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Summary: The channel estimation (CE) process is an important phase that has a considerable influence on the performance of massive multiple‐input multiple‐output systems, in particular, in a more realistic scenario where the channels are spatially correlated (ScD). Thereby, in this work, the uplink (UL) CE process and channel hardening (CH) feature is addressed for ScD Rayleigh fading channels using the statistical Bayesian minimum mean square error estimator. The spatial correlation (SC) of the channels is described using different models, namely, the Gaussian local scattering (GLS) model, the uniform local scattering model, and the proposed hybrid model. Each model (i.e., GLS model and the uniform local scattering model) is studied using two arrangements, that is, for a uniform linear array (ULA) and uniform planar array (UPA). Moreover, the CH feature is investigated under SC of the channels using different models. Furthermore, this study proposes an efficient hybrid strategy based on SC of the channels for UL CE; that is, this work proposes a hybrid covariance matrix (CM) for UPA arrangement by relying on the Kronecker product of the CMs generated through two ULA arrangements, where the first CM is generated through horizontal ULA using GLS model, whereas the second CM is generated through vertical ULA using uniform local scattering model (i.e., one‐ring model). Numerical results regarding CE and CH are provided to assert the theoretical expressions, where the CE is evaluated using the normalized mean square error, whereas the CH is assessed using the variance of CH. [ABSTRACT FROM AUTHOR]

Abstract: The goal of the present contribution is to use the Hammerstein series and higher order cumulants (HOC) techniques for modelling the time series of the video packet transmission in internet protocol (IP) networks. The model obtained is compared with existing linear moving average (MA) model using root mean square error (RMSE) criterion. The obtained results prove that the model based on the Hammerstein series is more precise than the MA model and demonstrate the effectiveness of the nonlinear model, which provides an effective description of network conditions at different times. [Copyright &y& Elsevier]

In recent years, microwave filtering technologies have known great advancement and wide employment in wireless communication systems, necessitating the development of miniaturization techniques to respect the size limitation in wireless communication devices and reduce the cost, in order to satisfy the consumer and be more competitive. Accordingly, the design of a microwave filter is chosen based on its electrical performance, size, and manufacturing price. Therefore, it is necessary to make a good compromise between the mentioned criteria to satisfy the industrial requirements. This paper proposes a small and inexpensive bandpass filter (BPF), where the proposed structure is carefully constructed over a low-price FR4 Epoxy substrate with a full dimension of (17.6 × 9 × 1.6) mm3. The proposed filter offers good electrical performance in terms of reflection coefficient (S11), insertion loss (S21), Voltage Standing Wave Ratio (VSWR), and selectivity. A filter prototype is fabricated and tested to affirm the simulation results. Consequently, the measured results show a good agreement with the simulation, proving the suitability of the proposed filter for different wireless applications, including WLAN, Bluetooth, ZigBee, RFID, and ISM bands. [ABSTRACT FROM AUTHOR]

Summary: This work addresses channel estimation (CE) in the uplink phase for a cell‐free massive multiple‐input multiple‐output system operating under the time division duplex protocol. Considering that, channels are spatially correlated under the Rician fading model, where the investigated model is composed of two components: deterministic and nondeterministic, with the deterministic component describing the line‐of‐sight paths and the nondeterministic component describing the non‐line‐of‐sight paths. Additionally, we dealt with correlated shadow fading that represents the most realistic situation. On the other hand, this work introduces a dynamic cooperation cluster framework in which the user is not served with the whole network (i.e., all access points [APs]) but only the APs that present the best channel conditions regarding that user. In other words, this work proposes partial CE for each user because only APs with the best channel conditions are allowed to compute channel estimates. Consequently, we proposed partial channel estimators that perform the CE process with low complexity, namely, a partial minimum mean square error estimator and a partial element‐wise minimum mean square error estimator. In addition, a simple pilot assignment technique is proposed in order to reduce interference signals so that each user experiences low interference from other users. Furthermore, the computational complexity required by each estimator is derived, where it is represented by the number of complex multiplications that each estimator requires in each consistency block. Theoretical and simulated results are provided, where the performance of each estimator is evaluated and analyzed using the normalized mean‐square error metric. [ABSTRACT FROM AUTHOR]

