A Survey Study of the Current Challenges and Opportunities of Deploying the ECG Biometric Authentication Method in IoT and 5G Environments

The environment prototype of the Internet of Things (IoT) has opened the horizon for researchers to utilize such environments in deploying useful new techniques and methods in different fields and areas. The deployment process takes place when numerous IoT devices are utilized in the implementation phase for new techniques and methods. With the wide use of IoT devices in our daily lives in many fields, personal identification is becoming increasingly important for our society. This survey aims to demonstrate various aspects related to the implementation of biometric authentication in healthcare monitoring systems based on acquiring vital ECG signals via designated wearable devices that are compatible with 5G technology. The nature of ECG signals and current ongoing research related to ECG authentication are investigated in this survey along with the factors that may affect the signal acquisition process. In addition, the survey addresses the psycho-physiological factors that pose a challenge to the usage of ECG signals as a biometric trait in biometric authentication systems along with other challenges that must be addressed and resolved in any future related research.

Mécanismes de réduction de la consommation d'énergie dans les réseaux mobiles

La consommation en énergie des réseaux de télécommunications a suscité un intérêt grandissant au cours des dernières années et les opérateurs mobiles cherchent des solutions innovantes pour optimiser l’efficacité énergétique. Dans cette thèse, nous nous focaliserons sur les schémas d’optimisation de la consommation d’énergie des réseaux d’accès mobiles. Nous commençons par étudier la stratégie de partage de charge qui minimise la consommation d’énergie dans la cellule tout en limitant l’impact sur la Qualité de Service. Le gain obtenu par ces algorithmes de gestion des ressources radio reste cependant limité; ceci est dû au fait que la consommation d’énergie ne dépend pas que de la charge, mais comporte une importante partie constante. Pour obtenir un gain plus important, nous proposons la mise en veille de certaines ressources du réseaux aux heures creuses où le trafic est faible, ce qui mène à des gains substantiels. Nous proposons ensuite un contrôleur de gestion de la mise en veille qui choisit l’action optimale en fonction de l’état du réseau. En effet, l’activation d’une nouvelle ressource n’est pas instantanée et un effet ping-pong peut apparaitre suite aux commandes simultanées d’activation/désactivation des ressources. Nous adaptons nos contrôleurs afin de prendre en compte ces imperfections, et nous montrons comment déduire la politique optimale. Nous étudions ensuite le cas de déploiement de petites cellules dans des réseaux hétérogènes et montrons que leur efficacité énergétique est améliorée par rapport au réseau purement macro-cellulaire, pourvu que la consommation d’énergie de petites cellules reste faible. Nous proposons ensuite un contrôleur optimal qui active/désactive les petites cellules en se basant sur des informations de trafic et de localisation des usagers. Nous considérons différents cas de figure avec une information complète, partielle ou retardée et montrons que ces schémas de mise en veille permettent d’atteindre d’importants gains de consommation d’énergieIn the recent years, more importance has been given to the energy consumption issue in telecommunication networks and mobile operators are rethinking their network design for optimizing its energy efficiency. In this thesis, we propose schemes for optimizing the energy consumption of mobile access networks. We begin by proposing energy-aware Radio Resource Management (RRM) schemes and show that a load balancing between available resources gives some energy savings. However, these gains remain small as a large part of the energy consumption is load-independent. We thus propose sleep mode schemes of resources in the network (cells or carriers) and show that they give a large gain when traffic is low. We then propose optimal sleep mode controllers that give, for each traffic scenario, the best actions to take in each state of the network. We make two observations: the first is that activating a new resource is not instantaneous, leading to QoS degradation if a conservative policy is not considered, and the second is that a ping-pong effect may appear at the frontier between two capacity regions. We adapt our controllers to take into account these imperfections, and show how to derive the optimal policy using Markov decision theory. We then extend our works to the case of small cell deployment in heterogeneous networks, composed of macro and small cells base stations. We study the capacity and power consumption of these networks and show that the energy efficiency is increased for some deployment strategies when the power consumption of small cells is low. We then propose sleep mode for small cells and develop optimal sleep/wakeup schemes based on the information on traffic load and user localization in the cell, in the cases where this information is complete, partial or delayed. We show that these sleep mode schemes achieve large energy consumption gain

Minimizing energy consumption via sleep mode in green base station

International audienceIn this paper, we develop new energy-efficient, radio resource management schemes for green wireless networks. Our goal is to optimize energy consumption at the network scale while preserving the Quality of Service (QoS) perceived by users. We specifically propose two new sleep mechanisms for base station where a number of resources in system can be shut down for some traffic scenarios in one of two ways: a dynamic way where resources are activated/deactivated in real-time as a function of the instantaneous load of the system, and a semi-static one where resources are kept unchanged during longer time intervals, in the order of one hour. We apply the proposed schemes to 2G and HSPA (High Speed Packet Access) systems and show that the dynamic one achieves larger energy reductions while the semistatic one has an acceptable performance with low complexit

