A5036021669- Software-Defined Networks and 5G
- IoT and Edge/Fog Computing
- Direction-of-Arrival Estimation Techniques
- Indoor and Outdoor Localization Technologies
- Advanced MIMO Systems Optimization
- Energy Harvesting in Wireless Networks
- Speech and Audio Processing
- Wireless Networks and Protocols
- Smart Grid Energy Management
- Wireless Communication Networks Research
- Radar Systems and Signal Processing
- Distributed Sensor Networks and Detection Algorithms
- Cooperative Communication and Network Coding
- Smart Grid Security and Resilience
- Energy Efficient Wireless Sensor Networks
- Advanced Wireless Network Optimization
- Context-Aware Activity Recognition Systems
- IoT Networks and Protocols
- Satellite Communication Systems
- Building Energy and Comfort Optimization
- Mobile Agent-Based Network Management
- Network Security and Intrusion Detection
- Cloud Computing and Resource Management
- Bluetooth and Wireless Communication Technologies
- GNSS positioning and interference
Centre Tecnologic de Telecomunicacions de Catalunya
2011-2020
Universitat Politècnica de Catalunya
2006-2018
As industries are under pressure for shorter business and product life cycles, there is an extensive effort from the research community novel profitable automation processes. This has given rise to fifth-generation (5G) Tactile Internet, which characterized by extremely low latency communication in combination with high availability, reliability, security. In this paper, we discuss key technologies support Internet characteristics industrial environments then showcase implementation of a 5G...
Smart grid is one of the main applications Internet Things (IoT) paradigm. Within this context, paper addresses efficient energy consumption management heating, ventilation, and air conditioning (HVAC) systems in smart grids with variable price. To that end, first, we propose an scheduling method minimizes cost for a particular time interval, taking into account price set comfort constraints, is, range temperatures according to user’s preferences given room. Then, scheduler where user may...
We propose an SDN/NFV-enabled edge node for IoT Services by means of orchestration integrated Cloud/Fog and network resources. Network connectivity is provided between gateways deployed virtual machines allocated at the node.
The Internet of Things (IoT) will facilitate a wide variety applications in different domains, such as smart cities, grids, industrial automation (Industry 4.0), driving, assistance the elderly, and home automation. Billions heterogeneous devices with application requirements be connected to networks generate huge aggregated volumes data that processed distributed cloud infrastructures. On other hand, there is also general trend deploy functions software (SW) instances infrastructures [e.g.,...
Future Internet of Things (IoT) will connect to the billions heterogeneous smart devices with capacity interacting environment. Therefore, proposed solutions from an IoT networking perspective must take into account scalability nodes as well operational cost deploying infrastructure. This generate a huge volume data, which poses tremendous challenge both transport, and processing information point view. Moreover, security issues appear, due fact that untrusted are interconnected towards...
This paper evaluates the applicability of MIMO techniques to satellite networks in order achieve diversity and multiplexing gain through dual polarized antennas. In single scenarios proposed STTC OSTBC offer better BER than plain stream along each polarizations SISO transmissions. By adding a with polarization antennas performing joint distributed OSTBC, spectral efficiency increases as satellites transmit same frequency band. Finally hybrid satellite-terrestrial network has been considered...
This paper deals with Internet of Things (IoT) data analytics in a collaborative platform where computing resources are available both at the network edge and backend cloud. Thereby, requirements low-latency delay tolerant IoT applications can be met. Moreover, this faces challenging heterogeneous features data, i.e. its high dimensionality or geo-distributed streaming nature. The proposed approach relies on two pillars. On one hand, recent advances machine learning (ML) techniques leveraged...
Next generation networks, as the Internet of Things (IoT), aim to create open and global networks for connecting smart objects, network elements, applications, web services end-users. Research industry attempt integrate this evolving technology exponential growth IoT by overcoming significant hurdles such dynamicity, scalability, heterogeneity end-to-end security privacy. Motivated above, SEMIoTICS proposes development a pattern-driven framework, built upon existing platforms, enable...
Telemedicine, or the ability granted to doctors remotely assist patients has been greatly benefited by advances in IoT, network communications, Machine Learning and Edge/Cloud computing. With impeding arrival of 5G, virtualized infrastructures cloud-native approaches enable execution unprecedented procedures during such patient/doctor interactions, allowing medical professionals e.g. request higher granularity metrics from patients' telemetry equipment, perform on-demand data...
Conventional implementations of the linear minimum mean-square (LMMSE) and variance distortionless response (MVDR) estimators rely on sample matrix inversion (SMI) technique, i.e., covariance (SCM). This approach is optimal in large size regime. Nonetheless, small situations, those suffer a performance degradation. Thus, aim this paper to propose corrections these methods that counteract their degradation regime keep optimality situations. To aim, twofold proposed. First, shrinkage are...
Current IoT trends reveal an increase in computational requirements for data processing. Traditionally, from sensors was uploaded to compute nodes at a backend cloud. Nevertheless, ever-growing amount of generated by devices have rendered this option too expensive terms network traffic, possibly leading delays due bottlenecks. Moreover, even if connectivity were be guaranteed, live processing sensitive (e.g.: biomedical) remote location may not comply with protection policies. A popular...
Wireless Sensor Networks (WSN) devices are usually battery powered and thereby their lifetime is limited. This issue leads to lose data measurements thus a performance loss of the underlying WSN application. It also increases maintenance cost in Internet Things (IoT) scenarios with huge number devices. Energy harvesting (EH) one key technologies solve this issue. In paper, energy by artificial light proposed power indoor scenarios. Contrary state-of-the-art related work, paper experimentally...
We investigate optimal bias corrections in the problem of linear minimum mean square error (LMMSE) estimation a scalar parameter linearly described by set Gaussian multidimensional observations. The finding scaling class LMMSE filter implementations based on sample covariance matrix (SCM) is addressed. By applying recent results from random theory, factor minimizing (MSE) and depending both unknown its estimator firstly asymptotically analyzed terms key scenario parameters, finally estimated...
This paper deals with the problem of Heating, Ventilation and Air-Conditioning (HVAC) control optimization under dynamic pricing policies. In contrast to other appliances, HVAC system entails a more challenging since not only cost should be taken into account but also user comfort temperature. We design mechanism that firstly estimates predicts temperature considering configuration then optimizes energy assuming given electricity price policy. addition, we present technique relaxes...
This paper addresses the TOA (Time Of Arrival) estimation problem for ranging applications in wireless location systems. High resolution first arrival path detector based on MV (Minimum Variance) and NMV (Normalized Minimum can provide an accurate even high multipath scenarios when LOS (Line-Of-Sight) signal is strongly attenuated. A new estimator a polynomial rooting approach of criterion, named RMV (Root Variance), proposed this paper. Performance compared with grid search estimators RDMV...
The conventional linear minimum mean square error estimator (LMMSE) suffers a severe performance degradation whenever the sample size is comparable to observation dimension. In order tackle this problem, we propose an optimal correction of LMMSE, which minimizes average (MSE) by using moments complex inverse Wishart distribution. Numerical simulations highlight that proposed dramatically outperforms LMMSE in small regime.
Advances in virtualisation technology have reached the mobile networking domain. Network Functions Virtualisation Management and Orchestration (NFV MANO) as proposed by ETSI realised via Opensource MANO (OSM) allows sharing or partitioning a fairly generic pool of hardware into virtual compute, network storage resources among differentiated services. A direct consequence this is dramatic reduction CAPEX/OPEX, but also possibility instantaneously deploy services across one several Mobile...