storing information is most important for this. In this paper, the application of Internet of Things (IoT) and Distributed Ledger Technology (Blockchain) are hence discussed by presenting the case of professional Electrical and Electronic Equipment (EEE) in Italy. Within the context of CE, prevention of electronic waste (WEEE) is extremely relevant as it is a fast-growing waste stream, and the products contain environmentally damaging substances as well as valuable and rare materials. The use of a proper combination of IoT and blockchain can help the producers to keep control on products until EEE end-of-life, while promoting CE strategies and supporting decision-making. Based on the outcomes of five interviews conducted in 2019 to companies of the EEE sector, potential improvements in the EEE end-of-use management are discussed. After providing the definition of requirements for both the technical solution and its testing are provided, three solution variations and the related business models are created and presented, as well as considerations on their environmental and economic impacts. The study shows how digital technologies can support the appropriate and circular management of EEE products and WEEE.

Multiple radar systems represent an attractive option for target tracking because they can significantly enlarge the area coverage and improve both the probability of trajectory detection and the localization accuracy. The presence of multiple extended targets or weak targets is a challenge for multiple radar systems. Moreover, their performance may be severely deteriorated by regions characterized by a high clutter density. In this article, an algorithm for detection and tracking of multiple targets, extended or weak, based on measurements provided by multiple radars in an environment with heavily cluttered regions, is proposed. The proposed method features three stages. In the first stage, past measurements are exploited to build a spatiotemporal clutter map in each radar; a weight is then assigned to each measurement to assess its significance. In the second stage, a track-before-detect algorithm, based on a weighted 3-D Hough transform, is applied to obtain target tracklets. In the third stage, a low-complexity tracklet association method, exploiting a lion reproduction model, is applied to associate tracklets of the same target. Three experiments are presented to illustrate the effectiveness of the proposed approach. The first experiment is based on synthetic data, the second one is based on actual data from a radar network with two homogeneous air surveillance radars, and the third one is based on actual data from a radar network with four different marine surveillance radars. The results reveal that the proposed method can outperform competing approaches.

In this letter, we develop a converse bound on the asymptotic load threshold of coded slotted ALOHA (CSA) schemes with K-multi packet reception capabilities at the receiver. Density evolution is used to track the average probability of packet segment loss and an area matching condition is applied to obtain the converse. For any given CSA rate, the converse normalized to K increases with K, which is in contrast with the results obtained so far for slotted ALOHA schemes based on successive interference cancellation. We show how the derived bound can be approached using spatially-coupled CSA.