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The purpose of this paper is to compare the low‐cost switched‐beam antennas and the more expensive adaptive antennas in a wireless mesh network (WMN) scenario.

A mathematical framework is adopted in order to determine, for the two antenna systems, the number of sustainable simultaneous communications and the achievable throughput of a backbone WMN in a realistic outdoor environment.

The paper includes a thorough examination of benefits and crucial implementation issues concerning the adoption multiple antennas on mesh routers.

The paper investigates the relationship between the antenna system and the adopted channel coding technique, to determine the set‐up that may offer the best compromise between performance and complexity.

The purpose of this paper is to design and analyze the performance of live model of Bessel beamformer for thorough comprehension of beamforming in adaptive environment and compared with live model of least mean square (LMS) in terms of gain and mean square error (MSE). It presents the principal elements of communication system. The performance of designed live model is tested for its efficiency in terms of signal recovery, directive gain by minimizing MSE using the “wavrecord” function to bring live audio data in WAV format into the MATLAB workspace. These adaptive techniques are illustrated by appropriate examples.

The proposed algorithm framework relies on MATLAB software with the goal to obtain high efficiency in terms of signal recovery, directive gain by minimizing MSE using the “wavrecord” function to bring live audio data in WAV format. It is assumed that this audio signal is only the message or the baseband signal received by the computer. Here the authors consider computer (laptop) as a base station containing adaptive signal processing algorithm and source (mobile phone) as a desired user, so the experiment setup is designed for uplink application (user to base station) to differentiate between desired signal, multipath and interfering signals as well as to calculate their directions of arrival.

The presented adaptive live model is reliable, robust and lead to a substantial reduction of MSE, signal recovery in comparison with the LMS technique. The paper contains experimental data. Obtained results are presented clearly and the conclusion comes directly from the presented experimental data. The paper shows that the presented method leads to superior results in comparison with the popular LMS method and can be used as a better alternative in many practical applications.

The adaptive processes described in the paper are still limited to simulation. It is because of the non-availability of real system for testing, therefore chosen research approach that is platform of MATLAB is opted for simulation. Therefore, researchers are encouraged to test the proposed algorithms on real system if possible.

The paper contains experimental data. The paper's impact on the society is acceptable. These implications are consistent with the findings and the conclusions of the paper. However, there is a need to extend this paper to a next level by implementing the proposed algorithms in the real time environment using FPGA technology.

This research will improve the signal quality of wireless cellular system by increasing capacity and will reduce the total cost of the system so that cost toward subscribers be decreased.

The live model presented in this paper is shown to provide better results. It is the original work and can provide scientific contribution to signal processing community.

There can be little dispute that the UK, with its excellent science base, has the potential to take advantage of the opportunities arising from the increasing speed of scientific and technological advance. However, especially in more recent decades, this potential has been consistently wasted. The fact is that despite an almost unparalleled track record on invention, the transfer from invention to innovation has often not been achieved by UK businesses with the result that the economy has failed to reap the commercial rewards from these discoveries.

The purpose of this paper is to present the application of an efficient genetic algorithm to deal with the problem of computing the trade‐off curves for non‐uniform circular arrays. In order to answer questions related to the performance of the non‐uniform circular phased arrays, two criteria are considered to evaluate the design: the criteria of minimum main beam width and minimum side lobe level (SLL) during scanning.

The design of non‐uniform circular arrays is modeled as a multi‐objective optimization problem. The Non‐dominated Sorting Genetic Algorithm II (NSGA‐II) is employed as the methodology to solve the resulting optimization problem. This algorithm is considered to be one of the best evolutionary optimizer for multi‐objective problems. It is chosen for its ease of implementation and its efficiency for computation of non‐dominated ranks. The method is based on the survival of the fittest paradigm, where each individual in the population represents a feasible solution of the optimization problem being solved. The concept of fitness is adapted to take into account the concept of solution quality in multi‐objective problems. This evolutionary method can be used effectively for computing the trade‐off curves between the SLL and the main beam width.

