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This work proposes a modified circular fractal antenna array for multiband applications, including WLAN (5.15–5.85 GHz), C-band applications (3.8–4.4 GHz), and X-band for satellite communication (7.1–7.76 GHz). High Frequency Structure Simulator (HFSS) is used to simulate the antenna. The substrate material is FR4 epoxy, which has a 4.4 relative permittivity and 1.6 mm of thickness. It is discovered that the antenna only covers a portion of the bandwidth of the aforementioned applications.

the pilot contamination (PC) issue still faces and limits the promising massive MIMO (mMIMO) technology, to unleash the high benefits of mMIMO, we provide here a new decontaminating strategy, which exploits the large-scale fading coefficients' characteristics to construct a search space for the Ant colony-based optimization (ACO) algorithm. This algorithm is employed to find the best pattern in which each UE is linked to its most concurrent UEs of the adjacent cells; specifically, each UEs has an enemy UEs that if they are allocated with the same pilot, the severity of the PC upon the two UEs become subversive for the quality-of-service of the two UEs. Hence, the ACO algorithm finds for each UE its enemy UE, which leads to construct a Hamiltonian graph. This graph is exploited during the assignment of the pilot sequences to the overall UEs; specifically, the linked UEs are successively allocated with the available OPSs, which leads to address the PC problem within multi-cell mMIMO systems.

This paper proposes a compact 2*1 reader array antenna for RFID system having high directivity, good gain, and good reflection coefficient. The structure consists of two main radiating rectangular patch antennas connected in parallel with a common impedance of (50 Ω). These patches are printed on an RT/duroid 5880 substrate possessing a dielectric constant εr equal to 2.2 and 0.0009 as a loss tangent. It operates in ISM (Industrial, Scientific and Medical) band with a resonant frequency of 5.8 GHz. The structure is implemented on a compact size of 38.77× 59.44× 1.6 mm3 equivalent to an electrical size of 0.74λ0× 1.14λ0× 0.03λ0, where λ0 is the free-space wavelength at the resonant frequency. The gain achieved by the final design of the proposed antenna is equal to 9.83 dB, the directivity is around 9.99 dB and the coefficient of reflection (S11) is equal to -49.48 dB. The proposed antenna design is optimized and simulated using Computer Simulation Technology software (CST Microwave Studio).

Channel estimation (CE) is an important process that is done during the pilot transmission phase in each base station. This work addresses this process for the massive multiple-input multiple-output systems by studying the scenario where the channels are spatially correlated. Throughout this work, the spatial correlation between channels is modeled using the exponential correlation model. The minimum mean square error (MMSE) estimator’s performance for uncorrelated and correlated channels is compared and examined using the normalized mean square error (NMSE) metric, where the correlated scenario is presented through two array designs, namely proposed uniform planar array (UPA) and uniform linear array (ULA). In comparison to the uncorrelated situation, the correlated channels scenario is a more practical scenario that represents the real- world environment and provides superior channel estimate quality since the spatial correlation is advantageous for CE. Hence, we proposed a proposed UPA arrangement for correlated channels based on the Kronecker product of the ULA arrangement that outperforms the ULA arrangement and offers superior performance comparedto ULA. Numerical results are offered in order to support our analytical study.

Historically, power grids have emerged as the most economical way to match diversified generation resources. After the Second World War, all advanced countries chose to develop a centralized electrical system to transport energy throughout the national territory and then distribute it to the various points of consumption. In this centralized management, production is adapted to an ever-increasing demand, driven by economic and demographic developments. Gradually, the consumption profile has changed: the development of electrical uses (particularly heating and air conditioning), leading to consumption peaks that are increasingly difficult to satisfy. The appearance of the electric vehicle reinforces these growing imbalances between supply and demand. Thus, the production profile has gradually changed: production has moved closer to the places of consumption but has become more variable, such as wind and solar energy (known as intermittent sources of energy production). In this transforming energy view, these historical centralized and unidirectional networks reach saturation and need to be modernized by turning to a decentralized model. In this perspective, the development of smart grids (SG) is taking place. This paper aims to define decentralized energy systems that provide various benefits and cause significant challenges. Finally, we propose several techniques that are highly efficient in modeling and controlling smart grid systems in order to help decision-makers to address complex problems.

This research proposes a compact tag antenna for Radio Frequency Identification (RFID) which provides two bands of operation at 2.3-2.5 GHz and 5.78-6 GHz. The tag antenna structure consists of two meander lines connected with an inductive loop of the metamaterial. This design topology offers benefits such as achieving multi-band, good impedance matching and radiation pattern at resonant frequencies. The design has a small size of 16 x 23 x 1.6 mm³. The suggested tag antenna is produced on top of the FR4 substrate having εr = 4.3 and tanδ = 0.022. The tag antenna has a maximum gain of 2.14 dBi and 3.22 dBi at the resonant frequencies of 2.45 GHz and 5.8 GHz, respectively. The study of the suggested tag antenna with the human body, solution bag, and bandage is presented. In addition, the proposed tag antenna has good performance and supports two bands of operation, which confirms its suitability for RFID technology and remote healthcare applications. [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]