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Within the most recent years, most of the cancer patients are older age, which implies the necessity to a better understanding of aging and cancer connection. This work presents the LifeChamps solution built on top of cutting-edge Big Data architecture and HPC infrastructure concepts. An innovative architecture was envisioned supported by the Big Data Value Reference Model and answering the system requirements from high to low level and from logical to physical perspective, following the "4+1 architectural model".

POCI-01-0145-FEDER-030433 LISBOA-01-0145-FEDER-0307095 This work presents an innovative methodology to predict the future trajectories of vehicles when its current and previous locations are known. We propose an algorithm to adapt the vehicles trajectories' data based on consecutive GPS locations and to construct a statistical inference module that can be used online for mobility prediction. The inference module is based on a hidden Markov model (HMM), where each trajectory is modeled as a subset of consecutive locations. The prediction stage uses the statistical information inferred so far and is based on the Viterbi algorithm, which identifies the subset of consecutive locations (hidden information) with the maximum likelihood when a prior subset of locations are known (observations). By analyzing the disadvantages of using the Viterbi algorithm (TDVIT) when the number of hidden states increases, we propose an enhanced algorithm (OPTVIT), which decreases the prediction computation time. Offline analysis of vehicle mobility is conducted through the evaluation of a dataset containing real traces of 442 taxis running in the city of Porto, Portugal, during a full year. Experimental results obtained with the dataset show that the prediction process is improved when more information about prior vehicle mobility is available. Moreover, the computation time of the prediction process is significantly improved when OPTVIT is adopted and approximately 90% of prediction performance can be achieved, showing the effectiveness of the proposed method for vehicle trajectory prediction. publishersversion published

In this letter, the problem of coexistence interference caused by multiple networks operating in the same band is considered. Specifically, two different methods to characterize the aggregate interference caused to a receiver when the interferers belong to different coexisting networks are presented. While the first method is inspired on the interference distribution in homogeneous Poisson point process (PPP) networks, the second method proposes a highly precise approximation based on the $\alpha $ - $\mu $ distribution. Both methods are described and their accuracies are assessed through simulations, showing that the adoption of the second approach can effectively increase the accuracy of the interference power distribution in coexisting scenarios.

Funding Information: This work was funded by Fundac¸ão para a Ciência e Tecnologia, under the projects InfoCent-IoT (PTDC/EEI-TEL/30433/2017), CoSHARE (PTDC/EEI-TEL/30709/2017), and Grant UIDB/50008/2020. This work presents an effective tool to predict the future trajectories of vehicles when its current and previous locations are known. We propose a Long Short-Term Memory (LSTM) Recurrent Neural Network (RNN) prediction scheme due to its adequacy to learn from sequential data. To fully learn the vehicles' mobility patterns, during the training process we use a dataset that contains real traces of 442 taxis running in the city of Porto, Portugal, during a full year. From experimental results, we observe that the prediction process is improved when more information about prior vehicle mobility is available. Moreover, the computation time is evaluated for a distinct number of prior locations considered in the prediction process. The results exhibit a prediction performance higher than 89%, showing the effectiveness of the proposed LSTM network. authorsversion published

InfoCent-IoT (POCI-01-0145- FEDER-030433). In this paper, we present a novel method to estimate the distribution of the residual self-interference (SI) power of an in-band Full-duplex (IBFDX) system. Considering the residual SI distribution caused by the uncanceled SI in a post-mixer scheme due to a single propagation tap, we propose a framework capable of estimating the residual SI distribution. The estimator relies on the computation of two estimated parameters, which takes advantage of using the method of moments of the residual SI distribution in a straightforward manner. Additionally, we assess the accuracy of the proposed estimators, considering different sample set lengths adopted in the estimation process. The results testify the quality of the estimation method and its ability to achieve high accuracy, even for a reduced number of samples. This work is of practical importance, particularly when the residual self-interference is mainly due to a line-of-sight component, where the proposed technique can use a small set of samples to predict the residual interference in an accurate way. published

