Analysis and Evaluation of Pattern Division Multiple Access Scheme Jointed With 5G Waveforms

Nonorthogonal multiple access (NOMA) techniques represent a key feature for 5G systems in order to increase multiple users' systems' capacity. In particular, we propose, for study, a pattern division multiple access (PDMA) technique, which denes a pattern matrix used for mapping the users to a group of resource elements that might be shared by multiple users. The contribution of this paper is the analysis of the performances, in terms of bit error rate (BER), of 5G candidate waveforms, such as orthogonal frequency division multiplexing (OFDM), lter bank multi-carrier (FBMC), and generalized frequency division multiplexing (GFDM), in the PDMA scheme. Regarding the detection of different users' data, the successive interference cancellation algorithm is performed at the receiver side. The simulation results, consolidated by the analytic study, exhibit that OFDM and FBMC could be used in the NOMA context, while the BER related to GFDM is very high

WBAN Off-Body Channel Angular Structure Comparison between SAGE Estimation and Ray Tracing Simulation

International audienceIn this paper, we present a comparison between Off-Body channel characteristics estimated with Space-Alternating Generalized Expectation-Maximization (SAGE) algorithm from measurement data and those obtained from ray-tracing simulated data. Measurement data were obtained considering a body-worn antenna on a phantom and an external one simulating an access point. The chosen simulation approach takes into account the influence of the body directly into the antenna radiation pattern, and not by including a dedicated body representation into the simulated environment. This simplified approach provides a good agreement between simulation and measurement in terms of received power and Angle of Arrival retrieval

5G-SMART D1.5 Evaluation of radio network deployment options

This deliverable results from the work on the radio network performance analysis of the identified use cases and deployment options. Covered topics include latency reduction and mobility features of the 5G NR itself, as well as detailed analysis of the radio network KPIs, such as latency, reliability, throughput, spectral efficiency and capacity. Corresponding trade-offs for the identified deployment options and industrial use cases are quantified with an extensive set of technical results. Also, this deliverable is looking into co-channel coexistence performance analyzed through a real-life measurement campaign and considers performance optimization in presence of a special micro-exclusion zone within a factory.Comment: Deliverable D1.5 of the project 5G For Smart Manufacturing (5G-SMART

Contribution à la simulation déterministe du canal Body area network dans le contexte de la navigation du groupe et analyse du mouvement du corps

Les progrès récents dans les technologies et les systèmes de communications sans fil soutenus par la miniaturisation de dispositifs ont donné naissance une nouvelle génération de réseaux personnels permettant des communications autour du corps humain: les réseaux corporels. Cette thèse étudie les différents types du canal de propagation des réseaux corporels en environnement intérieur dans le contexte de l’analyse du mouvement et de la navigation de groupe. Dans ce travail, une approche de simulation pour le cala de propagation est présenté. Le simulateur de canal de propagation est basé sur les techniques de tracé de rayons et l’approche de simulation est basée sur l’utilisation d’antennes perturbées et l’utilisation des données de capture de mouvement pour la modélisation de la mobilité humaine. Premièrement, nous étudions la question de l’antenne et l’influence de la proximité du corps humain sur diagramme de rayonnement de l’antenne. En outre, un modèle simple utilisé pour prédire le diagramme de rayonnement d’une antenne placée à proximité d’un corps humain. Deuxièmement, le simulateur physique est présenté et l’approche de simulation est introduite. Afin de vérifier l’approche proposée, des simulations préliminaires ont été effectuées et une première comparaison avec des donnes de mesures disponibles est faite. Enfin, une campagne de mesure spécifique joignant les données radio et les données de capture de mouvement a été exploitée pour valider et évaluer les résultats de la simulation.Recent advances in wireless technologies and system, empowered by the miniaturization of devices, give rise to a new generation of Personal Area Networks allowing communications around the human body : Body Area networks. This thesis studies the Body Area Network channels in indoor environment in the context of motion analysis and group navigation. In this work a simulation approach for BAN channels is presented. The propagation channel simulator is based on ray tracing and the simulation approach is based on using perturbed antennas and the use of motion capture data for modelling the human mobility. Firstly, we investigate the antenna issue and the influence of the human body prox- imity on antenna radiation pattern. Besides, a simple model used to predict the antenna radiation pattern placed in proximity to a human body. Secondly, the physical sim- ulator is presented and the simulation approach is introduced. In order to check the proposed approach, preliminary simulations were carried out and a first comparison with available measurement data is made. Finally, a specific measurement campaign jointing radio data and motion capture data was exploited to validate and evaluate the simulation results

