Optimal design of planar terahertz Yagi-Uda antenna using adaptive chaos optimization algorithm

Megahed, A.; Shaker, Ahmed; Mahmoud, Korany R.

doi:10.1016/j.ijleo.2019.05.103

Cited by 5 publications

(2 citation statements)

References 15 publications

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“…It is worth mentioning that the CEU is a user that experiences less relative received signal strength from the two BSs, and therefore, it experiences a strong ICI from the adjacent cells. Furthermore, supposing that each BS has been provided with N Uniform Planar Array (UPA) antenna elements, 43,44 and the CEU has one antenna for transmission and reception.…”

Section: Achievable Data Rate Analysismentioning

confidence: 99%

Deep learning‐assisted reconfigurable intelligent surface for enhancing 6G mobile networks

Megahed,

Elmesalawy,

Ibrahim

et al. 2023

Trans Emerging Tel Tech

Self Cite

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This article presents the role of Reconfigurable Intelligent Surface (RIS) using the Multi‐Input Multi‐Output (MIMO) technique as the enabling technology to boost the achievable data rate for mobile networks of the sixth generation (6G). The RIS has been adopted to mitigate the interference at the Cell Edge User (CEU) placed where two adjacent cells are separated. That is by reflecting the incident interference signal in the CEU direction out of phase with the basic interference signals coming from the interfering BS towards the CEU. This article adopts an efficient solution for designing the RIS redirecting (reflection) matrix with trivial training overhead using Deep Learning (DL) technology. Whereas a few of the reflecting elements in RIS are chosen to be active (attached to the baseband), whilst the majority are chosen to be passive, in which the active element's channels are known and used as medium indicators and indicate further the positions of the transmitter and receiver. This article illustrated the efficacy of the adopted framework with DL, by changing the training parameters regarding the data rates that can be achieved, the Spectral Energy Efficiency (SEE), and the Satisfaction Rate (SR). As a result, the proposed model improves the achievable data rate by a near average of 97% above the reference model. Furthermore, it enhances the achievable data rate above the baseline model that assumes no RIS used by an average of 115%. Therefore, The DL method demonstrated that the proposed model is promising for enhancing 6G Mobile Networks.

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Section: Achievable Data Rate Analysismentioning

confidence: 99%

Deep learning‐assisted reconfigurable intelligent surface for enhancing 6G mobile networks

Megahed,

Elmesalawy,

Ibrahim

et al. 2023

Trans Emerging Tel Tech

Self Cite

View full text Add to dashboard Cite

show abstract

“…Recently, the mathematics of chaos theory has been used to improve various optimization methods. So, most researchers incorporate chaotic maps with the optimization techniques in order to get the global solutions of complex problems [53][54][55] and accelerate the convergence to the optimal solution such as adaptive firefly algorithm with chaos [56], Chaosenhanced cuckoo search optimization algorithm [57], chaos game optimization [58], chaos grasshopper optimization algorithm [59], chaotic fruit fly optimization algorithm [60] and chaos-enhanced bat algorithm [61].…”

Section: Introductionmentioning

confidence: 99%

Steady-State Sine Cosine Genetic Algorithm Based Chaotic Search for Nonlinear Programming and Engineering Applications

2020

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This paper proposes a newly meta-heuristic approach, steady-state sine cosine genetic algorithm-based chaotic search, for solving nonlinear programming and engineering applications. It is a combination of sine cosine approach (SCA), steady-state genetic algorithm (SSGA), and chaotic search (CS), and named as chaos-enhanced SCA with SSGA. The proposed approach integrates SSGA's exploitation ability and SCA's exploration ability and local search capability of CS. The performance of the new approach works in two different stages. Firstly, SCA and SSGA start together to increase exploration capability and exploitation tendencies. Secondly, CS used to improve the approximate solution obtained from the first stage and reach the global solution. Hence, the proposed new approach will be more robust as it avoids trapping into local minima in addition to the speed of the search process and rapid convergence towards the global solution. The efficiency of the proposed approach is verified by using it to solve 32 wellknown benchmark problems and different engineering design problems. Simulation results show that the proposed approach is competitive and better in most cases as a comparison to others. INDEX TERMS Chaos search, Hybrid approach, Nonlinear programming problems, Engineering Applications, Optimization.

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Vivaldi antenna for early cancer detection based on THz spectroscopy: Comparison between response of breast and skin cancer

Toolabi

Khatir

Naser‐Moghadasi

et al. 2023

Optik

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Optimal design of planar terahertz Yagi-Uda antenna using adaptive chaos optimization algorithm

Cited by 5 publications

References 15 publications

Deep learning‐assisted reconfigurable intelligent surface for enhancing 6G mobile networks

Deep learning‐assisted reconfigurable intelligent surface for enhancing 6G mobile networks

Steady-State Sine Cosine Genetic Algorithm Based Chaotic Search for Nonlinear Programming and Engineering Applications

Vivaldi antenna for early cancer detection based on THz spectroscopy: Comparison between response of breast and skin cancer

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