Miniaturization in the telecommunications field is deemed a current challenge and a critical demand in order to improve communication quality between the transmitter and the receiver while avoiding clutter issues. The main objective of this work is to design a miniature interdigital bandpass filter (IBF) using planar technology. The proposed bandpass filter is made up of three equidistant parallel-coupled lines carefully deposited on a small Rogers-5880 substrate possessing a full dimension of 10×10×1.6 mm³, a relative permittivity =2.2, and a loss tangen of 0.0009. The proposed IBF has been designed and simulated using the HFSS software, which is a simulator that studies the electromagnetic behavior of radio frequency structures using cutting-edge finite element solvers. The reached outcomes present good electrical performance in terms of insertion loss, reflection coefficient, voltage standing wave ratio (VSWR), and selectivity, making the proposed IBF suitable for integration in small electronic devices for C-band applications (4 GHz to 8 GHz). [ABSTRACT FROM AUTHOR]

Precise global solar radiation (GSR) measurements in a given location are very essential for designing and supervising solar energy systems. In the case of rarity or absence of these measurements, it is important to have a theoretical or empirical model to compute the GSR values. Therefore, the main goal of this work is to offer, to designers and engineers of solar energy systems, an appropriate and accurate way to predict the half-hour global solar radiation (HHGSR) time series from some available meteorological parameters (relative humidity, air temperature, wind speed, precipitation, and acquisition time vector in half-hour scale). For that purpose, two intelligent models are developed: the first one is a multivariate dynamic neural network with feedback connection, and the second is a multivariate static neural network. The database used to build these models was recorded in Agdal’s meteorological station in Marrakesh, Morocco, during the years of 2013 and 2014, and it was divided into two subsets. The first subset is used for training and validating the models, and the second subset is used for testing the efficiency and the robustness of the developed models. The obtained results, in terms of the statistical performance indicators, demonstrate the efficiency of the developed forecasting models to accurately predict the HHGSR parameter in the city of Marrakesh, Morocco. [ABSTRACT FROM AUTHOR]

An accurate predictive model is essential for monitoring the energy produced by a solar system based on different meteorological parameters. In the present paper, a novel machine-learning model named DNN-RODDPSO is proposed to improve the real-time prediction accuracy of the hourly energy produced by four dual-axis solar trackers. This model integrates a new deep neural network (DNN) model with a recent variant of PSO algorithm referred to as a randomly occurring distributed delayed particle swarm optimization (RODDPSO) algorithm. This algorithm is adopted to enhance the training process of the DNN model by reducing the risk of being trapped into local optima and for the search space diversification. Furthermore, to develop the DNN-RODDPSO model, the hourly observations of seven meteorological parameters including time variable measured during 2014–2015 in Alice Springs city, Australia, are used. This model integrates two novel hidden layers, the first one is a selective layer based on daytime/nighttime data selection. The second one named automatic inputs relevance determination to point out the most relevant inputs for an accurate prediction. The obtained results demonstrate the high performance of the two novel hidden layers and the RODDPSO algorithm to improve significantly the prediction accuracy compared to the actual literature standards. • A novel hybrid ANN based on RODDPSO algorithm is developed. • A novel selective layer based on daytime/nighttime data selection is introduced. • A novel automatic inputs relevance determination layer is proposed and validated. • The energy potential produced by four solar trackers is monitored. [ABSTRACT FROM AUTHOR]

In this study, we propose a new hybrid machine-learning algorithm called artificial multi-neural approach, for developing a multi-input single-output (MISO) model to estimate the hourly global solar radiation (HGSR) time series in Agdal site (latitude 31° 37′ N, longitude 08° 01′ W, elevation 466 m), Marrakesh, Morocco. To achieve this goal, three training algorithms (scaled conjugate gradient, Levenberg-Marquardt, and resilient backpropagation) are selected to train the developed model, using some accessible hourly meteorological variables recorded during 7 years (from 2008 to 2014) as exogenous inputs. Furthermore, a pertinence determination test (PDT) is used to point out the most pertinent inputs for the accurate HGSR estimation. The best configuration of the multi-neural model includes five known input parameters as the best scenario, i.e., acquisition hour, air temperature, relative humidity, wind speed, and precipitation. Some statistical indicators are used to evaluate the performance of the developed model. The obtained results demonstrate the reliability and the precision of our proposed machine-learning algorithm, representing a good solution for estimating solar radiation time series needed to design and manage solar energy systems compared to the present standards. [ABSTRACT FROM AUTHOR]

