Farshad Lahouti

University of Guilan, Resht, Gīlān, Iran

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Publications (101)73.24 Total impact

  • Source
    Amin Azari, Jalil Seifali Harsini, Farshad Lahouti
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    ABSTRACT: This paper analyzes the performance of clustered decode-and-forward multi-hop relaying (CDFMR) wireless Rayleigh fading networks, and sheds light on their design principles for energy and spectral efficiency. The focus is on a general performance analysis (over all SNR range) of heterogeneous wireless networks with possibly different numbers of relays in clusters of various separations. For clustered multi-hop relaying systems, ad-hoc routing is known as an efficient decentralized routing algorithm which selects the best relay node on a hop-by-hop basis using local channel state information. In this article, we combine ad-hoc routing and cooperative diversity in CDFMR systems, and we derive (i) a closed-form expression for the probability distribution of the end-to-end SNR at the destination node; (ii) the system symbol error rate (SER) performance for a wide class of modulation schemes; and (iii) exact analytical expressions for the system ergodic capacity, the outage probability and the achievable probability of the SNR (power) gain. We also provide simple analytical asymptotic expressions for SER and the outage probability in high SNR regime. Simulation results are provided to validate the correctness of the presented analyses.
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    Alla Tarighati, Hamed Farhadi, Farshad Lahouti
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    ABSTRACT: We address noisy message-passing decoding of low-density parity-check (LDPC) codes over additive white Gaussian noise channels. The internal decoder noise is motivated by the quantization noise of the messages in digital decoders or the intrinsic noise in analog decoders. We model the internal decoder noise as AWGN degrading exchanged messages. Using Gaussian approximation of the exchanged messages, we perform a two-dimensional density evolution analysis for the noisy LDPC decoder. This provides tracking both the mean, and the variance of the exchanged message densities, and hence, quantifying the threshold of the LDPC code in the presence of internal decoder noise. The numerical and simulation results are presented that quantify the performance loss due to the internal decoder noise. To partially compensate this performance loss, we propose a simple method, based on EXIT chart analysis, to design robust irregular LDPC codes. The simulation results indicate that the designed codes can indeed compensate part of the performance loss due to the internal decoder noise.
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    Hamidreza Arjmandi, Farshad Lahouti
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    ABSTRACT: A key pre-distribution scheme (KPS) based on multiple codewords of block codes is presented for wireless sensor networks. The connectivity and security of the proposed KPS, quantified in terms of probabilities of sharing common keys for communications of pairs of nodes and their resilience against colluding nodes, are analytically assessed. The analysis is applicable to both linear and nonlinear codes and is simplified in the case of maximum distance separable codes. It is shown that the multiplicity of codes significantly enhances the security and connectivity of KPS at the cost of a modest increase of the nodes storage. Numerical and simulation results are provided, which sheds light on the effect of system parameters of the proposed KPS on its complexity and performance. Specifically, it is shown that the probability of resilience of secure pairs against collusion of other nodes only reduces slowly as the number of colluding nodes increase.
  • Source
    Siavash Ghavami, Farshad Lahouti
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    ABSTRACT: This paper investigates the capacity and capacity per unit cost of Gaussian multiple access-channel (GMAC) with peak power constraints. We first devise an approach based on Blahut-Arimoto Algorithm to numerically optimize the sum rate and quantify the corresponding input distributions. The results reveal that in the case with identical peak power constraints, the user with higher SNR is to have a symmetric antipodal input distribution for all values of noise variance. Next, we analytically derive and characterize an achievable rate region for the capacity in cases with small peak power constraints, which coincides with the capacity in a certain scenario. The capacity per unit cost is of interest in low power regimes and is a target performance measure in energy efficient communications. In this work, we derive the capacity per unit cost of additive white Gaussian channel and GMAC with peak power constraints. The results in case of GMAC demonstrate that the capacity per unit cost is obtained using antipodal signaling for both users and is independent of users rate ratio. We characterize the optimized transmission strategies obtained for capacity and capacity per unit cost with peak-power constraint in detail and specifically in contrast to the settings with average-power constraints.