The NSGA‐II algorithm can effectively compute the trade‐off curve of different non‐uniform circular arrays. The simulation results presented in this paper show design options that maintain a low SLL and main beam width without pattern distortion during beam steering. Moreover, these trade‐off curves provide a more realistic approach to the solution of the design problem.

The design problem is set to determine which are the best design configurations or separations between the antenna elements and the best amplitude excitations when a circular structure is employed. Owing to the complex feasible region and the non‐linear dependence of optimization criteria from the decision variables, simple traditional and more sophisticated mathematical programming approaches will lead us to local optimal solutions in the case we can apply them. To the best of our knowledge, this multi‐objective optimization problem has not dealt with before, when two or more conflicting design criteria are taken into account. Therefore, the solution to this problem constitutes the main contribution of our paper.

The purpose of this paper is to conduct the accurate analysis and systematic characterisation of realistic generalised bi‐isotropic and lossy chiral metamaterial 3D applications at microwave frequencies.

An accuracy‐adjustable time‐domain methodology is developed. The technique uses a convex combination of optimal stencils along with an advanced wavefield decomposition to precisely model the highly dispersive, double negative nature of chirality and constitutive parameters. Furthermore, open‐region radiation or scattering problems are terminated through a pertinently modified perfectly matched layer (PML) of variable depth.

The paper reveals that the proposed algorithm is versatile in the generation of adaptive stencils that attain a very natural way of manipulating continuity conditions at material interfaces. Thus, when periodic structures with split‐ring resonators are to be modelled, the resulting schemes attain optimal precision and minimised dispersion errors. Numerical validation proves these merits via diverse demanding structures of curved shape and multiple layers.

The new technique introduces a family of piecewise polynomials and spatial discretization criteria which lead to additional degrees of freedom for the discrete vectors of the application. In this manner, grid dual is intrinsically embedded in the physical profile of the problem, without resorting to the simplified conventions of other approaches. Moreover, singularity points or demanding geometric discontinuities are properly manipulated, even via coarse lattice resolutions. Thus, the overall accuracy is significantly improved and the computational requirements remain in very logical and affordable levels.

The aim of the paper is to propose three computer tools to create electromagnetic simulation programs: GiD, Kratos and EMANT.

The paper presents a review of numerical methods for solving electromagnetic problems and presentation of the main features of GiD, Kratos and EMANT.

The paper provides information about three computer tools to create electromagnetic simulation packages: GiD (geometrical modeling, data input, visualisation of results), Kratos (C++ library) and EMANT (finite element software for solving Maxwell equations).

The proposed platforms are in development and future work should be done to validate the codes for expecific problems and to provide extensive manual and tutorial information.

The tools could be easily learnt by different user profiles: from end‐users interested in simulation programs to developers of simulation packages.

This paper offers an integrated vision of open and easily customisable tools for the demands of different users profiles.

This research investigated the feasibility of using an inductively coupled antenna as the basis of applying a systems approach to smart clothing. In order to simulate real-life situations, the impact of the distortions and relative displacement of different fabric layers (with affixed antennas) on the signal quality was assessed. The paper aims to discuss these issues.

A spiral antenna was printed on different fabric substrates. Obstructive conditions of the inductively coupled fabric layers were investigated to find out how much influence these conditions had on transmission performance. Reflected signals and transmitted signals were observed, while fabric antennas were subjected to displacement (distance and dislocation) or deformation (stretching and bending). The threshold of physical obstacles was estimated based on statistical analyses.

The limits of physical conditions that enable proper wireless transmission were estimated up to ∼2 cm for both distance and dislocation, and ∼0.24 K for bending deformation. The antenna performance remained within an acceptable level of 20 percent transmission up to 10 percent fabric stretch. Based on well-established performance metrics used in clothing environment on the body, which employs 2-5 cm of ease, the results imply that the inductively coupled antennas may be suitable for use in smart clothing.