The MIMO antenna is one of the essential elements for the implementation of the new fifth-generation (5 G) technologies. The design of the MIMO antenna goes through several steps; the important one is the design of the single-element antenna that resonates at the desired frequency band(s). Its design becomes more difficult if it is a multi-band antenna. In addition, determining the dimensions of multi-band antennas by simulation or mathematical models is both more complicated, difficult, and time-consuming. In this research, different approaches based on artificial neural networks (ANN), radial basis function neural networks (RBFNN), and adaptive neuro-fuzzy inference systems (ANFIS) are used to predict the dimensions of a dual-band circular patch antenna with defected ground structure (DGS) for mm-wave 5 G applications, and then the performances of the three models are compared. To determine the training and the testing data, 280 antennas with different patch values and added slots in the ground plane are simulated. The resonant frequencies of the dual-band circular patch antenna and the height of the substrate are used as the input vector for the ANN, RBFNN, and ANFIS models. Two hundred twenty simulated antennas were used for training, and the remaining 60 data points were used to test the ANN, RBFNN, and ANFIS models. The performance of these models is compared in the training and testing process using some statistical criteria such as MSE, MAE, and RMSE. The proposed dual-band circular patch single-element antenna has a compact size of 5 × 6 × 0.8 m m 3 and exhibits good performance, such as broad band (3.8 and 3 GHz), high gain (6 and 7.1 dB), and high efficiency (99 % and 95 % ) in both operating bands. After studying the single-element antenna and in order to improve its performance, we proposed a 4 × 4 MIMO antenna with a total volume of 17 × 17 × 0.8 m m 3 that was designed by using four copies of the single-element antenna arranged orthogonally on the same low-loss Rogers Duroid 5880 substrate. The suggested 4 × 4 MIMO antenna achieves a high level of isolation (more than - 30 dB in both operating bands), which is obtained by inserting a cross-shaped decoupling structure among elements on the upper and lower sides of the substrate. Moreover, the proposed MIMO antenna has a good gain of 6.4 and 7.5 dB in both bands and a high radiation efficiency of 99.5 % and 99 % at 28 and 38 GHz, respectively. Furthermore, the diversity performance of the MIMO antenna is evaluated using a variety of crucial indicators, all of which greatly surpass realistic norms. The envelope correlation coefficient (ECC) is less than 0.005, the diversity gain (DG) is greater than 9.99 dB, the total active reflection coefficient (TARC) is below 10 dB, and the channel capacity loss (CCL) is no longer than 0.4 bits/s/Hz. In addition, the proposed dual band circular patch single element antenna and the 4 × 4 MIMO antenna are fabricated, and the measured results are in good agreement with the simulated results using HFSS and CST software. [ABSTRACT FROM AUTHOR]

Summary: This work proposes an electrical compact triple‐bands antenna founded on a composite left‐/right‐handed approach. This structure contains a rectangular patch combined with two unit cells based on the metamaterial properties that are used to produce wide electrical lengths in miniature physical sizes. Thus, the presented antenna is designed with a lower resonant frequency and miniature physical dimensions compared to conventional antennas. The suggested antenna has been produced on top of the FR4 substrate having tan δ = 0.022, εr = 4.58, and a size of 28 × 16 × 1.6 mm3. This structure provides three bandwidths of (2.391–2.54 GHz), (3.42–3.56 GHz), and (5.02–11.40 GHz). Additionally, a multi‐input multioutput (MIMO) antenna is designed by placing two similar radiating patches in a perpendicular shape. Therefore, this design approach has been used to achieve an important isolation among ports and less than −30 dB at frequency bands. The results of radiation patterns, envelope correlation coefficient, diversity gain, and channel capacity loss are below to 0.06, 10 dB, and 0.4 b/s/Hz respectively, which confirms that the MIMO antenna is compatible with wireless MIMO devices. These antennas have been modeled and experimentally confirmed, and the results have proven that the suggested antennas are useable and can support multi‐standard wireless applications. [ABSTRACT FROM AUTHOR]

This paper focuses on the design of a novel automatic‐dependent surveillance‐broadcast (ADS‐B) patch antenna operating at 1090 MHz with good bandwidth and good gain for aircraft tracking and navigation purposes. The structure of the proposed antenna consists of a long strip line ended by a crescent patch, a U‐shaped ground plane, and a rectangular substrate. The proposed antenna is simulated using both HFSS and CST electromagnetic simulators. The overall dimensions of the antenna are 130 × 26 × 1.6 mm3, and is fabricated on a low‐cost FR‐4 epoxy substrate. Various parameters are determined and analyzed to evaluate the antenna performance in terms of reflection coefficient, impedance bandwidth, radiation pattern, gain, and efficiency. It has been verified and tested that the simulated results are in very good agreement with the measured ones. At the desired frequency of 1090 MHz, the ADS‐B patch antenna has a gain of 2.23 dBi and a measured impedance bandwidth at −10 dB of 200 MHz. The antenna has an omnidirectional radiation pattern, which will allow the antenna to pick up ADS‐B signals broadcasted by aircraft in all directions. An ADS‐B system has been built and validated using aircraft data provided by the Flightradar platform. [ABSTRACT FROM AUTHOR]