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    ABSTRACT: In this paper, a scheme based on 1-D nested lattice quantization followed by multi-level distributed arithmetic coding (MLDAC) as the Slepian-Wolf (SW) code is proposed for the lossy source coding of continuous sources. This system can be employed in distributed video and image coding applications. The output of the quantizer is first converted to binary, and then the SW coding is applied on each bit plane. An efficient algorithm for joint decoding of bit planes at the decoder is proposed, which exploits the dependency of the bit planes with each other and the side-information available at the decoder. Also, a methodology for rate allocation among the bit planes is presented. The quantization parameters are designed to improve the end-to-end system performance based on its overall rate-distortion function taking into account both the distortions due to quantization and imperfect practical Slepian-Wolf coding. The simulation results demonstrate the effectiveness of the proposed MLDAC with the lattice quantization.
    2014 Data Compression Conference (DCC); 03/2014
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    ABSTRACT: We are interested in understanding the neural correlates of attentional processes using first principles. Here we apply a recently developed first principles approach that uses transmitted information in bits per joule to quantify the energy efficiency of information transmission for an inter-spike-interval (ISI) code that can be modulated by means of the synchrony in the presynaptic population. We simulate a single compartment conductance-based model neuron driven by excitatory and inhibitory spikes from a presynaptic population, where the rate and synchrony in the presynaptic excitatory population may vary independently from the average rate. We find that for a fixed input rate, the ISI distribution of the post synaptic neuron depends on the level of synchrony and is well-described by a Gamma distribution for synchrony levels less than 50%. For levels of synchrony between 15% and 50% (restricted for technical reasons), we compute the optimum input distribution that maximizes the mutual information per unit energy. This optimum distribution shows that an increased level of synchrony, as it has been reported experimentally in attention-demanding conditions, reduces the mode of the input distribution and the excitability threshold of post synaptic neuron. This facilitates a more energy efficient neuronal communication.
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    ABSTRACT: Studying the development of malignant tumours, it is important to know and predict the proportions of different cell types in tissue samples. Knowing the expected temporal evolution of the proportion of normal tissue cells, compared to stem-like and non-stem like cancer cells, gives an indication about the progression of the disease and indicates the expected response to interventions with drugs. Such processes have been modeled using Markov processes. An essential step for the simulation of such models is then the determination of state transition probabilities. We here consider the experimentally more realistic scenario in which the measurement of cell population sizes is noisy, leading to a hidden Markov model. In this context, extrinsic randomness is related to noisy measurements, which are used for the estimation of the transition probability matrix. Intrinsic randomness, on the other hand, is here related to the error in estimating the state probability from small cell populations. Using aggregated data of fluorescence-activated cell sorting (FACS) measurement, we develop a minimum mean square error estimator (MMSE) and maximum likelihood (ML) estimator and formulate two problems to find the minimum number of required samples and measurements to guarantee the accuracy of predicted population sizes using a transition probability matrix estimated from noisy data. We analyze the properties of two estimators for different noise distributions and prove an optimal solution for Gaussian distributions with the MMSE. Our numerical results show, that for noisy measurements the convergence mechanism of transition probabilities and steady states differ widely from the real values if one uses the standard deterministic approach in which measurements are assumed to be noise free.
