Fig 7 - available from: EURASIP Journal on Wireless Communications and Networking
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Massive multiple input multiple output antenna array is crucial for the fifth generation wireless communication. Proper antenna array design can reduce interference among different signals and generate desirable beamforming. Sparse antenna array is able to form narrower beam with lower sidelobe than equally spaced antenna array given the same numbe...
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Through the lens of memetic folk humor, this essay examines the slippery, ephemeral nature of hybridized forms of contemporary digital folklore. In doing so, it is argued that scholars should not be distracted by the breakneck speed in which expressive materials proliferate and then dissipate but should instead focus on the overarching ways that po...
In this work, a coevolving memetic particle swarm optimization (CoMPSO) algorithm is presented. CoMPSO introduces the memetic evolution of local search operators in particle swarm optimization (PSO) continuous/discrete hybrid search spaces. The proposed solution allows one to overcome the rigidity of uniform local search strategies when applied to...
Citations
This paper presents an optimization approach for static antenna array thinning using a genetic algorithm (GA). The goal is to reduce hardware complexity while maintaining a radiation pattern similar to that of a fully populated uniform linear array (ULA). The proposed method statically deactivates a specific percentage of the array elements, achieving the desired hardware complexity reduction. Furthermore, a previously proposed algorithm for compensating the beam squint effect in a hybrid beamforming architecture, initially tested on a ULA, is applied to the thinned array, demonstrating its effectiveness on non-uniformly distributed arrays.
Integrated optical phased arrays (OPAs) play an important role in a broad range of applications. Fabrication constraints, however, pose a limit to the minimum inter-element separation that further results in high-intensity side lobes. The intensity of these secondary lobes can be reduced by arranging the antenna elements with non-uniform separation distance, which has been addressed by different methods. In this paper we employ one of the already proven optimization algorithms, i.e., differential evolution, to optimize the element positions of linear arrays with different configurations operating under beam-steering operation and considering a minimum inter-element distance. These optimizations allowed us to derive some design guidelines that can assist in reducing the side-lobe level (SLL) of integrated linear OPAs. In particular, we found that it is necessary to optimize the positions for the broadest beam-steering angle and the shortest operation wavelength. Additionally, optimizations of different configurations reveal that, when imposing a minimum inter-element distance, there is an optimum mean distance that minimizes the SLL of the array.
One of the ultimate goals of future wireless networks is to maximize data rates to accommodate bandwidth-hungry services and applications. Thus, extracting the maximum amount of information bits for given spatial constraints when designing wireless systems will be of great importance. In this paper, we present antenna array topologies that maximize the communication channel capacity for given number of array elements while occupying minimum space. Capacity is maximized via the development of an advanced particle swarm optimization (PSO) algorithm devising optimum standardized and arbitrarily-shaped antenna array topologies. Number of array elements and occupied space are informed by novel heuristic spatial degrees of freedom (SDoF) formulations which rigorously generalize existing SDoF formulas. Our generalized SDoF formulations rely on the differential entropy of three-dimensional (3D) angle of arrival (AOA) distributions and can associate the number of array elements and occupied space for any AOA distribution. The proposed analysis departs from novel closed-form spatial correlation functions (SCFs) of arbitrarily-positioned array elements for all classes of 3D multipath propagation channels, namely, isotropic, omnidirectional, and directional. Extensive simulation runs and comparisons with existing trivial solutions verify correctness of our SDoF formulations resulting in optimum antenna array topologies with maximum capacity performance and minimum space occupancy.
To satisfy the increasing requirements of big data transmission, mutual interference and wide band, the optimal design of antenna and antenna array has drawn great interests and attentions of researchers. This paper summarizes and classifies state-of-the-art optimal antenna designs by using evolutionary computing (EC) methods. Antenna designs are classified based on three aspects. First, based on array type, they are divided into single antenna design, linear array design and planar array design. Second, based on the number of optimization objectives, they are divided into single objective, bi-objective, and three objective methods. Third, approaches are divided based on real world scenarios. Furthermore, a benchmark is built for the designs of linear antenna array and planar antenna array. Such benchmark can be used as baseline to assist researchers to verify or create more powerful EC methods. Simulation results show that the benchmark is scalable and reliable for testing the performance of EC methods.KeywordAntenna designSurveyBenchmarkEvolutionary computing
This chapter reviews applications of Memetic Algorithms in the areas of business analytics and data science. This approach originates from the need to address optimization problems that involve combinatorial search processes. Some of these problems were from the area of operations research, management science, artificial intelligence and machine learning. The methodology has developed considerably since its beginnings and now is being applied to a large number of problem domains. This work gives a historical timeline of events to explain the current developments and, as a survey, gives emphasis to the large number of applications in business and consumer analytics that were published between January 2014 and May 2018.
The technology of wireless power transfer (WPT) has broad applications especially in implantable biomedical devices. Because of the limitation of the size of the receiver coil, how to lengthen the power transfer distance is crucial in biomedical applications. In order to address this problem, in this paper, a novel three-coil WPT system is proposed and analyzed. In the system, there are two transmitter coils and one receiver coil. Based on the Biot–Savart’s law, the electromagnetic property of the square coil is analyzed using finite element method. Moreover, the structural design of the system is optimized by a memetic algorithm. The memetic algorithm combines features of the artificial bee colony method and the covariance matrix adaption evolutionary strategy method. The simulation and experiment results show that the receiver coil can receive about dozens of millivolt when the power transfer distance is about 15 cm. This means the proposed system is suitable for implantable biomedical devices. Compared with the two-coil WPT system, in addition, the power received in the receiver coil of three-coil WPT system can increase about 48%.
