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This paper evaluates the performance of space shift keying (SSK) free-space optical communication (FSO) over moderate and strong turbulent channels. It has been shown previously that repetition codes (RCs) using intensity modulation with... more
This paper evaluates the performance of space shift keying (SSK) free-space optical communication (FSO) over moderate and strong turbulent channels. It has been shown previously that repetition codes (RCs) using intensity modulation with direct detection techniques are superior to SSK system for a spectral efficiency of 1 bit/s/Hz. It is shown in this study that SSK outperforms RCs using M-ary pulse amplitude modulation for spectral efficiencies of 3 bits/s/Hz or larger. Analytical expressions for the bit error rate for the SSK system under study are derived and extensive simulation results corroborate the correctness of the conducted analysis.
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Simulation and experimental performance analyses of simultaneous up-converted signals, for the first time, were investigated utilizing a semiconductor optical amplifier Mach–Zehnder interferometer (SOA-MZI) sampling mixer in co- and... more
Simulation and experimental performance analyses of simultaneous up-converted signals, for the first time, were investigated utilizing a semiconductor optical amplifier Mach–Zehnder interferometer (SOA-MZI) sampling mixer in co- and counter-directions for standard and differential modulation modes. An optical pulse source at a sampling frequency of fs = 15.6 GHz was used as a sampling signal. The IF signal channels carrying quadrature phase shift keying (QPSK) data at frequencies fm were up-converted at different mixing frequencies up to 195.5 GHz. Using the Virtual Photonics Inc. (VPI) simulator, we realized mixed QPSK signals and studied their characteristics through a conversion gain and an error vector magnitude (EVM). Simulations of up mixing operated in a frequency range up to 158 GHz. For the standard modulation in the co-direction, the conversion gain decreased from 43.3 dB at the mixing frequency of 16.6 GHz to 21.8 dB at 157 GHz for the first channel and from 43 dB at 17.6...
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Spectrum Sensing (SS) plays an essential role in Cognitive Radio (CR) networks to diagnose the availability of frequency resources. In this paper, we aim to provide an in-depth survey on the most recent advances in SS for CR. We start by... more
Spectrum Sensing (SS) plays an essential role in Cognitive Radio (CR) networks to diagnose the availability of frequency resources. In this paper, we aim to provide an in-depth survey on the most recent advances in SS for CR. We start by explaining the Half-Duplex and Full-Duplex paradigms, while focusing on the operating modes in the Full-Duplex. A thorough discussion of Full-Duplex operation modes from collision and throughput points of view is presented. Then, we discuss the use of learning techniques in enhancing the SS performance considering both local and cooperative sensing scenarios. In addition, recent SS applications for CR-based Internet of Things and Wireless Sensors Networks are presented. Furthermore, we survey the latest achievements in Spectrum Sensing as a Service, where the Internet of Things or the Wireless Sensor Networks may play an essential role in providing the CR network with the SS data. We also discuss the utilisation of CR for the 5th Generation and Beyo...
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In cognitive radio wireless sensor networks (CRSN), the nodes act as secondary users. Therefore, they can access a channel whenever its primary user (PU) is absent. Thus, the nodes are assumed to be equipped with a spectrum sensing (SS)... more
In cognitive radio wireless sensor networks (CRSN), the nodes act as secondary users. Therefore, they can access a channel whenever its primary user (PU) is absent. Thus, the nodes are assumed to be equipped with a spectrum sensing (SS) module to monitor the PU activity. In this manuscript, we focus on a clustered CRSN, where the cluster head (CH) performs SS, gathers the data, and sends it toward a central base station by adopting an ad hoc topology with in-network data aggregation (IDA) capability. In such networks, when the number of clusters increases, the consumed energy by the data transmission decreases, while the total consumed energy of SS increases, since more CHs need to perform SS before transmitting. The effect of IDA on CRSN performance is investigated in this manuscript. To select the best number of clusters, a study is derived aiming to extend the network lifespan, taking the SS requirements, the IDA effect, and the energy consumed by both SS and transmission into co...
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In this study, a crop health monitoring system is developed by using state of the art technologies including wireless sensors and Unmanned Aerial Vehicles (UAVs). Conventionally data is collected from sensor nodes either by fixed base... more
In this study, a crop health monitoring system is developed by using state of the art technologies including wireless sensors and Unmanned Aerial Vehicles (UAVs). Conventionally data is collected from sensor nodes either by fixed base stations or mobile sinks. Mobile sinks are considered a better choice nowadays due to their improved network coverage and energy utilization. Usually, the mobile sink is used in two ways: either it goes for random walk to find the scattered nodes and collect data, or follows a pre-defined path established by the ground network/clusters. Neither of these options is suitable in our scenario due to the factors like dynamic data collection, the strict targeted area required to be scanned, unavailability of a large number of nodes, dynamic path of the UAV, and most importantly, none of these are known in advance. The contribution of this paper is the formation of dynamic runtime clusters of field sensors by considering the above mentioned factors. Furthermo...
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This paper proposes a method of “blind separation” which extracts non-stationary signals (e.g., speech signals, music) from their convolutive mixtures (observed signals). The function is acquired by modifying a network's... more
This paper proposes a method of “blind separation” which extracts non-stationary signals (e.g., speech signals, music) from their convolutive mixtures (observed signals). The function is acquired by modifying a network's parameters so that a cost function takes the minimum at any time. The cost function is the one introduced by Matsuoka et al. (Neural Networks 8 (3) (1995) 411–419). The learning rule is derived from the natural gradient (Amari et al., 1998, IEEE Trans. Signal Processing, submitted) minimization of the cost function. The validity of the proposed method is confirmed by computer simulation. The proposed method is applied to the case of No (the number of observed signals)=Ns (the number of source signals) and No>Ns.