AI-based prediction for Ultra Reliable Low Latency service performance in industrial environments

This article investigates the usage of Artificial Intelligence (AI) techniques in the prediction of network performance for Industrial Internet of Things (IIoT). In industrial environments, 5G Ultra Reliable Low Latency Communications (URLLC) are intended for serving critical services with very stringent latency requirements, such as those involving collaborative robots. Even if the flexible 5G New Radio (NR) design is able to achieve the target IIoT performances, the necessary spectrum resources need to be available and reserved for URLLC. A Quality of Service (QoS) prediction scheme is thus needed for anticipating performance degradation and undertake necessary actions, such as network resource provisioning or application adaptation, e.g. by entering an adapted mode. We explore the design of AI algorithms for QoS prediction in industrial environments, and compare different tools for regression and classification, including Neural Networks (NN) and K Nearest Neighbors (K-NN). We explore prediction based on Signal to Interference and Noise Ratio (SINR), or simply based on the position of robots within the plant. As the latency degradation event is rare in general, we observe that the training data is highly imbalanced leading to a low prediction accuracy. We show how the prediction performance can be enhanced by importance sampling techniques and by a modified detection threshold in what we call M-KNN scheme

Comparison of vector and Scalar Spherical Harmonics expansions of UWB antenna patterns

International audienc

Comparison of vector and Scalar Spherical Harmonics expansions of UWB antenna patterns

International audienc

Constrained LMDS technique for human motion and gesture estimation

International audienceBody Area Networks is an emerging domain taking a big interest from developers and system designers. On the other hand, the need to localize is becoming necessary in diverse applications. Within this context, the aim of this paper is to estimate the different gestures and motions of the human body. Initially, we use information, about human motion, extracted from C3D files. In fact, these files provide us with the exact 3D coordinates of the sensors on a moving body. In a second step the IEEE 802.15.6 channel model is used to estimate the distances between sensors which are the input of the locomotion technique based on Multidimensional Scaling. Basically, this technique did not present satisfying results, that's why we have improved our results by an SVD reconstruction algorithm and by adding distance constraints

Optimal random packet replication policies for IIoT in 5G and Beyond considering different feedback regimes

In the context of Industrial Internet of Thing (IIoT) applications, network administrators must use their availablebandwidth to both identify best 5G NR (New Radio) configuration and best transmission schemes. In this paper we derive optimal channel access and packet replication schemes for Ultra Reliable Low Latency Communications (URLLC) traffic in 5G and Beyond networks. Based on typical system configurations, we identify three main regimes, characterized by the delay and the consequent presence or absence of feedback received from the network. In particular, we identify (a) extreme situations where there is only one time slot opportunity for packet transmission with possible replications in the frequency dimension, (b) blind repeated replication with several transmission slots opportunities, with no received ACK before the delay expiration, and (c) far-sighted scenarios where, additionally, some ACKs may be received, acknowledging older replicas of the packet. We propose adapted replication models for each radio scenario and develop corresponding mathematical models from which the transmission schemes may be optimized. The proposed policies are semi-distributed, in the sense that the optimal policy is communicated to each device by the network, that then applies it autonomously in order to respect the stringent timing constraints of URLLC. We then show the corresponding system dimensioning for achieving the target reliability and identify the best NR configurations to be deployed in the controlled industrial environments

3D UTD Modeling of a Measured Antenna Disturbed by a Dielectric Circular Cylinder in WBAN Context

International audienceThis paper describes a work realized for On-Body antennas characterization: the 3D deterministic modeling of a measured antenna disturbed by a dielectric circular cylinder of finite length. This prediction model is based on the ray-tracing technique for the electromagnetic wave paths search and the Uniform Theory of Diffraction (UTD) for the modeling of the electromagnetic waves interactions with the cylinder. After a detailed description, the model is validated in 3D with measurements made for an antenna disturbed by a cylindrical phantom [1]. Indeed, the presented model gives results very close to these measurements. These first validations allow the presented model to be implemented into more complex WBAN (Wireless Body Area Networks) propagation models