This research demonstrates that the use of inductively coupled antennas on multiple clothing layers could offer the basis of a new “wireless” system approach to smart clothing. This would not only result in performance benefits, but would also significantly improve the aesthetics of smart clothing which should result in new markets for such products.

This paper aims to present an innovative system able to establish an inter-satellite communication crosslink and to determine the mutual physical positioning for CubeSats belonging to a swarm.

Through a system involving a smart antenna array managed by a beamforming control strategy, every CubeSat of the swarm can measure the direction of arrival (DOA) and the distance (range) to estimate the physical position of the received signal. Moreover, during the transmission phase, the smart antenna shapes the beam to establish a reliable and directive communication link with the other spacecraft and/or with the ground station. Furthermore, the authors introduce a deployable structure fully developed at Politecnico di Torino that is able to increase the external surface of CubeSats: this surface allows to gain the interspace between elements of the smart antenna.

As a consequence, the communication crosslink, the directivity and the detection performance of the DOA system in terms of directivity and accuracy are improved.

Moreover, the deployable structure offers a greater usable surface, so a larger number of solar panels can be used. This guarantees up to 25 W of average power supply for the on-board systems and for transmission on a one-unit (1U) CubeSat (10 × 10 × 10 cm).

This paper describes the physical implementation of the antenna array system on a 1U CubeSat by using the deployable structure developed. Depending on actuators and ability that every CubeSat disposes, various interaction levels between elements can be achieved, thus making the CubeSat constellation an efficient and valid solution for space missions.

Optimization involves changing the input parameters of a process that is experimented with different conditions to obtain the maximum or minimum result. Increasing interest is shown by antenna researchers in finding the optimum solution for designing complex antenna arrays which are possible by optimization techniques.

Design of antenna array is a significant electro-magnetic problem of optimization in the current era. The philosophy of optimization is to find the best solution among several available alternatives. In an antenna array, energy is wasted due to side lobe levels which can be reduced by various optimization techniques. Currently, developing optimization techniques applicable for various types of antenna arrays is focused on by researchers.

In the paper, different optimization algorithms for reducing the side lobe level of the antenna array are presented. Specifically, genetic algorithm (GA), particle swarm optimization (PSO), ant colony optimization (ACO), cuckoo search algorithm (CSA), invasive weed optimization (IWO), whale optimization algorithm (WOA), fruitfly optimization algorithm (FOA), firefly algorithm (FA), cat swarm optimization (CSO), dragonfly algorithm (DA), enhanced firefly algorithm (EFA) and bat flower pollinator (BFP) are the most popular optimization techniques. Various metrics such as gain enhancement, reduction of side lobe, speed of convergence and the directivity of these algorithms are discussed. Faster convergence is provided by the GA which is used for genetic operator randomization. GA provides improved efficiency of computation with the extreme optimal result as well as outperforming other algorithms of optimization in finding the best solution.

The originality of the paper includes a study that reveals the usage of the different antennas and their importance in various applications.

The purpose of this paper is to present and solve the problem of adaptive beamforming (ABF) for a uniform linear array (ULA) as an optimization problem. ABF mainly concerns with estimation of weights of antenna array so as to direct the major lobe in the direction of desired user and nulls in the direction of interfering signals with reduced side lobe level (SLL).

The potential of gravitational search algorithm is explored to optimize multi-objective fitness function for ABF using MATLAB software.

The performance of the algorithm has been compared by considering different number of interference signals at different power levels. The proposed algorithm presents good convergence rate and accurate steering of main lobe and nulls with reduced SLL compared to the well-known ABF technique, namely, minimum variance distortionless response (MVDR) and previously reported results. The simulation results are presented in tabular form.

The present work is limited to simulation. The researchers are encouraged to solve the problem of ABF using the proposed approach in hardware.

The application of proposed algorithm is to optimize multi-objective function for ABF with reduced SLL in linear antenna arrays.