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ABSTRACT A control-oriented modeling approach is proposed for a low-speed semi-AUV (Autonomous Underwater Vehicle) CISCREA, which has complex-shaped structures. Due to the geometry of this AUV, it is very difficult to identify its dynamic... more
ABSTRACT A control-oriented modeling approach is proposed for a low-speed semi-AUV (Autonomous Underwater Vehicle) CISCREA, which has complex-shaped structures. Due to the geometry of this AUV, it is very difficult to identify its dynamic and hydrodynamic parameters. Therefore, the main objective of this paper is to find an efficient modeling approach to tune acceptable control design models. The presented solution uses cost efficient CFD (computational fluid dynamic) softwares predicting the two hydrodynamic key parameters: The added mass matrix and the damping matrix. A complete model is built for CISCREA from CFD and verified through experimental results. The results indicate that the proposed computational approach seems to be desirable for the robust control scheme of many complex-shaped AUVs. Finally, Numerical and experimental results are compared.
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Abstract--Biometric security systems such as Retina scanner, fingerprint and face recognition among others are the most recently developed security systems. The latest systems can be found in various situations (police checkpoints,... more
Abstract--Biometric security systems such as Retina scanner, fingerprint and face recognition among others are the most recently developed security systems. The latest systems can be found in various situations (police checkpoints, airport facilities, . . . ). As they become widely used and requested, an increasing number of researchers are working in this field. In this paper, we propose a new Biometric Recognition method based on Independent Component Analysis technique "ICA".
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International audienc
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Providing a wide variety of the most up-to-date innovations in sensor technology and sensor network, our current project should achieve two major goals. The first goal covers some issues related to public safety and security, such as the... more
Providing a wide variety of the most up-to-date innovations in sensor technology and sensor network, our current project should achieve two major goals. The first goal covers some issues related to public safety and security, such as the coastal and port surveillance systems. While the second one will improve the capacity of public authorities to develop and implement smart environment policies by monitoring the shallow coastal water ecosystems. At this stage of our project, a surveillance platform has been already installed near the "Molene Island" which is a small but the largest island of an archipelago of many islands located off the West coast of Brittany in France. Our final objective is to add various sensors as well as to design, develop and implement new algorithms to extend the capacity of the existing platform and reach the goals of our project. This chapter describes the whole project by focusing on the variety of used sensors and it will briefly introduce the most important required theoretical approaches such as: Blind signal processing, High Order Statistics (HOS), classification algorithms and data fusion methods which will be applied to build up an original and reliable system able to perform a sustainable and long term monitoring of coastal marine ecosystems and to enhance port surveillance capability. In addition, it discusses developed techniques and concepts to deal with several problems related to our project. The new system will address the shortcomings of traditional approaches based on measuring environmental parameters, which are expensive and fail to provide adequate large-scale monitoring. More efficient monitoring will also enable improved analysis of climate change, and provide knowledge informing the civil authority's economic relationship with its coastal marine ecosystems. Some results are given and discussed.
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We consider the problem of preliminary classification of digitally modulated signals. The goal is to simplify further signal analysis (synchronization, signal separation, modulation identification and parameters estimation) by making... more
We consider the problem of preliminary classification of digitally modulated signals. The goal is to simplify further signal analysis (synchronization, signal separation, modulation identification and parameters estimation) by making initial separation among the most ...
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This paper proposes a new method for classifying Digital Modulations, including the typical PSK (Phase Shift Keying), FSK (Frequency Shift Keying), ASK (Amplitude Shift Keying) as well as the present OFDM (Orthogonal Frequency Division... more
This paper proposes a new method for classifying Digital Modulations, including the typical PSK (Phase Shift Keying), FSK (Frequency Shift Keying), ASK (Amplitude Shift Keying) as well as the present OFDM (Orthogonal Frequency Division Multiplex) modulation. The method is based on the analysis of the time frequency representation of the digitally modulated signals. At first, some experiments have been done
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Research Interests: Robotics, Neuroscience, Computer Science, Signal Processing, Wireless Communications, and 11 moreMotion control, Blind Source Separation, Random Walk, Randomness, Higher order statistics, Cognitive Radios, Homing, Obstacle Avoidance, Biological systems, Mobile Agent, and Electrical And Electronic Engineering
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This paper presents an adaptive procedure for the linear and non-linear separation of signals with non-uniform, symmetrical probability distributions, based on both simulated annealing and competitive learning methods by means of a neural... more
This paper presents an adaptive procedure for the linear and non-linear separation of signals with non-uniform, symmetrical probability distributions, based on both simulated annealing and competitive learning methods by means of a neural network, considering the properties of the vectorial spaces of signals, and using a multiple linearization in the mixture space.
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ABSTRACT
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For the convolutive mixture, a subspace method to separate the sources is proposed. It is showed that after using only the second order statistic but more sensors than sources, the convolutive mixture can be itentified up to instantaneou... more
For the convolutive mixture, a subspace method to separate the sources is proposed. It is showed that after using only the second order statistic but more sensors than sources, the convolutive mixture can be itentified up to instantaneou mixture. Furthermore, the sources can be separated by any algorithm for instantaneous mixture (based in generally on the fourth order statistics).