Internet of Things (IoT) technology has become ubiquitous in a multitude of applications and its use is growing. However, the expansion of IoT faces a major difficulty: scalability, that is, very dense deployment of communicating devices is currently limited. In long-range networks, such as LoRa, the downlink is critical because it limits the number of acknowledgements that can be sent, and consequently reliability. It also limits the possibility to update the devices, which could be critical when they are deployed for decades. To overcome those problems, we propose a solution, inspired by Non Orthogonal Multiple Access (NOMA) techniques, to increase by at least one order of magnitude the number of devices that can be addressed. While the approach differentiates the devices by the power allocated to them, it differs from the vast majority of previous works on power domain NOMA because it does not require interference cancellation. Instead, it benefits from the spectrum spreading of the modulation scheme (chirp spread spectrum), where, at the end of the decoding phase, the information carried by a symbol is found in the position of a peak in the Fourier domain. In the vast majority of cases, the information from different users results in different peak positions, not creating any interference. In that sense, we get closer to avoidance schemes such as time or frequency hopping, but without using a code. In this article, we propose a new solution for NOMA in the power domain that does not suffer from the limitations induced by interference cancellation residues. The proposed system, including preamble detection and channel estimation, is presented and evaluated by simulations. We demonstrate that our proposed scheme increases the number of devices by one order of magnitude compared to the current system which allows addressing only one user at a time and maintains full compatibility with the LoRa physical layer standard.

The brief contact losses between the pantograph and the catenary in high-speed trains create transient interferences, which extend to the frequency bands used by telecommunication systems. This article presents a study of the impact of these transient wideband interferences on LTE communications between the train and a base station. In this study, we set up an experimental test bench, which establishes LTE communication between a communication tester and a USB/LTE dongle in the presence of transient interferences. We analysed the impact of these interferences on the error vector magnitude (EVM) of the received LTE signals and we observed that the EVM evolution does not explain certain communication interruptions. Indeed, interruptions can occur for EVM values significantly inferior to the standard limits. To understand the relationship between the interference characteristics and the communication interruption, we studied the peak to average power ratio (PAPR). Indeed, the PAPR is well suited to analyse transient interferences because it evolves with the amplitude but also with the repetition of the transient. Then, the PAPR measurement can provide a diagnostic assistance to analyse whether along certain railway lines, pantograph-catenary interferences are the cause of the LTE interruptions.

Wireless connections are more and more used in different applications and in public areas for services to consumers but also for handling (sometimes) sensitive communications (for instance, in railway systems or for remote video monitoring systems). Such systems can have to face different kind of attacks that target the behind service. Our article aims to detect, as soon as possible and online, attacks that can occur on wireless networks, to be able to react very quickly. In this article, we present some results of data analysis methods, on Wi-Fi signals, to differentiate the ones with attacks from the ones without. This study focuses on low-power jamming attacks with a slight or even no impact on Wi-Fi communications. This is more challenging than detecting high-power jamming attacks, which have already been addressed in the literature. Being able to detect a low-impact attack is a crucial issue in a global security strategy, making it possible to launch countermeasures before the interruption of the communication. The Wi-Fi bands are also in the Industrial, Scientific and Medical (ISM) frequencies, making the environment complicated to analyze. Clustering methods such as agglomerative hierarchical clustering are used to identify some clusters and then to map them to the real classes (with or without attacks). A deep analysis of the clusters obtained in a dataset acquired in uncontrolled conditions is carried out. This is done in order to understand what is responsible of the clustering assignment of the different points and to extract the clusters, which can be used to design a detection attack strategy.

In this study, power-domain non-orthogonal multiple access (NOMA) is combined with zero-forcing (ZF) vertical Bell Labs layered space-time (V-BLAST) technique. Motivated by the fact that the successive interference cancellation (SIC) is a pivotal element in either technique, we thoroughly investigate the impact of SIC on inter-user and inter-layer interference. A two-user downlink scenario is investigated where a multi-antenna base station with no instantaneous channel state information simultaneously communicates with two users each with multiple antennas. The average sum rate of the considered system is analytically derived in an exact form. Correspondingly, the power allocation value on each substream is optimized such that the average sum rate is maximized. We show that when the classical power-domain NOMA idea is incorporated into the ZF V-BLAST algorithm, the far user cannot completely cancel inter-layer interference. Nonetheless, the proposed approach turns out to yield an average sum rate performance near to that of a higher-complexity method based on maximum likelihood detection.

In massive multiple-input–multiple-output (MIMO) systems, user clustering techniques are crucial for addressing interbeam interference. These techniques become even more critical when incorporating nonorthogonal multiple access to enhance spectral efficiency and user fairness. Prior research in this area has primarily focused on channel correlation for user pairing. This article presents a novel approach for user pairing and subband allocation in a crowded downlink system that utilizes a criterion based on minimizing the condition number (CN) of channel matrices. A benchmark resource allocation technique, which is based on a rate maximization criterion and has a higher complexity but quasi-optimal performance, is also introduced. To evaluate the performance of the proposed technique in a realistic setting, experimental massive MIMO channel measurements in a dense user deployment scenario are used. Results indicate that the CN criterion leads to significantly higher throughput and fairness levels compared with the channel correlation criterion and achieves performance that is close to that obtained with rate maximization. The study is further extended to the case of multiantenna reception, where interference cancellation techniques are proposed to increase the throughput of users with low channel gains. The proposed methods outperform a well-referenced technique in the literature.