How femtocells impact the capacity and the energy efficiency of LTE-Advanced networks

International audienceIn this paper, we show the impact of femtocells deployment on the capacity of LTE-Advanced networks. We analyze the Erlang-like capacity of a network composed of macro networks only and study the impact of introducing femtocells. We study the ability of open and closed access femtocells to offload traffic from the macro network and draw the capacity gains that are expected from this offload. Knowing that femtocells are not managed by the operator, but installed by clients, we take into account the random nature of the resulting deployment in the capacity analysis. Our results quantify the gains thus achieved, in terms of user QoS and cell load, as well as energy efficiency, as compared to a pure macro networ

Optimal control for base station sleep mode in energy efficient radio access networks

International audienceIn this paper, we investigate network sleep mode for reducing energy consumption of radio access networks. We propose an offline-optimized controller that associates to each traffic an activation/deactivation policy that maximizes a multiple objective function of the Quality of Service (QoS) and the energy consumption. We focus on practical implementation issues that may affect the QoS and the stability of the system. We namely consider the activation time issue that results in the degradation of the throughput and the ping-pong effect that results in unnecessary ON/OFF oscillations. We illustrate our results numerically in beyond 3G network

Optimal control of wake up mechanisms of femtocells in heterogeneous networks

International audienceWe study, in this work, optimal sleep/wake up schemes for the base stations of network-operated femto cells deployed within macro cells for the purpose of offloading part of its traffic. Our aim is to minimize the energy consumption of the overall heterogeneous network while preserving the Quality of Service (QoS) experienced by users. We model such a system at the flow level, considering a dynamic user configuration, and derive, using Markov Decision Processes (MDPs), optimal sleep/wake up schemes based on the information on traffic load and user localization in the cell, in the cases where this information is complete, partial or delayed. Our results quantify the energy consumption and QoS perceived by the users in each of these cases and identify the tradeoffs between those two quantities. We also illustrate numerically the optimal policies in different traffic scenario

Capacity and energy efficiency of picocell deployment in LTE-A networks

International audienceIn this paper, we show the impact of deploying picocells on the capacity and energy efficiency of LTE-A networks. We analyze the Erlang-like capacity of a network composed of macro networks only and study the impact of introducing a number of picocells per site. Knowing that the capacity is not the only factor that will drive the evolution of the network, we also consider the energy efficiency as a Key Performance Indicator (KPI). Our results show that, in some scenarios, introducing picocells is a good network densification method as they achieve a higher network capacity with good energy efficienc

Realistic Energy Saving Potential of Sleep Mode for Existing and Future Mobile Networks

Abstract—This paper presents an extensive overview on an energy saving feature referred to as ‘site sleep mode’, designed for existing and future mobile broadband networks. In addition to providing a detailed understanding of the main concept, the paper also provides various studies and results to highlight potential savings, and emphasize some of the expected limitations. Since site measurements show that the energy consumption of base station sites is largely load-independent, this makes such a feature highly effective for reducing the energy consumption of mobile networks during hours of low traffic. After going through a number of different alternatives of the feature, this is applied to different network topologies, macro-only based networks, and a set of heterogeneous networks that employ the use of small cells in traffic hotspots. Results obtained through detailed case studies show that sleep mode can reduce the average daily energy consumption of a network by around 30%. This can be achieved while maintaining a predefined level of performance, used as a measure of comparing different scenarios. Index Terms—sleep mode, energy efficiency, case study, HSPA, LTE, base station, energy model, power model, heterogeneous network, femtocells, picocells I

Optimal online control for sleep mode in green base stations

International audienceIn this paper, we investigate network sleep mode schemes for reducing energy consumption of radio access networks. We first propose, using Markov Decision Processes (MDPs), an optimal controller that associates to each traffic an activation/deactivation policy that maximizes a multiple objective function of the Quality of Service (QoS) and the energy consumption. We focus on a practical implementation issue, namely ping-pong effect resulting in unnecessary ON/OFF oscillations, that may affect the stability of the system. We illustrate our results numerically using theoretical models of the radio access network, and apply the developed mechanisms on a large-scale network simulator. Knowing that an offline optimization is not suitable for a large-scale network nor does it fit all traffic configurations, we propose, using an online controller that derives dynamically the optimal policy based on the dynamics of users in the cell. The design of our online controller is based on a simple ∊-greedy algorithm and learns the optimal threshold policy for activation/deactivation of network resources