A Random Access Protocol incorporating Multi-Packet Reception, Retransmission Diversity and Successive Interference Cancellation

8th International Workshop on Multiple Access Communications (MACOM2015), Helsinki, Finland.

On the Scalability of Constructive Interference in Low-Power Wireless Networks

12th European Conference on Wireless Sensor Networks (EWSN 2015). 9 to 11, Feb, 2015. Porto, Portugal

Monitorização de pesticidas em águas de Esposende

De forma a proteger o ambiente e a saúde humana, é imperativo evitar, prevenir ou reduzir as concentrações prejudiciais de poluentes nocivos na água subterrânea. A necessidade da obtenção de níveis de protecção da água subterrânea, encontra-se estabelecida em normas de qualidade e devem ser desenvolvidas metodologias que permitam a avaliação do estado químico da água subterrânea. Este trabalho experimental centrou-se no desenvolvimento de uma metodologia analítica de detecção e quantificação por cromatografia gasosa com detector de captura de electrões dos pesticidas atrazina e respectivos metabolitos (desetilatrazina e deisopropilatrazina), simazina, terbutilazina e o metabolito desetiterbutilazina, folpete, dimetoato, diazinão, malatião, cloropirifos e o azinfos-metilo em águas de poços. O estudo progressivo baseou-se na colheita de água a 20 poços agrícolas na zona de Esposende, área considerada pelo Ministério da Agricultura do Desenvolvimento Rural e Pescas como sendo uma zona vulnerável. O método utilizado para a validação da técnica cromatográfica baseou-se na norma ISO 8466-1:1990. Os parâmetros de validação considerados foram: especificidade/selectividade, capacidade de identificação, limites de detecção e quantificação, relação sinal/ruído, linearidade e curva de calibração, precisão (repetibilidade, precisão intermédia e reprodutibilidade), eficiência de extracção e arrastamento. O método demonstrou ser capaz de identificar e quantificar os analitos, sem interferência de outros compostos. Obteve-se um valor para os parâmetros da precisão inferior a 10%, enquanto os mais baixos limites de detecção e de quantificação foram, respectivamente, 0,014 e 0,047 μg L-1. Na preparação de amostras optou-se pelo método de extracção em fase sólida, tendo sido testadas cinco diferentes tipos de colunas extractivas; Lichrolut® EN/RP-18; Strata SDB-L e C18-E; Chromabond HR-P e HR-X, sendo que as colunas Lichrolut® EN/RP- 18 apresentaram melhores resultados para a globalidade dos pesticidas. Da análise efectuada aos 20 poços agrícolas verificou-se que apenas 3 não apresentavam qualquer vestígio dos pesticidas monitorizados, sendo que as restantes apresentavam valores entre 0,05 e 53,2 μg L-1, valores superiores aos impostos pela legislação em vigor (Decreto-Lei n.º 208/2008 de 28 de Outubro para água subterrânea e Decreto-Lei nº306/2007 referente a água para consumo). Verificou-se que os proprietários dos poços agrícolas, dos quais se procedeu à amostragem de água para análise não têm a consciência da falta de qualidade dessa água, nem dos malefícios que possam advir do seu consumo.

ECG denoising based on adaptive signal processing technique

An Electrocardiogram (ECG) monitoring system deals with several challenges related with noise sources. The main goal of this text was the study of Adaptive Signal Processing Algorithms for ECG noise reduction when applied to real signals. This document presents an adaptive ltering technique based on Least Mean Square (LMS) algorithm to remove the artefacts caused by electromyography (EMG) and power line noise into ECG signal. For this experiments it was used real noise signals, mainly to observe the di erence between real noise and simulated noise sources. It was obtained very good results due to the ability of noise removing that can be reached with this technique. A recolha de sinais electrocardiogr a cos (ECG) sofre de diversos problemas relacionados com ru dos. O objectivo deste trabalho foi o estudo de algoritmos adaptativos para processamento digital de sinal, para redu c~ao de ru do em sinais ECG reais. Este texto apresenta uma t ecnica de redu c~ao de ru do baseada no algoritmo Least Mean Square (LMS) para remo c~ao de ru dos causados quer pela actividade muscular (EMG) quer por ru dos causados pela rede de energia el ectrica. Para as experiencias foram utilizados ru dos reais, principalmente para aferir a diferen ca de performance do algoritmo entre os sinais reais e os simulados. Foram conseguidos bons resultados, essencialmente devido as excelentes caracter sticas que esta t ecnica tem para remover ru dos.