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    ABSTRACT: Studying the development of malignant tumours, it is important to know and predict the proportions of different cell types in tissue samples. Knowing the expected temporal evolution of the proportion of normal tissue cells, compared to stem-like and non-stem like cancer cells, gives an indication about the progression of the disease and indicates the expected response to interventions with drugs. Such processes have been modeled using Markov processes. An essential step for the simulation of such models is then the determination of state transition probabilities. We here consider the experimentally more realistic scenario in which the measurement of cell population sizes is noisy, leading to a particular hidden Markov model. In this context, randomness in measurement is related to noisy measurements, which are used for the estimation of the transition probability matrix. Randomness in sampling, on the other hand, is here related to the error in estimating the state probability from small cell populations. Using aggregated data of fluorescence-activated cell sorting (FACS) measurement, we develop a minimum mean square error estimator (MMSE) and maximum likelihood (ML) estimator and formulate two problems to find the minimum number of required samples and measurements to guarantee the accuracy of predicted population sizes using a transition probability matrix estimated from noisy data. We analyze the properties of two estimators for different noise distributions and prove an optimal solution for Gaussian distributions with the MMSE. Our numerical results show, that for noisy measurements the convergence mechanism of transition probabilities and steady states differ widely from the real values if one uses the standard deterministic approach in which measurements are assumed to be noise free.
    IET Systems Biology 10/2013; 8(5). DOI:10.1049/iet-syb.2013.0031 · 1.67 Impact Factor
  • Reza Parseh, Farshad Lahouti
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    ABSTRACT: In this paper, the problem of uniform quantization for the Wyner-Ziv (WZ) problem in presence of uncertain side information at the encoder is addressed. The uncertain side information problem arises in data compression with side information (SI) when the joint probability distribution of source and SI is not (fully) known at the encoder. The uncertainty is due to the time varying nature of the dependency of source and SI in settings such as wireless sensor networks and distributed video coding. In this paper, a solution is proposed which consists of a multi-mode WZ encoder in conjunction with a carefully designed feedback scheme from the decoder. Each encoder mode is associated with a uniform nested quantizer. In this framework, the quantization parameters, the feedback scheme, and the source coding rate are jointly optimized to minimize the average rate or distortion. Two distinct schemes with adaptive or fixed transmission rate are proposed. Simulation results are provided which demonstrate the effectiveness of the presented solutions and assess the effect of different design parameters including the number of modes (feedback rate) on the performance.
    IEEE Transactions on Communications 02/2013; 61(2):743-752. DOI:10.1109/TCOMM.2012.120512.110792 · 1.98 Impact Factor
  • Siavash Ghavami, Farshad Lahouti, Lars Schwabe
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    ABSTRACT: In this paper we investigate the consequences of biologically plausible constraints on predictions of the Berger-Levy energy efficient neuron model. As new constraints we consider i) a peak power constraint, ii) peak energy expenditure per ISI constraint, iii) a lower bound on the value of inter spike interval (ISI), and iv) lower and upper bounds on the excitatory postsynaptic potential (EPSP) intensity, λ. Our analysis shows that considering these constraints of the capacity per unit cost maximization problem changes the shape of probability distribution function (PDF) of λ and the ISIs. We show, using numerical solutions of the optimization problem, that the new constraints change the PDFs of λ and the ISIs in term of their shape and location of the peak value. We also derive predictions for how the coefficient of variation (CV) of the ISI is changed, which is easier to characterize experimentally than the full PDF.
    Neural Networks (IJCNN), The 2013 International Joint Conference on; 01/2013
  • Jalil S. Harsini, Farshad Lahouti
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    ABSTRACT: The effective capacity (EC) for a wireless system expresses the maximum arrival source rate that the system can reliably transmit over the wireless channel while fulfilling a probabilistic delay constraint. This paper presents an EC optimization for a multiuser diversity system exploiting proportional opportunistic scheduling at the medium access control layer in conjunction with adaptive modulation and coding (AMC) at the physical layer. We consider the downlink of a time-slotted multiuser system with two different types of channel state information (CSI) at the transmitter, that is, (i) full CSI, whereby each user feeds back its normalized signal-to-noise ratio to the transmitter and (ii) quantized CSI, where each user feeds back the AMC mode for transmission. For each case, we first derive the EC function of the queue service process for the individual users at the medium access control layer. We then design the AMC scheme with power control aiming at maximizing the said function subject to a target packet-error rate constraint. Both independent and identically distributed and time-correlated fading channels are considered. The results illustrate the superior performance of the proposed schemes, when compared with the previous systems such as opportunistic scheduling with single-rate transmission and round-robin scheduling with AMC. Copyright © 2012 John Wiley & Sons, Ltd.
