Planar arrays synthesis for optimal wireless power transmission

Li, Xun; Zhou, Jinzhu; Du, Xiaolin

doi:10.1587/elex.12.20150346

Cited by 20 publications

(15 citation statements)

References 14 publications

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“…It is obvious that CPSO algorithm outperforms PSO algorithm, and less than 500 iterations are needed for the CPSO to converge to its final value. To further compare their performance, the problem presented in [11] is solved by the CPSO algorithm, and CSL constraint is added. Higher BCE and lower CSL can be obtained, which further shows the superior of the CPSO algorithm.…”

Section: Numerical Analysis and Discussionmentioning

confidence: 99%

“…The minimum element spacing d c between adjacent elements is guaranteed by (11). The constraint of CSL is ensured in (12).…”

Section: Problem Formulationmentioning

confidence: 99%

“…It can be used to overcome the drawback mentioned above. Previous work has been done to optimize element positions of isophoric planar array [11] to obtain the optimal BCE. However, the minimum element spacing and CSL constraints are not taken into consideration.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Planar Array Synthesis for Optimal Microwave Power Transmission With Multiple Constraints

Duan

Zhou

et al. 2017

Antennas Wirel. Propag. Lett.

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This paper describes a synthesis method of uniformly excited unequally spaced planar array with maximum beam collection efficiency (BCE) based on Chaotic Particle Swarm Optimization (CPSO) algorithm. And here the multiple optimization constrains include the number of array elements, the aperture, the minimum element spacing, and the maximum sidelobe level (SLL) outside the receiving region. Through this method, feeding network of the array becomes simple and compact. Effectiveness of the proposed method is validated by comparing the simulation results obtained in this paper to those reported in the state-of-the-art literature.Index Terms-Antenna arrays, microwave power transmission, chaotic particle swarm optimization, solar power satellite.

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Section: Numerical Analysis and Discussionmentioning

confidence: 99%

“…The minimum element spacing d c between adjacent elements is guaranteed by (11). The constraint of CSL is ensured in (12).…”

Section: Problem Formulationmentioning

confidence: 99%

See 1 more Smart Citation

Planar Array Synthesis for Optimal Microwave Power Transmission With Multiple Constraints

Duan

Zhou

et al. 2017

Antennas Wirel. Propag. Lett.

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“…However, energy radiation capacity of the power beam is improved without considering the energy cost of each node. In Li et al, 32 a PSO-based optimization algorithm for WPT is presented. The improvement of the energy collection efficiency in the power pattern is achieved by optimizing the node spacing, but the node weight is not optimal.…”

Section: Related Workmentioning

confidence: 99%

Energy-efficient collaborative transmission algorithm based on potential game theory for beamforming

Zhang

Feng

2019

International Journal of Distributed Sensor Networks

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A group of collaborative nodes can efficiently complete spatial long-distance transmission tasks using beamforming technology. However, a high sidelobe level interferes with communication quality, and uneven energy consumption of nodes affects network lifetime. This paper proposes an energy-efficient collaborative transmission algorithm based on potential game theory for beamforming. First, the minimum number of cooperative nodes is determined in accordance with the energy consumption and spacing limitation condition. A group of nodes satisfying the node spacing condition is selected as cooperative nodes based on the ring array to minimize communication interference among nodes. Second, a potential game model is proposed as a joint method for optimizing the collaborative parameters of the cooperative nodes and their energy consumption balancing features. Finally, the game process is continuously executed until the Nash equilibrium is reached. According to simulation results, the sidelobe level caused by the cooperative nodes is reduced and the transmission conflicts are lessened. Thus, the quality of communication links in between nodes in the network is improved. Energy efficiency is also promoted because a balancing of energy consumption is involved in the proposed potential game model, and network lifetime is effectively prolonged accordingly.

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“…Two important factors that are the transmission distance and the energy efficiency should be considered in the RF-based WPT system [1]. Thus, to enhance the transmission distance while keeping a certain level receiving efficiency has been taken into account [5]. For improving the receiving efficiency, most current research commit to improve the RF-to-DC conversion efficiency of the receiving antenna.…”

Section: Introductionmentioning

confidence: 99%

Suppressing Sidelobe Level of the Planar Antenna Array in Wireless Power Transmission

et al. 2019

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The power pattern synthesis, as well as the sidelobe level (SLL) suppression of the planar antenna arrays for the wireless power transmission is investigated. An improved chicken swarm optimization (ICSO) algorithm is proposed for reducing the maximum SLL of the power pattern. ICSO introduces the global search, the local search, and the duplicate solution removing operators to enhance the accuracy and the convergence rate of the conventional CSO algorithm, thereby making it suitable for the power pattern optimizations. Simulations are conducted to verify the performance of the proposed algorithm, and the results show that ICSO obtains the lowest maximum SLL compared with other algorithms. Moreover, the power pattern performances of different algorithms are tested by the electromagnetic simulations, and the results show that the proposed ICSO has the best optimization ability. INDEX TERMS Wireless power transmission, power pattern, energy beamforming, sidelobe level, chicken swarm optimization. III. SYSTEM MODEL, ARRAY FACTOR AND PROBLEM DESCRIPTION A. SYSTEM MODEL AND ARRAY FACTOR GUOJUN SHEN received the B.S. degree in computer science from Jilin University, China, in 2015, where he is currently pursuing the M.S. degree in computer science. His research interests include wireless communication and optimizations. YANHENG LIU received the M.Sc. and Ph.D. degrees in computer science from Jilin University, China, where he is currently a Professor. His primary research interests include network security, network management, mobile computing network theory, and applications. GENG SUN (S'17) received the B.S. degree in communication engineering from Dalian Polytechnic University, in 2007, and the Ph.D. degree in computer science and technology from Jilin University, in 2018. He was a Visiting Researcher with the School of Electrical and Computer Engineering, Georgia Institute of Technology, USA. He currently holds a Postdoctoral position with Jilin University. His research interests include wireless sensor networks, antenna arrays, collaborative beamforming, and optimizations. TINGTING ZHENG received the B.S. degree in computer science from Jilin University, China, in 2017, where she is currently pursuing the Ph.D. degree in computer science. Her research interests include wireless communications and optimizations. XU ZHOU received the M.S. degree from Northeast Normal University, in 2013, and the Ph.D. degree from Jilin University, in 2016, where she currently holds a Postdoctoral position. Her research interests include intelligent algorithms, data mining, and complex network analysis. AIMIN WANG received the Ph.D. degree in communication and information system from Jilin University, where he is currently an Associate Professor. His research interests include wireless sensor networks and QoS for multimedia transmission.

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Planar arrays synthesis for optimal wireless power transmission

Cited by 20 publications

References 14 publications

Planar Array Synthesis for Optimal Microwave Power Transmission With Multiple Constraints

Planar Array Synthesis for Optimal Microwave Power Transmission With Multiple Constraints

Energy-efficient collaborative transmission algorithm based on potential game theory for beamforming

Suppressing Sidelobe Level of the Planar Antenna Array in Wireless Power Transmission

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