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The present article aims to investigate and evaluate the performances of DWDM (or Dense Wavelength Division Multiplexed) system under MIMO-FSO (or multiple input multiple output-free space optical) channel. However, the proposed system is configured and simulated in the worst-case meteorological conditions, and we base here on the variation of the attenuation coefficient. In this article, the proposed system is devoted to 90 users, every user exploits 30 Gbps. So, the total capacity of system is 90x30 Gbps. In addition, the use of MIMO technique in FSO channel ensures us the stability of the proposed system in the worst-case meteorological conditions and especially when the system exploits a high throughput. To assess the acceptable performance levels of the proposed system, it is necessary to use the following criteria: the minimum bit error rate (or BER) performance, the maximum quality factor (or Q-Factor) and the optical signal to noise ratio (or OSNR) performance. Finally, the proposed system in this paper provides a promising solution for 5G networks as back-up optical link.

In this paper, the magnitude optimization for the design of two dimensional digital filter is attempted and new design method for a two-dimensional (2-D) recursive digital filter is proposed via appropriate genetical swarm optimization with the introduction of the desired stability constraints. The method is tested on a numerical example and the obtained results are presented with previously published methods.

This paper aims at improving the performance of spectrum mobility in cognitive radio local area networks under a congested environment. Due to the atmospheric turbulence and random effects of fading and multipath shading, the nature of the propagation channel could be affected. For this, the link with the smallest SNR can be considered. The main purpose of the present paper is to enhance the SNR link and the end-to-end throughput, and to reduce the expected transmission time from the primary base station towards the secondary user under the used spectrum, while considering that the secondary user is in motion. To meet these objectives, three algorithms have been suggested, namely the Kalman Filter, the Alpha–Beta Filter and the Simple Recursive Estimator. The Kalman Filter and the Alpha–Beta Filter have been particularly used to estimate the path of a secondary user node, while the Simple Recursive Estimator has been employed to get better primary signal sensing in a congested environment. In the end, the simulation results obtained allowed demonstrating the effectiveness of the proposed algorithms. Note that the average expected total transmission time could be reduced to 4.1827 s, while the mean end-to-end throughput reached the value 3.67 kbps.

The present article aims to investigate and analyze the performance of a 90 wavelengths multiplexed in optical link network using Dense Wavelength Division Multiplexed (DWDM) technology under a 20x20 multiple input multiple output (MIMO) based free space optical (FSO) communication system. The data rate for each wavelength is 30 Gbps, and the proposed scheme is simulated with the worst case, which is fog attenuation. The use of MIMO system ensures the data transmission with less bit error rate and improves the quality factor (Q-Factor) and optical signal to noise ratio (OSNR) of optical link. Finally, the suggested scheme provides a promising solution for the future as back-up optical links.

DOA estimation in array processing uses MUSIC (Multiple Signal Classification) algorithm, mainly. It’s the most investigated technique and is very attractive because of its simplicity. However, it meets drawbacks and fails when only very few samples are available and the sources are very close or highly correlated. In these conditions, the problem is more intricate and the detection of targets becomes arduous. To overcome these problems, a new algorithm is developed in this paper. We combine bootstrap technique to increase sample size, spatial sampling and MUSIC method to improve resolution. Through different simulations, the performance and the effectiveness of the proposed approach, referred as spatial Sampling and Bootstrapped technique ‘’SSBoot’’, are demonstrated.

The signal strength sensing in the context of cognitive radio networks (CRNs), is very important to predict the primary signal of base station (PBS), particularly when the secondary user (SU) is in a congested environment, and also when is in motion towards the end of coverage of PBS. However, this article presents an analysis on the prediction of primary signal strength in CRNs using an Alpha-Beta Filter (ABF) and a Neyman-Pearson Detector (NPD). The challenge of this contribution is based on a realistic sensing of primary signal strength and to do that, we have assumed that the reporting channels between the SU and the PBS are composited with the shadowing and multipath fading (SMF), and the receiver noise has also added. In this regard, the obtained results were discussed through: the signal-to-noise ratio (SNR) uncertainty, the detection probability (PD) and the False Alarm Probability (PFA), where the average relative error of prediction for the PD will be equal to10-5.

This paper describes the design and the optimization of microwave integer-N frequency synthesizer used in transceivers for satellite application capable to process in S band [2]–[4] GHz frequencies. The optimization and the choice of the loop filter parameters are a very critical part of the frequency synthesizer. The optimized principle is based on the search for the best compromise between spectral purity and acquisition time to meet the defined applications requirements. Through different simulations and frequencies comparison, the performance and effectiveness of the proposed design are demonstrated.

The effects of impulse noise are felt by most communication systems so much research is done to model and eliminate it. In this paper, we discuss the different impulsive noise models in the literature Middleton Class A, Bernoulli-Gaussian and Symmetric alpha-stable. We then go further to give the influence of each one of these models on the ECG signal, Normalized Least Mean Square (NLMS) and Recursive least squares (RLS) are used to remove the impulsive noise. We simulate the different noises and filters using MATLAB and analyze the effect of the noise on the ECG as well as the performances of the algorithms in terms of MSE

Orthogonal frequency division multiplexing (OFDM), with its resistance to selective fading and multipath effect has become the most widely used technique in wireless communication. OFDM transmission is destroyed by interference noise that has impulsive behavior. In this paper, bit-error-rate (BER) performance of the OFDM system in the presence of impulsive noise was evaluated under different combinations of digital modulation and Convolutional Code (CC) rate.