    10/2012; 23(6). DOI:10.1002/ett.2511
  • Source
    Hamid Khodakarami, Farshad Lahouti
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    ABSTRACT: In this paper, a link adaptation and untrusted relay assignment (LAURA) framework for efficient and reliable wireless cooperative communications with physical layer security is proposed. Using sharp channel codes in different transmission modes, reliability for the destination and security in the presence of untrusted relays (low probability of interception) are provided through rate and power allocation. Within this framework, several schemes are designed for highly spectrally efficient link adaptation and relay selection, which involve different levels of complexity and channel state information requirement. Analytical and simulation performance evaluation of the proposed LAURA schemes are provided, which demonstrates the effectiveness of the presented designs. The results indicate that power adaptation at the source plays a critical role in spectral efficiency performance. Also, it is shown that relay selection based on the signal to noise ratio of the source to relays channels provides an interesting balance of performance and complexity within the proposed LAURA framework.
    IEEE Transactions on Communications 08/2012; 61(12). DOI:10.1109/TCOMM.2013.111513.120888 · 1.98 Impact Factor
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    ABSTRACT: A scheme for detection of abnormality in molecular nano-networks is proposed. This is motivated by the fact that early diagnosis, classification and detection of diseases such as cancer play a crucial role in their successful treatment. The proposed nano-abnormality detection scheme (NADS) comprises of a two-tier network of sensor nano-machines (SNMs) in the first tier and a data gathering node (DGN) at the sink. The SNMs detect the presence of competitor cells as abnormality that is captured by variations in parameters of a nano-communications channel. In the second step, the SNMs transmit micro-scale messages over a noisy micro communications channel (MCC) to the DGN, where a decision is made upon fusing the received signals. The detection performance of each SNM is analyzed by setting up a Neyman-Pearson test. Next, taking into account the effect of the MCC, the overall performance of the proposed NADS is quantified in terms of probabilities of misdetection and false alarm. A design problem is formulated, when the optimized concentration of SNMs in a sample is obtained for a high probability of detection and a limited probability of false alarm.
    Nano Communication Networks 05/2012; DOI:10.1016/j.nancom.2012.09.008
  • Source
    Roghayeh Joda, Farshad Lahouti
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    ABSTRACT: In this paper, delay-limited transmission of quasi-stationary sources over block fading channels are considered. Considering distortion outage probability as the performance measure, two source and channel coding schemes with power adaptive transmission are presented. The first one is optimized for fixed rate transmission, and hence enjoys simplicity of implementation. The second one is a high performance scheme, which also benefits from optimized rate adaptation with respect to source and channel states. In high SNR regime, the performance scaling laws in terms of outage distortion exponent and asymptotic outage distortion gain are derived, where two schemes with fixed transmission power and adaptive or optimized fixed rates are considered as benchmarks for comparisons. Various analytical and numerical results are provided which demonstrate a superior performance for source and channel optimized rate and power adaptive scheme. It is also observed that from a distortion outage perspective, the fixed rate adaptive power scheme substantially outperforms an adaptive rate fixed power scheme for delay-limited transmission of quasi-stationary sources over wireless block fading channels. The effect of the characteristics of the quasi-stationary source on performance, and the implication of the results for transmission of stationary sources are also investigated.