In this paper, we characterize the wireless interference of a mobile ad hoc network, where the nodes move according to the random waypoint model. The interferers are assumed to be located within an interference region that is defined as a circular region centered in a fixed node located at a given point of the mobility scenario. The main contribution of this paper is the characterization of the aggregate interference caused to the fixed node by mobile interferers located within the interference region. The distribution of the interference is analyzed taking into account the stochastic nature of the path loss due to the mobility of the nodes, as well as fast fading and shadowing effects. The derivation of the characteristic function of the aggregate interference is used in two different estimators, which successfully characterize the interference using only a small set of samples. The theoretical approach is validated through simulations, which confirm its effectiveness. Finally, we assess the accuracy of the proposed estimators, demonstrating the practical value of this paper.

In this paper, the problem of coexistence interference caused by unlicensed networks is addressed. An analytical framework is developed to characterize the aggregate interference caused to a fixed licensed user when the coexisting interferers belong to different unlicensed networks. The distribution of the interference is analyzed considering the stochastic nature of the path loss, as well as fast fading and shadowing effects. The unlicensed users are deployed according to a homogeneous Poisson Process, and it is shown that the distribution of aggregate interference can be approximated by an $\alpha$-μ distribution. Our results show the impact of node densities, transmitted power levels, and access channel probabilities on the distribution of the aggregate interference. Numerical and simulated results are compared to assess the accuracy of the proposed analysis.

In this letter, we investigate the impact of wireless-powered communications when energy is harvested from multiple static and/or mobile wireless coexisting networks.In a first step, we characterize the aggregate power received by a harvester node when it harnesses the energy generated by the coexisting wireless networks. Considering that the harvester node acts as a transmitter after the harvesting duration, we derive the outage probability for such coexisting scenario. In addition, the throughput achieved by the harvester node is also characterized, and the optimal harvesting duration is identified taking into account the mobility of the coexisting networks, the features of the static networks, the energy harvesting process, as well as the communication performance between the harvester node and the receiver. Our work shows that the distribution of the power received by the harvester from the coexisting networks can be accurately approximated by an $\alpha-\mu$ distribution. Moreover, the mobility also impacts on the optimal throughput of the wireless-powered communications, which is accurately confirmed by the proposed analysis and extensive simulations.

Full-duplex wireless communication systems are capable of transmitting and receiving signals in the same band. An important performance indicator of full-duplex systems is the amount of uncanceled self-interference, a.k.a. residual self-interference. This work investigates the distribution of the residual self-interference (SI) power in an analog post-mixer canceler. First, we focus on the impact of the SI channel coherence time on the distribution of the residual SI power and we analyze in detail the impact of the phase-noise caused by the up/down-conversion oscillators. The results achieved in this study confirm that the coherence time of the SI channel strongly impacts the distribution of the residual SI power. Considering a SI Rayleigh channel, we show that the residual SI power only follows a Gamma distribution in the limit case, when the coherence time tends to infinity (time-invariant channel). This work is the first step to understand the stochastic properties of the residual SI power, which is an important feature when digital-domain cancellation is jointly adopted with analog-domain cancellation to account for the estimated effects of the propagation channel.

This paper assesses the influence of the phase noise on the Bit Error Rate (BER) performance of wireless communications systems. The phase-noise distribution is characterized for different types of oscillators. The influence of the phase-noise is then evaluated considering an Orthogonal Frequency Division Multiplexing (OFDM) wireless communication system and different modulation constellations. The main conclusions of this work are based on simulation results, obtained through the simulation of the OFDM wireless communication system in the time-domain.

This work evaluates the secondary users’ (SUs) transmission capability considering that the primary users (PUs) can move to different positions. The transmission capability identifies the available opportunities for SU’s transmission. No opportunities are available when mobile PUs are active within the SU’s sensing region. We also consider the scenario when the PUs are undesirable detected active when they are not located within the SUs’ sensing region. Our analysis indicate that the transmission capability increases as the average mobility of the PUs decreases, which is confirmed by simulation.