BANMAC: an opportunistic MAC protocol for reliable communications in body area networks

We consider reliable communications in Body Area Networks (BAN), where a set of nodes placed on human body are connected using wireless links. In order to keep the Specific Absorption Rate (SAR) as low as possible for health safety reasons, these networks operate in low transmit power regime, which however, is known to be error prone. It has been observed that the fluctuations of the Received Signal Strength (RSS) at the nodes of a BAN on a moving person show certain regularities and that the magnitude of these fluctuations are significant (5 - 20 dB). In this paper, we present BANMAC, a MAC protocol that monitors and predicts the channel fluctuations and schedules transmissions opportunistically when the RSS is likely to be higher. The MAC protocol is capable of providing differentiated service and resolves co-channel interference in the event of multiple co-located BANs in a vicinity. We report the design and implementation details of BANMAC integrated with the IEEE 802.15.4 protocol stack. We present experimental data which show that the packet loss rate (PLR) of BANMAC is significantly lower as compared to that of the IEEE 802.15.4 MAC. For comparable PLR, the power consumption of BANMAC is also significantly lower than that of the IEEE 802.15.4. For co-located networks, the convergence time to find a conflict-free channel allocation was approximately 1 s for the centralized coordination mechanism and was approximately 4 s for the distributed coordination mechanism.

Extending fixed task-priority schedulability by interference limitation

While the earliest deadline first algorithm is known to be optimal as a uniprocessor scheduling policy, the implementation comes at a cost in terms of complexity. Fixed taskpriority algorithms on the other hand have lower complexity but higher likelihood of task sets being declared unschedulable, when compared to earliest deadline first (EDF). Various attempts have been undertaken to increase the chances of proving a task set schedulable with similar low complexity. In some cases, this was achieved by modifying applications to limit preemptions, at the cost of flexibility. In this work, we explore several variants of a concept to limit interference by locking down the ready queue at certain instances. The aim is to increase the prospects of schedulability of a given task system, without compromising on complexity or flexibility, when compared to the regular fixed task-priority algorithm. As a final contribution, a new preemption threshold assignment algorithm is provided which is less complex and more straightforward than the previous method available in the literature.

JamLab: augmenting sensornet testbeds with realistic and controlled interference generation

Radio interference drastically affects the performance of sensor-net communications, leading to packet loss and reduced energy-efficiency. As an increasing number of wireless devices operates on the same ISM frequencies, there is a strong need for understanding and debugging the performance of existing sensornet protocols under interference. Doing so requires a low-cost flexible testbed infrastructure that allows the repeatable generation of a wide range of interference patterns. Unfortunately, to date, existing sensornet testbeds lack such capabilities, and do not permit to study easily the coexistence problems between devices sharing the same frequencies. This paper addresses the current lack of such an infrastructure by using off-the-shelf sensor motes to record and playback interference patterns as well as to generate customizable and repeat-able interference in real-time. We propose and develop JamLab: a low-cost infrastructure to augment existing sensornet testbeds with accurate interference generation while limiting the overhead to a simple upload of the appropriate software. We explain how we tackle the hardware limitations and get an accurate measurement and regeneration of interference, and we experimentally evaluate the accuracy of JamLab with respect to time, space, and intensity. We further use JamLab to characterize the impact of interference on sensornet MAC protocols.

Quantifying the channel quality for interference-aware wireless sensor networks

Reliability of communications is key to expand application domains for sensor networks. SinceWireless Sensor Networks (WSN) operate in the license-free Industrial Scientific and Medical (ISM) bands and hence share the spectrum with other wireless technologies, addressing interference is an important challenge. In order to minimize its effect, nodes can dynamically adapt radio resources provided information about current spectrum usage is available. We present a new channel quality metric, based on availability of the channel over time, which meaningfully quantifies spectrum usage. We discuss the optimum scanning time for capturing the channel condition while maintaining energy-efficiency. Using data collected from a number of Wi-Fi networks operating in a library building, we show that our metric has strong correlation with the Packet Reception Rate (PRR). This suggests that quantifying interference in the channel can help in adapting resources for better reliability. We present a discussion of the usage of our metric for various resource allocation and adaptation strategies.

An embedded 1149.4 extension to support mixed-signal debugging

Debugging electronic circuits is traditionally done with bench equipment directly connected to the circuit under debug. In the digital domain, the difficulties associated with the direct physical access to circuit nodes led to the inclusion of resources providing support to that activity, first at the printed circuit level, and then at the integrated circuit level. The experience acquired with those solutions led to the emergence of dedicated infrastructures for debugging cores at the system-on-chip level. However, all these developments had a small impact in the analog and mixed-signal domain, where debugging still depends, to a large extent, on direct physical access to circuit nodes. As a consequence, when analog and mixed-signal circuits are integrated as cores inside a system-on-chip, the difficulties associated with debugging increase, which cause the time-to-market and the prototype verification costs to also increase. The present work considers the IEEE1149.4 infrastructure as a means to support the debugging of mixed-signal circuits, namely to access the circuit nodes and also an embedded debug mechanism named mixed-signal condition detector, necessary for watch-/breakpoints and real-time analysis operations. One of the main advantages associated with the proposed solution is the seamless migration to the system-on-chip level, as the access is done through electronic means, thus easing debugging operations at different hierarchical levels.