    IEEE Transactions on Communications 02/2012; 61(4). DOI:10.1109/TCOMM.2013.012313.120060 · 1.98 Impact Factor
  • H. Khodakarami, F. Lahouti
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    ABSTRACT: A secure link adaptation framework is proposed, which exploits the inherent fluctuations of wireless fading channels for high-performance communications and physical layer security in the presence of an eavesdropper. The authors use very sharp channel codes intended for reliability and demonstrate that they also provide security, when successfully incorporated in the link adaptation design framework and the security constraint is not very stringent. Two scenarios are considered in which the transmitter has access to the eavesdropper channel state information either instantaneously or statistically. The proposed secure link adaptation framework is formulated to maximise the spectral efficiency of the communication, whereas both reliability and security constraints are provisioned. Different designs are considered when the security constraint is quantified by instantaneous bit error rate (BER), average BER or leakage probability. For the problem with instantaneous BER constraint, an efficient analytical solution and a numerical solution are presented. A closed-form analytical solution is also provided for secure link adaptation with average BER constraint, whereas the problem with the leakage constraint is tackled numerically. Extensive results and detailed analysis are provided to draw insights on the effects of different design parameters on the performance.
    IET Communications 02/2012; 6(3):353-362. DOI:10.1049/iet-com.2011.0319 · 0.72 Impact Factor
  • Hamidreza Arjmandi, Mehrdad Taki, Farshad Lahouti
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    ABSTRACT: This paper addresses the problem of efficient data gathering in wireless sensor networks with a complexity constrained data gathering node. Due to the complexity constraint, the data gathering node employs an asymmetric DSC that (de)compresses the data of a given node exploiting its dependency with a limited number of other nodes. This is characterized in a DSC rate allocation structure that is referred to as limited-order DSC. Within this structure, we investigate the problem of rate allocation for the nodes to maximize the network lifetime. To this end, an algorithm is proposed that is proven optimal with polynomial complexity in terms of number of network nodes. Numerical results demonstrate that the algorithm, even with limited complexity, allows for exploiting most of the achievable compression gain.
    Signal Processing 11/2011; 91(11):2661-2666. DOI:10.1016/j.sigpro.2011.05.003 · 2.24 Impact Factor
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    Hamidreza Arjmandi, Farshad Lahouti
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    ABSTRACT: This paper addresses the problem of efficient data gathering based on distributed source coding (DSC) in wireless sensor networks (WSNs) with a complexity constrained data gathering node (DGN). A particular scenario of interest is a cluster of low complexity sensor nodes among which, one node is selected as the cluster head (CH) or the DGN. Utilizing DSC allows for reducing the required rate of communications by exploiting the dependency between the nodes observations in a distributed manner. We consider a DSC-based rate allocation structure, which takes into account the CH (DGN) memory and computational constraints. Specifically, this is accomplished, respectively, by limiting the number of nodes whose data may be stored at the CH and exploited during decoding, and the number of nodes that can be jointly (de)compressed using DSC. Based on this structure, we investigate two WSN resource optimization problems aiming at: (i) minimizing the total network cost and (ii) maximizing the network lifetime. To these ends, optimal dynamic programming solutions based on a trellis structure are proposed that incur substantially smaller computational complexity in comparison to an exhaustive search. Also, a suboptimal yet high performance solution is presented whose complexity grows in polynomial order with the number of network nodes. Numerical results demonstrate that the proposed rate allocation structure and solutions, even with limited complexity, allow for exploiting most of the available dependency and hence the achievable compression gain.
    IEEE Sensors Journal 10/2011; 11(9-11):2094 - 2101. DOI:10.1109/JSEN.2011.2109947 · 1.85 Impact Factor
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    ABSTRACT: In a cooperative relay network, a relay (R) node may facilitate data transmission to the destination (D) node when the latter node cannot correctly decode the source (S) node data. This paper considers such a system model and presents a cross-layer approach to jointly design adaptive modulation and coding (AMC) at the physical layer and the truncated cooperative automatic repeat request (C-ARQ) protocol at the data-link layer for quality-of-service (QoS)-constrained applications. The average spectral efficiency and packet loss rate of the joint C-ARQ and AMC scheme are first derived in closed form. Aiming to maximize the system spectral efficiency, AMC schemes for the S-D and R-D links are optimized, whereas a prescribed packet-loss-rate constraint is satisfied. As an interesting application, joint link adaptation and blockage mitigation in land mobile satellite communications (LMSC) with temporally correlated channels is then investigated. In LMSC, the S node data can be delivered to the D node when the S-D is in the outage, therefore provisioning the QoS requirements. For applications without instantaneous feedback, an optimized rate selection scheme based on the channel statistics is also devised. Detailed and insightful numerical results are presented, which indicate the superior performance of the proposed joint AMC and C-ARQ schemes over their optimized joint AMC and traditional ARQ counterparts.
