scholarly journals MULTIBAND MILLIMETER WAVE T-SHAPED ANTENNA WITH OPTIMIZED PATCH PARAMETER USING PARTICLE SWARM OPTIMIZATION

2017 ◽  
Vol 36 (3) ◽  
pp. 904-909
Author(s):  
AH Jabire ◽  
A Abdu ◽  
S Salisu
Keyword(s):  
Particle Swarm Optimization ◽  
Millimeter Wave ◽  
Patch Antenna ◽  
Return Loss ◽  
Particle Swarm ◽  
Impedance Bandwidth ◽  
Electromagnetic Spectrum ◽  
Radiation Characteristics ◽  
Swarm Optimization ◽  
High Frequency Structure Simulator

This paper proposed a simple T-shaped patch antenna for millimeter waveband frequency operation. Millimeter wave is a frequency ranges between 30GHz to 300GHz in an electromagnetic spectrum. The proposed antenna consists of T-shape radiating patch mounted on rectangular substrate (FR4-4) and microstrip line for antenna feeding. An evolutionary algorithm called particle swarm optimization was used to optimize the length and width of the proposed antenna patch. The proposed antenna gives triple bands with central frequencies at 42GHz, 51.5GHz and 60GHz. The antenna offers minimum return loss of -19db, -24db and -19.5db at 42GHz, 51.5GHz and 60GHz respectively. The return loss impedance bandwidth of 5GHz for the first band, 8.4GHz for the second band and 5GHz for the third band was obtained. The proposed antenna was analyzed using Ansoft High Frequency Structure Simulator (HFSS) and MATLAB 2013. Radiation characteristics of this patch antenna are observed at various resonating frequencies.  http://dx.doi.org/10.4314/njt.v36i3.33

scholarly journals Particle Swarm Optimization for Antenna Designs in Engineering Electromagnetics

2008 ◽  
Vol 2008 ◽  
pp. 1-10 ◽  
Author(s):  
Nanbo Jin ◽  
Yahya Rahmat-Samii
Keyword(s):  
Particle Swarm Optimization ◽  
Patch Antenna ◽  
Ground Plane ◽  
Particle Swarm ◽  
Dual Band ◽  
Radiation Characteristics ◽  
Swarm Optimization ◽  
Multiobjective Problems ◽  
Wave Antenna ◽  
Measurement Results

This paper presents recent advances in applying particle swarm optimization (PSO) to antenna designs in engineering electromagnetics. By linking the PSO kernel with external electromagnetic (EM) analyzers, the algorithm has the flexibility to handle both real and binary variables, as well as multiobjective problems with more than one optimization goal. Three examples, including the designs of a dual-band patch antenna, an artificial ground plane of a surface wave antenna, and an aperiodic antenna array, are presented. Both simulation and measurement results are provided to illustrate the effectiveness of applying the swarm intelligence to design antennas with desired frequency response and radiation characteristics for practical EM applications.

scholarly journals Design of a Single Band Microstrip Patch Antenna for 5G Applications

2018 ◽  
Vol 7 (2.7) ◽  
pp. 532 ◽  
Author(s):  
R Siri Chandana ◽  
P Sai Deepthi ◽  
D Sriram Teja ◽  
N Veera JayaKrishna ◽  
M Sujatha
Keyword(s):  
Millimeter Wave ◽  
Patch Antenna ◽  
Return Loss ◽  
Dielectric Substrate ◽  
Microstrip Patch Antenna ◽  
Single Band ◽  
Wave Frequency ◽  
High Frequency Structure Simulator ◽  
Microstrip Patch ◽  
Simulation Purpose

This article is about a single band microstrip patch antenna used for the 5G applications. And this antenna is suitable for the millimeter wave frequency. The patch antenna design consists of 2 E shaped slots and 1 H shaped slot. These slots are loaded on the radiating patch with the 50 ohms microstrip feed line. For the simulation purpose, Rogers’s RT5880 dielectric substrate with relative permittivity of 2.2 and loss tangent of 0.0009 is used. The design and simulation of the antenna is done using HFSS (High Frequency Structure Simulator) software. The results are simulated for the parameters Return loss, VSWR, 3D Radiation pattern. The proposed antenna has a return loss of -42.4383 at 59 GHz millimeter wave frequency. 

scholarly journals A Square Patch with L and Inverted L shaped slotted AMC structure for Wi-Fi Applications

2020 ◽  
Vol 9 (1) ◽  
pp. 1722-1725
Keyword(s):  
Resonant Frequency ◽  
Patch Antenna ◽  
High Frequency ◽  
Return Loss ◽  
Band Width ◽  
Magnetic Conductor ◽  
Radiation Characteristics ◽  
Artificial Magnetic Conductor ◽  
High Frequency Structure Simulator ◽  
Phase Reflection

To improve the antenna characteristics in terms of bandwidth, gain and its radiation characteristics without providing any phase reflections, Artificial Magnetic Conductor (AMC) are used in antenna designing. This paper initially designed AMC structure for 2.4GHz frequency. The proposed AMC structure consists of three L shaped and inverted L shaped slots and provides zero degrees phase reflection at 2.4GHz resonant frequency. This proposed AMC structure is incorporated on conventional micro strip square patch antenna and results are simulated in High Frequency Structure Simulator (HFSS) software. The Proposed AMC incorporated patch antenna, return loss is improved from -16.16dB to -31.75dB, VSWR is from 1.42 to 1.05, the band width is increased from 16.5 MHz to 348.1 MHz This design resonates at a frequency of 2.4GHz and applicable to Wi-Fi applications.

scholarly journals Particle Swarm Optimization Based Beamforming in Massive MIMO Systems

2020 ◽  
Vol 14 (05) ◽  
pp. 176
Author(s):  
Thaar A. Kareem ◽  
Maab Alaa Hussain ◽  
Mays Kareem Jabbar
Keyword(s):  
Particle Swarm Optimization ◽  
Millimeter Wave ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Particle Swarm ◽  
Optimal Performance ◽  
Achievable Rate ◽  
Swarm Optimization ◽  
Transmit Precoding

<p>This research puts forth an optimization- based analog beamforming scheme for millimeter-wave (mmWave) massive MIMO systems. Main aim is to optimize the combination of analog precoder / combiner matrices for the purpose of getting near-optimal performance. Codebook-based analog beamforming with transmit precoding and receive combining serves the purpose of compensating the severe attenuation of mmWave signals. The existing and traditional beamforming schemes involve a complex search for the best pair of analog precoder / combiner matrices from predefined codebooks. In this research, we have solved this problem by using Particle Swarm Optimization (PSO) to find the best combination of precoder / combiner matrices among all possible pairs with the objective of achieving near-optimal performance with regard to maximum achievable rate. Experiments prove the robustness of the proposed approach in comparison to the benchmarks considered. <strong></strong></p><p class="IndexTerms"> </p>

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