SIR performance evaluation of MB-OFDM UWB system with residual timing offset

Signal-to-interference ratio (SIR) performance of a multiband orthogonal frequency division multiplexing ultra-wideband system with residual timing offset is investigated. To do so, an exact mathematical derivation of the SIR of this system is derived. It becomes obvious that, unlike a cyclic prefixing based system, a zero padding based system is sensitive to residual timing offset.

Distributed Linear Precoding and User Selection in Coordinated Multicell Systems

In this manuscript we tackle the problem of semidistributed user selection with distributed linear precoding for sum rate maximization in multiuser multicell systems. A set of adjacent base stations (BS) form a cluster in order to perform coordinated transmission to cell-edge users, and coordination is carried out through a central processing unit (CU). However, the message exchange between BSs and the CU is limited to scheduling control signaling and no user data or channel state information (CSI) exchange is allowed. In the considered multicell coordinated approach, each BS has its own set of cell-edge users and transmits only to one intended user while interference to non-intended users at other BSs is suppressed by signal steering (precoding). We use two distributed linear precoding schemes, Distributed Zero Forcing (DZF) and Distributed Virtual Signalto-Interference-plus-Noise Ratio (DVSINR). Considering multiple users per cell and the backhaul limitations, the BSs rely on local CSI to solve the user selection problem. First we investigate how the signal-to-noise-ratio (SNR) regime and the number of antennas at the BSs impact the effective channel gain (the magnitude of the channels after precoding) and its relationship with multiuser diversity. Considering that user selection must be based on the type of implemented precoding, we develop metrics of compatibility (estimations of the effective channel gains) that can be computed from local CSI at each BS and reported to the CU for scheduling decisions. Based on such metrics, we design user selection algorithms that can find a set of users that potentially maximizes the sum rate. Numerical results show the effectiveness of the proposed metrics and algorithms for different configurations of users and antennas at the base stations.

Analysis of self-interference within DAG tasks

6th Real-Time Scheduling Open Problems Seminar (RTSOPS 2015), Lund, Sweden.

Myoelectric Signal Monitoring System

The Electromyography (EMG) is an important tool for gait analyzes and disorders diagnoses. Traditional methods involve equipment that can disturb the analyses, being gradually substituted by different approaches, like wearable and wireless systems. The cable replacement for autonomous systems demands for technologies capable of meeting the power constraints. This work presents the development of an EMG and kinematic data capture wireless module, designed taking into account power consumption issues. This module captures and converts the analog myoeletric signal to digital, synchronously with the capture of kinetic information. Both data are time multiplexed and sent to a PC via Bluetooth link. The work carried out comprised the development of the hardware, the firmware and a graphical interface running in an external PC. The hardware was developed using the PIC18F14K22, a low power family of microcontrollers. The link was established via Bluetooth, a protocol designed for low power communication. An application was also developed to recover and trace the signal to a Graphic User Interface (GUI), coordinating the message exchange with the firmware. Results were obtained which allowed validating the conceived system in static and with the subject performing short movements. Although it was not possible to perform the tests within more dynamic movements, it is shown that it is possible to capture, transmit and display the captured data as expected. Some suggestions to improve the system performance also were made.

Analysis of Natural and Artificial Phenomena Using Signal Processing and Fractional Calculus

In this paper we study several natural and man-made complex phenomena in the perspective of dynamical systems. For each class of phenomena, the system outputs are time-series records obtained in identical conditions. The time-series are viewed as manifestations of the system behavior and are processed for analyzing the system dynamics. First, we use the Fourier transform to process the data and we approximate the amplitude spectra by means of power law functions. We interpret the power law parameters as a phenomenological signature of the system dynamics. Second, we adopt the techniques of non-hierarchical clustering and multidimensional scaling to visualize hidden relationships between the complex phenomena. Third, we propose a vector field based analogy to interpret the patterns unveiled by the PL parameters.

PIASA: A power and interference aware resource management strategy for heterogeneous workloads in cloud data centers

Cloud data centers have been progressively adopted in different scenarios, as reflected in the execution of heterogeneous applications with diverse workloads and diverse quality of service (QoS) requirements. Virtual machine (VM) technology eases resource management in physical servers and helps cloud providers achieve goals such as optimization of energy consumption. However, the performance of an application running inside a VM is not guaranteed due to the interference among co-hosted workloads sharing the same physical resources. Moreover, the different types of co-hosted applications with diverse QoS requirements as well as the dynamic behavior of the cloud makes efficient provisioning of resources even more difficult and a challenging problem in cloud data centers. In this paper, we address the problem of resource allocation within a data center that runs different types of application workloads, particularly CPU- and network-intensive applications. To address these challenges, we propose an interference- and power-aware management mechanism that combines a performance deviation estimator and a scheduling algorithm to guide the resource allocation in virtualized environments. We conduct simulations by injecting synthetic workloads whose characteristics follow the last version of the Google Cloud tracelogs. The results indicate that our performance-enforcing strategy is able to fulfill contracted SLAs of real-world environments while reducing energy costs by as much as 21%.