Social Network Optimization Based Procedure for Beam-Scanning Reflectarray Antenna Design

Niccolai, Alessandro; Beccaria, Michele; Zich, R.E.; Massaccesi, Andrea; Pirinoli, Paola

doi:10.1109/ojap.2020.3022935

Cited by 20 publications

(9 citation statements)

References 54 publications

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“…In summary, Table 4 compares the introduced antenna design's performance with other published works [14][15][16][17][18][19][20][21]. As can be seen, this work meets the objective of steering the main beam in any direction in the horizontal plane.…”

Section: S 11 and Radiation Pattern Of Array With Rf Beamformermentioning

confidence: 86%

“…However, this research investigates antenna array configurations rather than focusing on the performance of analog beamforming or antenna design. Many researchers investigate analog beamforming algorithms in terms of array performance [14][15][16][17][18][19][20][21]. To date, there has been a lack of discussion in terms of the hardware implementation of the effectiveness of the proposed methods by the measurement results.…”

Section: Introductionmentioning

confidence: 99%

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Analysis, Optimization, and Hardware Implementation of Dipole Antenna Array for Wireless Applications

Malek

Seager

Flint

et al. 2022

International Journal of Antennas and Propagation

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The antenna pattern synthesis is one of the significant problems in the phased array antenna. Pattern synthesis refers to the optimized weight excitation of each antenna element in order to steer the beam electronically without mechanically rotating the antenna. It can be achieved by using a combination of phase shifters and attenuator circuits. In this paper, a 2 by 2 dipole antennas with an RF beamforming circuit has been designed to steer the main beam along the azimuth plane. The main beam coverage from 100° to 140° with a step size of 10° has been successfully optimized using a hybrid of the induced EMF method and a genetic algorithm. The optimization results were compared to the full-wave simulation technique implemented in Empire XCCel. The design is realistically implemented at 2.45 GHz, with both simulation and measurement results shown. The measured reflection coefficient of the phased array antenna is −48 dB at 2.56 GHz. The feasibility of the beam synthesis has been validated successfully with the main beam being steered at 110°. The possibility of a fabrication discrepancy resulting in minor radiation degradation is also discussed in this research. The dipole antenna system with RF beamformer circuit can be applied to indoor positioning systems such as Wi-Fi, wireless local area network (WLAN), and fifth-generation.

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Section: S 11 and Radiation Pattern Of Array With Rf Beamformermentioning

confidence: 86%

Section: Introductionmentioning

confidence: 99%

Analysis, Optimization, and Hardware Implementation of Dipole Antenna Array for Wireless Applications

Malek

Seager

Flint

et al. 2022

International Journal of Antennas and Propagation

View full text Add to dashboard Cite

show abstract

“…This property can be effectively adopted in evolutionary optimization algorithms, where the influence of different agents has to be considered dealing with complex solution spaces, where often counterintuitive solutions stand [11]. Furthermore, the hybridization of quantum properties and evolutionary inspired approaches looks very promising to overcome most of the state of the art limits in electromagnetic optimization [6].…”

Section: Introductionmentioning

confidence: 99%

Insights on Quantum Computing Operators for EM Optimization

Zich,

Zich

2023

Proceedings of the XXXVth URSI General Assembly and Scientific Symposium – GASS 2023

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The introduction of quantum computing is right now dramatically impacting the research activities in many engineering fields, in particular where a lot of data have to be considered, stored, analyzed to find the best possible strategy to tackle a complex problem, such as dealing with electromagnetic (EM) optimization. In fact, EM problems are critical from a computational point of view, because they often require thousands of different numerical solutions that can be obtained by extremely time and resource consuming numerical solvers both in the frequency or in the time domain.In this framework, the combined application of quantum computing and evolutionary optimization algorithms can have a great effectiveness to manage the electromagnetic optimization of complex structures.

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“…The authors in [21] presented the design of a multiband microstrip patch antenna that was generated with the assistance of the coyote optimization algorithm. A social network optimization method for beam-scanning reflectarray antenna design was presented in [22]. The method was used for optimizing the various antenna radiation patterns, as well as minimizing the difference between the desired and actual radiation direction.…”

Section: Introductionmentioning

confidence: 99%

Drone-Base-Station for Next-Generation Internet-of-Things: A Comparison of Swarm Intelligence Approaches

Pliatsios

Goudos

Λάγκας

et al. 2022

IEEE Open J. Antennas Propag.

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The emergence of next-generation internet-of-things (NG-IoT) applications introduces several challenges for the sixth-generation (6G) mobile networks, such as massive connectivity, increased network capacity, and extremely low-latency. To countermeasure the aforementioned challenges, ultra-dense networking has been widely identified as a possible solution. However, the dense deployment of base stations (BSs) is not always possible or cost-efficient. Drone-base-stations (DBSs) can facilitate network expansion and efficiently address the requirements of NG-IoT. In addition, due to their flexibility, they can provide on-demand connectivity in emergency scenarios or address temporary increases in network traffic. Nevertheless, the optimal placement of a DBS is not a straightforward task due to the limited energy reserves and the increased signal quality degradation in air-to-ground links. To this end, swarm intelligence approaches can be attractive solutions for determining the optimal position of the DBS in the three-dimensional (3D) space. In this work, we explore well-known swarm intelligence approaches, namely the Cuckoo Search (CS), Elephant Herd Optimization (EHO), Grey Wolf Optimization (GWO), Monarch Butterfly Optimization (MBO), Salp Swarm Algorithm (SSA), and Particle Swarm Optimization (PSO) and investigate their performance and efficiency in solving the aforementioned problem. In particular, we investigate the performance of three scenarios in the presence of different swarm intelligence approaches. Additionally, we carry out non-parametric statistical tests, namely the Friedman and Wilcoxon tests, in order to compare the different approaches.

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Social Network Optimization Based Procedure for Beam-Scanning Reflectarray Antenna Design

Cited by 20 publications

References 54 publications

Analysis, Optimization, and Hardware Implementation of Dipole Antenna Array for Wireless Applications

Analysis, Optimization, and Hardware Implementation of Dipole Antenna Array for Wireless Applications

Insights on Quantum Computing Operators for EM Optimization

Drone-Base-Station for Next-Generation Internet-of-Things: A Comparison of Swarm Intelligence Approaches

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