The millimeter-wave spectrum is deemed as an attractive solution to deal with the urgency of the high-data-rate needed to construct the 5G technology systems. Accordingly, this research work presents a high-isolation ultra-wideband dual-port MIMO antenna, and operates at the pioneer 28 GHz band for millimeter-wave 5G applications. The individual antenna consists of a new ring-shaped monopole antenna built on the low loss Rogers RT Duroid 5880 laminate, well-refined to bear a large bandwidth of 10 GHz from 24 to 34 GHz with suitable radiation features including a high radiation efficiency up to 99% and good comparable gain reaches to 5.9 dB. The single-antenna unit is carefully investigated, then exploited to propose a compact orthogonally placed two-port MIMO antenna with small total volume of 11 × 20.5 × 0.254mm3 while provides a strong isolation surpassing 25 dB. The MIMO diversity performance has been neatly evaluated in terms of various essential metrics, where an impressive performance has been proven. The simulation results are experimentally validated for both single and MIMO structures where a great harmony is demonstrated. Moreover, the impact of connected ground plane scheme on the MIMO antenna performance is also discussed, where a gratifying outcomes are accomplished. Besides, the proposed two-element MIMO antenna is further extended to four and eight elements MIMO antennas with connected ground plane configuration. A pretty simple decoupling structures are used, whereas a very satisfying results are fulfilled. The achieved outcomes make the proposed design superior to many existing designs and highly fit for the 5G wireless systems. [ABSTRACT FROM AUTHOR]

In this study, a planar microwave sensor was proposed and manufactured with the aim of detecting and categorizing concentrations of various organic substances, including methanol (CH 3 OH), ethanol (CH 3 CH 2 OH), and 1-butanol (CH 3 CH 2 CH 2 CH 2 OH), as well as inorganic substances such as sodium carbonate (Na 2 CO 3), potassium carbonate (K 2 CO 3), and sodium hydroxide (NaOH). Throughout the sensor's development, a configuration incorporating a microstrip line and a rectangular patch with a central circular aperture was employed. Full-wave electromagnetic simulation software was utilized to analyze the performance of the sensor in terms of reflection coefficients. The sensor was fabricated using a PCB material with defined properties, which included a dielectric constant of 4.3, a loss tangent of 0.025, and a thickness of 1.6 mm. The reflection coefficient (S 11) was measured and analyzed using principal component analysis (PCA) to identify correlations between the classification groups and concentrations of organic and inorganic samples. Additionally, the equivalent circuit has been extracted and modeled to describe the operating mechanism of the microwave sensor. The simulation and measurement results indicate that the sensor is a suitable candidate for the detection and classification of water samples containing CH 3 OH, CH 3 CH 2 OH, CH 3 CH 2 CH 2 CH 2 OH, Na 2 CO 3 , K 2 CO 3 , and NaOH. The proposed microwave sensor features a surface area of 29 × 18 mm², leading to a noteworthy reduction in surface utilization compared to other breath biosensors designed for measurement purposes. [Display omitted] • The dielectric perturbation phenomena and sensing technique. • The proposed microwave sensor demonstrates a compact size and cost-effectiveness, rendering it highly suitable for integration as a biochemical sensor technology within the telecommunications and sensor domains. • Rapid detection and discrimination of organic substances (CH 3 OH, CH 3 CH 2 OH, and CH 3 CH 2 CH 2 CH 2 OH) as well as inorganic substances (Na 2 CO 3 , K 2 CO 3 , and NaOH). • The detection method is simple and rapid. [ABSTRACT FROM AUTHOR]

