Aris S. Lalos

A survey on M2M systems for mHealth: a wireless communications perspective.

In the new era of connectivity, marked by the explosive number of wireless electronic devices and the need for smart and pervasive applications, Machine-to-Machine (M2M) communications are an emerging technology that enables the seamless device interconnection without the need of human interaction. The use of M2M technology can bring to life a wide range of mHealth applications, with considerable benefits for both patients and healthcare providers. Many technological challenges have to be met, however, to ensure the widespread adoption of mHealth solutions in the future. In this context, we aim to provide a comprehensive survey on M2M systems for mHealth applications from a wireless communication perspective. An end-to-end holistic approach is adopted, focusing on different communication aspects of the M2M architecture. Hence, we first provide a systematic review of Wireless Body Area Networks (WBANs), which constitute the enabling technology at the patients side, and then discuss end-to-end solutions that involve the design and implementation of practical mHealth applications. We close the survey by identifying challenges and open research issues, thus paving the way for future research opportunities.

An experimental helical-tubular photobioreactor for continuous production of Nannochloropsis sp.

An experimental helical-tubular photobioreactor has been designed for controlled, continuous production of Nannochloropsis sp. Its main advantages are: (1) combination of large ratio of culture volume to surface area along with the optimised light penetration depth, (2) easy control of temperature and contaminants, (3) effective spatial distribution of fresh air and CO(2), (4) better CO(2) transfer through extensive interface surface between fresh air and culture-liquid medium and (5) novel automated flow-through sensor providing continuous cell concentration monitoring. Nannochloropsis sp. population density reached maximum value under rather high temperatures and combined natural and artificial light conditions. An average daily increase of 30 x 10(6)cells ml(-1) was obtained at population densities above 350 x 10(6)cells ml(-1) allowing daily harvesting rates of at least 10% the total volume. Measured cellular density productivity data and estimated volumetric productivity range of 1.10-3.03 g l(-1)day(-1), are among the highest Nannochloropsis sp. productivities reported in the literature.

Information Exchange in Randomly Deployed Dense WSNs With Wireless Energy Harvesting Capabilities

As large-scale dense and often randomly deployed wireless sensor networks (WSNs) become widespread, local information exchange between colocated sets of nodes may play a significant role in handling the excessive traffic volume. Moreover, to account for the limited life-span of the wireless devices, harvesting the energy of the network transmissions provides significant benefits to the lifetime of such networks. In this paper, we study the performance of communication in dense networks with wireless energy harvesting (WEH)-enabled sensor nodes. In particular, we examine two different communication scenarios (direct and cooperative) for data exchange and we provide theoretical expressions for the probability of successful communication. Then, considering the importance of lifetime in WSNs, we employ state-of-the-art WEH techniques and realistic energy converters, quantifying the potential energy gains that can be achieved in the network. Our analytical derivations, which are validated by extensive Monte-Carlo simulations, highlight the importance of WEH in dense networks and identify the tradeoffs between the direct and cooperative communication scenarios.

Reliable MAC design for ambient assisted living: moving the coordination to the cloud

AAL technologies constitute a new paradigm that promises quality of life enhancements in chronic care patients and elderly people. From a communication perspective, they involve heterogeneous deployments of body and ambient sensors in complex multihop topologies. Such networks can significantly benefit from the application of cooperative schemes based on network coding, where random linear combinations of the original data packets are transmitted in order to exploit diversity. Nevertheless, network coordination is sometimes required to obtain the full potential of these schemes, especially in the presence of channel errors, requiring the design of efficient, reliable, and versatile MAC protocols. Motivated by the recent advances in cloud computing, we investigate the possibility of transferring the network coordination to the cloud while maintaining the data exchange and storage at a local data plane. Hence, we design a general framework for the development of cloudassisted protocols for AAL applications and propose a high-performance and error-resilient MAC scheme with cloud capabilities.

Frequency Domain Channel Estimation for Cooperative Communication Networks

In this correspondence, we deal with the problem of channel estimation in amplify-and-forward (AF) wideband cooperative relay-based networks. Two types of frequency domain channel estimation techniques are proposed and analyzed. First, a training based technique is presented for which an optimal pilot placement and power allocation strategy is described. Second, hybrid techniques are introduced in which both training as well as channel output correlation information is utilized for channel estimation. A theoretical performance study of the proposed algorithms is presented and closed-form expressions for the mean squared channel estimation error are provided. The presented theoretical analysis is verified via extensive Monte Carlo simulations.