    IEEE Transactions on Vehicular Technology 10/2011; DOI:10.1109/TVT.2011.2151261 · 2.64 Impact Factor
  • Mehrdad Taki, Farshad Lahouti
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    ABSTRACT: We consider a primary and a cognitive user transmitting over a wireless fading interference channel. A discrete rate link adaptation scheme is proposed to maximize the average spectral efficiency of the cognitive radio, while a minimum average spectral efficiency for the primary user is provisioned. The discrete rate scheme for interfering transmission is devised based on two sets of modulation and coding pairs for the primary and cognitive links. The primary transmitter adapts its rate (modulation and coding) solely based on signal to interference plus noise ratio of its link; however, the cognitive transmitter influences the primary link rate by imposing a proper SINR. The adaptive modulation and coding mode selection and power control at the cognitive transmitter are optimized based on SINR of both links. The problem is then cast as a nonlinear discrete optimization problem for which a fast and efficient suboptimum solution is presented. We also present a scheme with rate adaptive and constant power cognitive radio. An important characteristic of the proposed schemes is that no computation overhead is imposed on primary radio due to cognitive radio activity. Numerical results and comparison with the interweave approach to cognitive radio demonstrate the efficiency of the proposed solutions.
    IEEE Transactions on Wireless Communications 09/2011; 10:2929-2939. DOI:10.1109/TWC.2011.070711.101078 · 2.76 Impact Factor
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    ABSTRACT: This paper presents performance analysis and cross-layer design approaches for hybrid ARQ (HARQ) protocols in wireless networks, which employ adaptive modulation and coding (AMC) in conjunction with adaptive cooperative diversity and are subject to time-correlated fading channels. We first consider a point-to-point scenario, i.e., non-cooperative HARQ with AMC. Utilizing a Markov channel model which accounts for the temporal correlation in the successive transmission of incremental redundancy by the HARQ protocol, we derive the system throughput and the packet loss probability based on a rate compatible punctured convolutional code family. Next, we consider a cooperative HARQ (CHARQ) scheme in which a relay node, also equipped with AMC, retransmits redundancy packets when it is able to decode the source information packet correctly. For this scenario, we also derive the throughput and packet loss performance. Finally, we present a cross-layer AMC design approach which takes into account the hybrid ARQ protocol at the link layer. The results illustrate that including AMC in the HARQ protocols leads to a substantial throughput gain. While the performance of the AMC with HARQ protocol is strongly affected by the channel correlation, the CHARQ protocol provides noticeable performance gains over correlated fading channels as well.
    IEEE Transactions on Wireless Communications 04/2011; 10(3-10):877 - 889. DOI:10.1109/TWC.2011.010411.100328 · 2.76 Impact Factor

Publication Stats

346 Citations
73.24 Total Impact Points

Institutions

  • 2015
    • University of Guilan
      • Department of Electrical Engineering
      Resht, Gīlān, Iran
  • 2006–2013
    • University of Tehran
      • • Center of Excellence for Applied Electromagnetic Systems
      • • School of Electrical and Computer Engineering
      • • College of Engineering
      Teheran, Tehrān, Iran
  • 2010
    • University of Padova
      • Department of Information Engineering
      Padua, Veneto, Italy
  • 2000–2009
    • University of Waterloo
      • Department of Electrical & Computer Engineering
      Waterloo, Quebec, Canada