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A Novel Modified Sparrow Search Algorithm with Application in Side Lobe Level Reduction of Linear Antenna Array
Antenna arrays play an increasingly important role in modern wireless communication systems. However, how to effectively suppress and optimize the side lobe level (SLL) of antenna arrays is critical for communication performance and communication capabilities. To solve the antenna array optimization...
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Published in: | Wireless communications and mobile computing 2021, Vol.2021 (1) |
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description | Antenna arrays play an increasingly important role in modern wireless communication systems. However, how to effectively suppress and optimize the side lobe level (SLL) of antenna arrays is critical for communication performance and communication capabilities. To solve the antenna array optimization problem, a new intelligent optimization algorithm called sparrow search algorithm (SSA) and its modification are applied to the electromagnetics and antenna community for the first time in this paper. Firstly, aimed at the shortcomings of SSA, such as being easy to fall into local optimum and limited convergence speed, a novel modified algorithm combining a homogeneous chaotic system, adaptive inertia weight, and improved boundary constraint is proposed. Secondly, three types of benchmark test functions are calculated to verify the effectiveness of the modified algorithm. Then, the element positions and excitation amplitudes of three different design examples of the linear antenna array (LAA) are optimized. The numerical results indicate that, compared with the other six algorithms, the modified algorithm has more advantages in terms of convergence accuracy, convergence speed, and stability, whether it is calculating the benchmark test functions or reducing the maximum SLL of the LAA. Finally, the electromagnetic (EM) simulation results obtained by FEKO also show that it can achieve a satisfactory beam pattern performance in practical arrays. |
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However, how to effectively suppress and optimize the side lobe level (SLL) of antenna arrays is critical for communication performance and communication capabilities. To solve the antenna array optimization problem, a new intelligent optimization algorithm called sparrow search algorithm (SSA) and its modification are applied to the electromagnetics and antenna community for the first time in this paper. Firstly, aimed at the shortcomings of SSA, such as being easy to fall into local optimum and limited convergence speed, a novel modified algorithm combining a homogeneous chaotic system, adaptive inertia weight, and improved boundary constraint is proposed. Secondly, three types of benchmark test functions are calculated to verify the effectiveness of the modified algorithm. Then, the element positions and excitation amplitudes of three different design examples of the linear antenna array (LAA) are optimized. The numerical results indicate that, compared with the other six algorithms, the modified algorithm has more advantages in terms of convergence accuracy, convergence speed, and stability, whether it is calculating the benchmark test functions or reducing the maximum SLL of the LAA. Finally, the electromagnetic (EM) simulation results obtained by FEKO also show that it can achieve a satisfactory beam pattern performance in practical arrays.</description><identifier>ISSN: 1530-8669</identifier><identifier>EISSN: 1530-8677</identifier><identifier>DOI: 10.1155/2021/9915420</identifier><language>eng</language><publisher>Oxford: Hindawi</publisher><subject>Adaptive systems ; Antenna arrays ; Antennas ; Benchmarks ; Chaos theory ; Convergence ; Energy ; Food ; Foraging behavior ; Mathematical analysis ; Normal distribution ; Optimization ; Optimization algorithms ; Population ; Search algorithms ; Sidelobe reduction ; Sidelobes ; System effectiveness ; Wireless communication systems</subject><ispartof>Wireless communications and mobile computing, 2021, Vol.2021 (1)</ispartof><rights>Copyright © 2021 Qiankun Liang et al.</rights><rights>Copyright © 2021 Qiankun Liang et al. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). 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Finally, the electromagnetic (EM) simulation results obtained by FEKO also show that it can achieve a satisfactory beam pattern performance in practical arrays.</description><subject>Adaptive systems</subject><subject>Antenna arrays</subject><subject>Antennas</subject><subject>Benchmarks</subject><subject>Chaos theory</subject><subject>Convergence</subject><subject>Energy</subject><subject>Food</subject><subject>Foraging behavior</subject><subject>Mathematical analysis</subject><subject>Normal distribution</subject><subject>Optimization</subject><subject>Optimization algorithms</subject><subject>Population</subject><subject>Search algorithms</subject><subject>Sidelobe reduction</subject><subject>Sidelobes</subject><subject>System effectiveness</subject><subject>Wireless communication systems</subject><issn>1530-8669</issn><issn>1530-8677</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><recordid>eNp9kEtLAzEUhYMoWKs7f0DApY7No5l0lkPxBaOC1fWQJjc2ZZqMmaml_97UFpduzr1wP849HIQuKbmlVIgRI4yOioKKMSNHaEAFJ9kkl_L4b8-LU3TWdUtCCE_wAIUSv4RvaPBzMM46MHjWqhjDBs9ARb3AZfMZousXK7xJisu2bZxWvQseO49nzgCuwjwJ7FzewKz17zFYXDmfPHDpe_Be4TJGtT1HJ1Y1HVwc5hB93N-9Tx-z6vXhaVpWmeZc9pmhkmojuRnnTOdiLomgHFJ-mhOrhIUxEKWBGWqVIWAmlHGpNWVWalYUOR-iq71vG8PXGrq-XoZ19OllzYQgVOYFmyTqZk_pGLougq3b6FYqbmtK6l2l9a7S-lBpwq_3-MJ5ozbuf_oHgt91Og</recordid><startdate>2021</startdate><enddate>2021</enddate><creator>Liang, Qiankun</creator><creator>Chen, Bin</creator><creator>Wu, Huaning</creator><creator>Ma, Chaoyi</creator><creator>Li, Senyou</creator><general>Hindawi</general><general>Hindawi Limited</general><scope>RHU</scope><scope>RHW</scope><scope>RHX</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7XB</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0N</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><orcidid>https://orcid.org/0000-0002-9398-7662</orcidid><orcidid>https://orcid.org/0000-0003-0648-9188</orcidid></search><sort><creationdate>2021</creationdate><title>A Novel Modified Sparrow Search Algorithm with Application in Side Lobe Level Reduction of Linear Antenna Array</title><author>Liang, Qiankun ; 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subjects | Adaptive systems Antenna arrays Antennas Benchmarks Chaos theory Convergence Energy Food Foraging behavior Mathematical analysis Normal distribution Optimization Optimization algorithms Population Search algorithms Sidelobe reduction Sidelobes System effectiveness Wireless communication systems |
title | A Novel Modified Sparrow Search Algorithm with Application in Side Lobe Level Reduction of Linear Antenna Array |
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