WSN4QoL: A WSN-Oriented Healthcare System Architecture:

People worldwide are getting older and this fact has pushed the need for designing new, more pervasive, and possibly cost effective healthcare systems. In this field, distributed and networked embedded systems, such as wireless sensor networks (WSNs), are the most appealing technology to achieve continuous monitoring of aged people for their own safety, without affecting their daily activities. This paper proposes recent advancements in this field by introducing WSN4QoL, a Marie Curie project which involves academic and industrial partners from three EU countries. The project aims to propose new WSN-based technologies to meet the specific requirements of pervasive healthcare applications. In particular, in this paper, the system architecture is presented to cope with the challenges imposed by the specific application scenario. This includes a network coding (NC) mechanism and a distributed localization solution that have been implemented on WSN testbeds to achieve efficiency in the communications and to enable indoor people tracking. Preliminary results in a real environment show good system performance that meet our expectations.

Channel estimation techniques in amplify and forward relay networks

In this work we present efficient channel estimation algorithms for wideband amplify-and-forward (AF) based relay networks which utilize a recently proposed transmission model. It is shown that all channels in the network from the source through the relays to the destination/receiver node can be blindly estimated up to a phase ambiguities vector which contains the phases of the direct source to destination channel frequency response. Hence, by employing a small number of pilot symbols, phase ambiguities can be effectively resolved. As verified by computer simulations, the proposed methods exhibit high estimation accuracy even for a short training sequence, and outperform direct training-based channel estimation. A performance study of the proposed schemes in high SNR conditions is also presented and verified through computer simulations.

RLNC-Aided Cooperative Compressed Sensing for Energy Efficient Vital Signal Telemonitoring

Wireless body area networks (WBANs) are composed of sensors that either monitor and transmit vital signals or act as relays that forward the received data to a body node coordinator (BNC). In this paper, we introduce an energy efficient vital signal telemonitoring scheme, which exploits compressed sensing (CS) for low-complexity signal compression/reconstruction and distributed cooperation for reliable data transmission to the BNC. More specifically, we introduce a cooperative compressed sensing (CCS) approach, which increases the energy efficiency of WBANs by exploiting the benefits of random linear network coding (RLNC). We study the energy efficiency of RLNC and compare it with the store-and-forward (FW) protocol. Our mathematical analysis shows that the gain introduced by RLNC increases as the link failure rate increases, especially in practical scenarios with a limited number of relays. Furthermore, we propose a reconstruction algorithm that further enhances the benefits of RLNC by exploiting key characteristics of vital signals. With the aid of electrocardiographic (ECG) and electroencephalographic (EEG) data available in medical databases, extensive simulation results are illustrated, which validate our theoretical findings and show that the proposed recovery algorithm increases the energy efficiency of the body sensor nodes by 40% compared to conventional CS-based reconstruction methods.

Connectivity of large-scale WSNs in fading environments under different routing mechanisms

As the number of nodes in wireless sensor networks (WSNs) increases, new challenges have to be faced in order to maintain their performance. A fundamental requirement of several applications is the correct transmission of the measurements to their final destinations. Thus, it is crucial to guarantee a high probability of connectivity, which characterizes the ability of every node to report to the fusion center. This network metric is strongly affected by both the fading characteristics and the different routing protocols that are used for the dissemination of data. In this paper, we study the probability of a network to be fully connected for two widely employed routing mechanisms, namely unicast and K-anycast. The analytical derivations and the simulations evaluate the trade-offs among the different routing mechanisms and provide useful guidelines on the design of WSNs.

Cross-Layer Theoretical Analysis of NC-Aided Cooperative ARQ Protocols in Correlated Shadowed Environments

In this paper, we propose a cross-layer analytical model for the study of network coding (NC)-based Automatic Repeat reQuest (ARQ) medium access control (MAC) protocols in correlated slow-faded (shadowed) environments, where two end nodes are assisted by a cluster of relays to exchange data packets. The goal of our work is threefold: 1) to provide general physical-layer theoretical expressions for estimating crucial network parameters (i.e., network outage probability and expected size of the active relay set), applicable in two-way communications; 2) to demonstrate how these expressions are incorporated into theoretical models of the upper layers (i.e., MAC); and 3) to study the performance of a recently proposed NC-aided cooperative ARQ (NCCARQ) MAC protocol under correlated shadowing conditions. Extensive Monte Carlo experiments have been carried out to validate the efficiency of the developed analytical model and to investigate the realistic performance of NCCARQ. Our results indicate that the number of active relays is independent of the shadowing correlation in the wireless links and reveal intriguing tradeoffs between throughput and energy efficiency, highlighting the importance of cross-layer approaches for the assessment of cooperative MAC protocols.