The sensing method of spectrum resources in wireless networks has become a very special challenge for the future generations of mobile communications, such as: the radio frequencies (RF) and the millimeter waves 5G. However, the awareness of the current spectral situation is very important in wireless networks and this to identify the spectrum scarcity with accurately. In this paper, we propose an original contribution in the spectrum sensing context for the cognitive radio networks (CRNs). The sensing of the primary signals for each primary base station (PBS) in the CRNs can be very difficult when the Gaussian noise of the channel becomes impulsive noise, i.e. the noise is non-stationary. To remedy this issue and optimized the Conventional Sensing Methods (CSMs), the Moving Average Filter (MAF) and the Kalman Filter (KF) have been used. In addition, to quantify the primary signal sensing, the Neyman-Pearson Detector (NPD) is proposed. Finally, the sensing parameter optimizations under an impulsive noise channel are confirmed by the numerical results.

Orthogonal frequency division multiplexing (OFDM) is a form of multi-carrier transmission technique widely used in the modern wireless network to achieve high-speed data transmission with good spectral efficiency. However, in impulsive noise environement BER performances of these systems, originally designed for a Gaussian noise model, are much degraded. In this paper, a new symmetric-alpha-stable (SαS) noise suppression technique based conjointly on adaptive modulation, convolutional coding (AMC) and Recursive Least Square (RLS) filtering is presented. The proposed scheme is applied on OFDM system in Rayleigh fading channel. The transmissions are analyzed under different combinations of digital modulation schemes (BPSK, QPSK, 16-QAM, 64-QAM) and convolutional code rates (1/2, 2/3, 3/4). Simulation results show that our proposed hybrid technique provides effective impulsive noise cancelation in OFDM system and exhibits better BER performance.

This paper presents a design of mm-Wave band integer PLL frequency synthesizer for 5G applications. An optimization between lock time and reference spurs is presented and an optimal value of loop bandwidth parameter is chosen such that satisfies the tradeoff between them.

This paper presents an analyzing on the prediction of a primary signal in cognitive radio networks using a hybrid algorithm based on two parts, know as: an alpha-beta filter and a neyman-pearson (NP) detector. Today, it is important to predict a primary signal in a cluttered environment and especially when the secondary user (SU) is moving. However, the challenges of this contribution are based on realistic sensing of a primary signal and to do that, we have assumed that the reporting channels between a SU and a primary base station are composited with multipath and shadowed fading (MSF), also with a receiver noise. Predicting the probability of a primary signal was discussed through the probability of total detection error. The average relative error obtained will be equal to 10−4.

DOA estimation in array processing uses MUSIC (Multiple Signal Classification) algorithm, mainly. It's the most investigated technique and is very attractive because of its simplicity. However, it meets drawbacks and fails when only very few samples are available and the sources are very close or highly correlated. In these conditions, the problem is more intricate and the detection of targets becomes arduous. To overcome these problems, a new algorithm is developed in this paper. We combine bootstrap technique to increase sample size, spatial sampling and MUSIC method to improve resolution. Through different simulations, the performance and the effectiveness of the proposed approach, referred as spatial Sampling and Bootstrapped technique “SSBoot”, are demonstrated.

In order to improve resolution and direction of arrival (DOA) estimation of two closely spaced sources, in context of array processing, a new algorithm is presented. However, the proposed algorithm combines both spatial sampling technic to widen the resolution and a high resolution method which is the Multiple Signal Classification (MUSIC) to estimate the DOA of two closely spaced sources impinging on the far-field of Uniform Linear Array (ULA). Simulations examples are discussed to demonstrate the performance and the effectiveness of the proposed approach (referred as Spatial sampling MUSIC SS-MUSIC) compared to the classical MUSIC method when it’s used alone in this context.

This paper presents a new technic to improve resolution and direction of arrival (DOA) estimation of two closed source, in array processing, when only few samples of received signal are available. In these conditions, the detection of sources (targets) is more arduous, and even breaks down. To overcome these problems, a new algorithm is proposed. It combines spatial smooth method to widen the spatial resolution, bootstrap technique to estimate increased sample size, and a high resolution technique which is Multiple Signal Classification (MUSIC) to estimate DOA. Through different simulations, performance and effectiveness of the proposed approach, referred to as Spatial Smooth and Bootstrapped technique “SSBoot’’, are demonstrated.

Cet article decrit la simulation et la conception d'un synthetiseur de frequence destine pour les applications des communications mobiles sur GSM. Dans ce travail, nous discutons les effets du bruit de phase dans chaque composant dans le circuit et les raies de reference sur les performances du systeme. Une evaluation precise du filtre de boucle est necessaire afin d’optimiser les performances du circuit en trouvant un compromis entre le temps du changement de la frequence (PLL lockup time) et les raies de reference. Mots-cles : PLL, GSM, synthetiseur de frequence, bruit de phase.