In this work, we characterize the wireless interference of a mobile ad hoc network, where the nodes move according to the Random Waypoint model. The interferers are assumed to be located within an interference region, which is defined as a circular region centered in a fixed node located in the center of the mobility scenario. The main contribution of this letter is the characterization of the aggregate interference caused to the fixed node by the mobile interferers located within the interference region. The distribution of the interference is analyzed taking into account the stochastic nature of the path loss due to the mobility of the nodes. The theoretical approach is validated through simulations, which confirm its effectiveness.

This work was partially supported by the Portuguese Science and Technology Foundation (FCT/MEC) under the grant SFRH/BD/108525/2015. It is well known that the stochastic nature of the interference deeply impacts the performance of emerging and future wireless communication systems. In this work we consider an ad hoc network where the nodes move according to the Random Waypoint mobility model. Assuming a timevarying wireless channel due to slow and fast fading and, considering the dynamic path loss due to the mobility of the nodes, we start by characterizing the interference distribution caused to a receiver by the moving interferers located in a ring. For this purpose, we consider a receiver located at the center of the simulated region. Based on the distribution of the interference's power, we evaluate different methodologies to estimate the power of the interference in real-time. Results achieved with a Maximum Log-likelihood estimator (MLE) and a Probability Weighted Moments (PWM) estimator are compared. The accuracy of the results achieved with the proposed methodologies in several simulations show that they may used as an effective tool of interference power estimation in future wireless communication systems, exhibiting high accuracy even when the number of samples is low. publishersversion published

Radio spectrum sensing (SS) has been an active topic of research over the past years due to its importance to cognitive radio (CR) systems. However, in CR networks (CRNs) with multiple primary users (PUs), the secondary users (SUs) can often detect PUs that are located outside the sensing range, due to the level of the aggregated interference caused by the PUs. This effect, known as spatial false alarm (SFA), degrades the performance of CRNs because it decreases the SUs' medium access probability. This paper characterizes the SFA effect in a CRN, identifying possible actions to attenuate it. Adopting energy-based sensing (EBS) in each SU, this paper starts to characterize the interference caused by multiple PUs located outside a desired sensing region. The interference formulation is then used to write the probabilities of detection and false alarm, and closed-form expressions are presented and validated through simulation. The first remark to be made is that the SFA can be neglected, depending on the path-loss factor and the number of samples collected by the energy detector to decide the spectrum's occupancy state. However, it is shown that by increasing the number of samples needed to increase the sensing accuracy, the SUs may degrade their throughput, namely, if SUs are equipped with a single radio that is sequentially used for sensing and transmission (split-phase operation). Assuming this scenario, this paper ends by providing a bound for the maximum throughput achieved in a CRN with multiple active PUs and for a given level of PUs' detection inside the SUs' sensing region. The results presented in this paper show the impact of path loss and EBS parameterization on SUs' throughput and are particularly useful to guide the design and parameterization of multihop CRNs, including future ad hoc CRNs considering multiple PUs.

Femtocells were proposed as a solution to improve the performance in dense networks. They complement the macro base stations (eNB) with a dense set of low power micro base stations (HeNB). However, they also bring increased interference problems and consequently more collisions and lost packets. This paper considers the use of femtocells running the Single Carrier with Frequency Domain Equalization (SC-FDE) transmission technique. It evaluates the performance of an Iterative Block Decision-Feedback Equalizer (IB-DFE) receiver employing Interference Cancellation (IC) techniques in the downlink channel. Using the interference cancellation capability, it is possible to dynamically adjust the network deployment and reduce the network total energy consumption. This paper also proposes a HeNB control algorithm and evaluates the energy saving capabilities of the reception technique for different load levels. Results show that it is possible to turn off femtocells and still satisfy the user's requirements, with significant energy saving.

Within the most recent years, most of the cancer patients are older age, which implies the necessity to a better understanding of aging and cancer connection. This work presents the LifeChamps solution built on top of cutting-edge Big Data architecture and HPC infrastructure concepts. An innovative architecture was envisioned supported by the Big Data Value Reference Model and answering the system requirements from high to low level and from logical to physical perspective, following the “4+1 architectural model”.