An adaptive hidden Markov model for indoor OFDM based wireless systems, Journal of Telecommunications and Information Technology, 2004, nr 2

Detailed physical layer simulation of orthogonal frequency division multiplexing (OFDM) systems requires programs that execute too slowly due to long coherence time of the indoor mobile channel. Evaluation of higher layers of such systems is simplified if suitable models for reproduction of channel errors statistics are available. An adaptive hidden Markov model (HMM) for indoor OFDM based systems that accurately reproduces error statistics of the real system with less computational effort than the exact simulation is presented in this paper. The standard HMM methodology has been modified in order to reproduce the periodicity in the error positions of the OFDM systems. The proposed model is validated by comparison of three statistical parameters: number of errors, length of the errors run and length of the error-free intervals in a frame of bits

Ubiquitous robust communications for emergency response using multi-operator heterogeneous networks

A number of disasters in various places of the planet have caused an extensive loss of lives, severe damages to properties and the environment, as well as a tremendous shock to the survivors. For relief and mitigation operations, emergency responders are immediately dispatched to the disaster areas. Ubiquitous and robust communications during the emergency response operations are of paramount importance. Nevertheless, various reports have highlighted that after many devastating events, the current technologies used, failed to support the mission critical communications, resulting in further loss of lives. Inefficiencies of the current communications used for emergency response include lack of technology inter-operability between different jurisdictions, and high vulnerability due to their centralized infrastructure. In this article, we propose a flexible network architecture that provides a common networking platform for heterogeneous multi-operator networks, for interoperation in case of emergencies. A wireless mesh network is the main part of the proposed architecture and this provides a back-up network in case of emergencies. We first describe the shortcomings and limitations of the current technologies, and then we address issues related to the applications and functionalities a future emergency response network should support. Furthermore, we describe the necessary requirements for a flexible, secure, robust, and QoS-aware emergency response multi-operator architecture, and then we suggest several schemes that can be adopted by our proposed architecture to meet those requirements. In addition, we suggest several methods for the re-tasking of communication means owned by independent individuals to provide support during emergencies. In order to investigate the feasibility of multimedia transmission over a wireless mesh network, we measured the performance of a video streaming application in a real wireless metropolitan multi-radio mesh network, showing that the mesh network can meet the requirements for high quality video transmissions

Power demand control scenarios for smart grid applications with finite number of appliances

In this paper we propose novel and more realistic analytical models for the determination of the peak demand under four power demand control scenarios. Each scenario considers a finite number of appliances installed in a residential area, with diverse power demands and different arrival rates of power requests. We develop recursive formulas for the efficient calculation of the peak demand under each scenario, which take into account the finite population of the appliances. Moreover, we associate each scenario with a proper real-time pricing process in order to derive the social welfare. The proposed analysis is validated through simulations. Moreover, the performance evaluation of the proposed formulas reveals that the absence of the assumption of finite number of appliances could lead to serious peak-demand over-estimations.This work has been funded by the E2SG project, an ENIAC Joint Undertaking under grant agreement No. 296131 and by the project AGAUR (2014SGR 1551).Scopu

Scheduling policies for two-state smart-home appliances in dynamic electricity pricing environments

In this paper we present and analyze online and offline scheduling models for the determination of the maximum power consumption in a smart grid environment. The proposed load models consider that each consumer's residence is equipped with a certain number of appliances of different power demands and different operational times, while the appliances' feature of alternating between ON and OFF states is also incorporated. Each load model is correlated with a scheduling policy that aims to the reduction of the power consumption through the compression of power demands or the postponement of power requests. Furthermore, we associate each load model with a proper dynamic pricing process in order to provide consumers with incentives to contribute to the overall power consumption reduction. The evaluation of the load models through simulation reveals the consistency and the accuracy of the proposed analysis.E2SG project, an ENIAC Joint Undertaking under grant agreement No. 296131 and Smart-NRG, No. 612254.Scopu

Analysis and quality of service evaluation of a fast charging station for electric vehicles

Electrification of transportation is considered as one of the most promising ways to mitigate climate change and reduce national security risks from oil and gasoline imports. Fast charging stations that provide high quality of service will facilitate the wide market penetration of electric vehicles. In this paper, the operation of a fast charging station is analyzed by employing a novel queuing model. The proposed analysis considers that the various electric vehicle models are classified by their battery size, and computes the customers' mean waiting time in the queue by taking into account the available charging spots, as well as the stochastic arrival process and the stochastic recharging needs of the various electric vehicle classes. Furthermore, a charging strategy is proposed according to which the drivers are motivated to limit their energy demands. The implementation of the proposed strategy allows the charging station to serve more customers without any increase in the queue waiting time. The high precision of the present analytical model is confirmed through simulations. Therefore, it may be utilized by existing fast charging station operators that need to provide high quality of service, or by future investors that need to design an efficient installation.This work has been funded by the FP7-PEOPLE-2013-IAPP-COMANDER project (Contract No. 612257 ).Scopu

An Energy Efficient Protocol Architecture for m–Health Systems

International audienc

Converged Wireless Networking and Optimization for Next Generation Services

The Next Generation Network (NGN) vision is tending towards the convergence of internet and mobile services providing the impetus for new market opportunities in combining the appealing services of internet with the roaming capability of mobile networks. However, this convergence does not go far enough, and with the emergence of new coexistence scenarios, there is a clear need to evolve the current architecture to provide cost-effective end-to-end communication. The LOOP project, a EUREKA-CELTIC driven initiative, is one piece in the jigsaw by helping European industry to sustain a leading role in telecommunications and manufacturing of high-value products and machinery by delivering pioneering converged wireless networking solutions that can be successfully demonstrated. This paper provides an overview of the LOOP project and the key achievements that have been tunneled into first prototypes for showcasing next generation services for operators and process manufacturers