In this paper we propose to predict the notch frequency of an ultra-wideband (UWB) antenna which operates in the frequency band from 3.85 GHz to 12.38 GHz. The prediction of the notch frequency in order to avoid interferences between (WLAN) IEEE802.11a and HIPERLAN/2 WLAN applications and UWB technology is achieved using the artificial neural networks (ANN) technique. The developed ANN is optimized with the help of K-fold cross validation method which allows us to divide the datasets into 10 subsets in the training phase. The simulated datasets are generated by controlling high frequency structural simulator (HFSS) from MATLAB using a VB script. The performance of the ANN technique is assessed using some statistical criteria. During the training process, the mean absolute percentage error (MAPE) between the simulated and the predicted ANN notch frequencies is 0,125. A comparison between simulated, theoretical, and ANN results has been achieved during the test and validation process, good accuracy is obtained between the simulated and the ANN predictions. The proposed UWB antenna exhibits a notch band from 5.1 GHz to 6.0 GHz with a notch frequency of approximately 5.51 GHz. [ABSTRACT FROM AUTHOR]

In this paper, a novel design of miniature and broadband‐multiband coplanar waveguide‐fed planar antenna with a symmetric quarter‐circular ground plane is suggested to realize multiband with better performance. The experimental results show that the suggested antenna has achieved two bandwidths (S11 < −10 dB): the lower band from 2.34 to 2.42 GHz centered around the resonant frequency of 2.38 GHz and the upper broadband from 3.16 to 6.57 GHz resonating at 3.5 and 5.38 GHz, respectively. The bandwidths cover the two required bands: WiMAX and WLAN at the frequencies 3.5/5.5 and 2.4/5.2/5.8 GHz, respectively. All these three resonant frequencies show better impedance matching with convenient gain and high radiation efficiency; moreover, the radiation patterns in the H‐plane and E‐plane are omnidirectional and bidirectional, respectively. The patch antenna prototype is constructed on a simple substrate named FR4 epoxy and having total dimensions of 0.23λ × 0.14λ × 0.012λ, as λ is the free‐space wavelength at the lower resonant frequency. In addition, the resulting multiband antenna is a highly compact size and having a good performance, which makes it appropriate for wireless systems in diverse applications. [ABSTRACT FROM AUTHOR]

• A neuro-fuzzy inference system boosted with a recent optimizer is proposed. • A new layer denominated as non-working time adaptation was proposed. • Autoregressive process is applied to generate significant endogenous inputs. • Hourly energy consumption of a Faculty building is accurately predicted. The accuracy of the prediction of buildings' energy consumption is being tackled using existing artificial intelligence techniques. However, there is a lack of effort on the development of new techniques for solving that problem and, therefore, achieving higher performance, which is important for the efficient management of energy in many levels. This study addresses this gap by proposing a new hybrid machine learning algorithm that incorporates the adaptive neuro-fuzzy inference system model with a new version of the firefly algorithm denominated as the gender-difference firefly algorithm. We expanded the search space diversification to increase the accuracy on the prediction and adopted the autoregressive process in order to approximate the chaotic behavior of the consumption time series. A new layer, denominated as non-working time adaptation was also integrated so as to decrease the fast variability of the predictions during non-working periods of time. We have applied our algorithm for the consumption prediction on 1 h, 2 h and 3 h ahead horizons. We have obtained improvements on the MAPE and R coefficient when compared with state-of-the-art publications in both a private dataset from the Faculty of Chemistry, located in the city of Murcia, Spain and a public dataset of the consumption of a Retail building located in California, United States. We also show our method's performance in five more buildings. Our results demonstrate the robustness and the accuracy of our proposal when compared to the traditional adaptive neuro-fuzzy inference system models and also to the different predictive techniques implemented in several pieces of literature. [ABSTRACT FROM AUTHOR]

This study presents a new dual‐layer metasurface structure proposed to enhance the performance of a circular patch antenna. A novel unit cell planar metasurface is characterized by nearly equal enhanced effective permeability and permittivity εr≅μr > 1 at the resonant frequency. In addition, a 5*5 array of these unit cells are used as a superstrate over a circular patch antenna which is fed by 50 Ω microstrip line and operating at 2.45 GHz for improving the antenna performance. The patch antenna gain is increased by creating an in‐phase electric field area on the top surface of the metasurface. The obtained results showed that the maximum gain of the antenna increased from 2.31 dBi to 7.5 dBi. A 30% increase in the bandwidth is also remarked. The proposed antenna with metasurface occupies an overall volume of 1.01λg×1.01λg×0.025λg. The simulation analysis and measured results were performed using the microwave studio, high frequency structure simulator software, and vector network analyzer. The proposed antenna prototype has been fabricated. The measured results indicate that the antenna has a good impedance matching in the desired operating band (2.37‐2.49 GHz) with the resonant frequency of 2.44 GHz which make the proposed antenna appropriate for microwave applications. [ABSTRACT FROM AUTHOR]