Abstract
Satellite communication is extensively used in television broadcasting and mobile communications. Multi-beams are used in satellite communication to communicate different distinct locations with multiple users. Optimization methods like quasi-Newton method (QNM) and teaching–learning-based optimization (TLBO) are used to generate multi-beam pattern using linear antenna arrays. The desired amplitude and phase distributions are determined by using both QNM and TLBO algorithms. The desired multi-beam pattern is plotted in U domain where u = sin θ. QNM has converged much fast and with less number of iterations than TLBO algorithm in generating the multi-beam pattern. The convergence plots are generated for n = 60, 80 elements using QNM and TLBO algorithms.
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References
Luo YZ, Tang GJ, Zhou LN (2008) Hybrid approach for solving systems of nonlinear equations using chaos optimization and quasi-Newton method. App Soft Comput 8(2):1068–1073
Becker S, Fadili J (2012) A quasi-Newton proximal splitting method. In: Advances in neural information processing systems. pp 2618–2626
Li Z, Wu W, Zhang B, Sun H, Guo Q (2013) Dynamic economic dispatch using Lagrangian relaxation with multiplier updates based on a quasi-Newton method. IEEE Trans Power Syst 28(4):4516–4527
Hamdi A, Griewank A (2011) Reduced quasi-Newton method for simultaneous design and optimization. Comput Optim Appl 49(3):521–548
Chakravarthy VS, Chowdary PS, Satpathy SC, Terlapu SK, Anguera J (2018) Antenna array synthesis using social group optimization. Microelectronics, electromagnetics and telecommunications. Springer, Singapore, pp 895–905
Satapathy S, Naik A (2013) Improved teaching learning based optimization for global function optimization. Decis Sci Lett 2(1):23–34
Chakravarthy VV, Babu KN, Suresh S, Devi PC, Rao PM (2015) Linear array optimization using teaching learning based optimization. In: Emerging ICT for bridging the future—proceedings of the 49th annual convention of the computer society of India CSI, vol 2. Springer, pp 183–190
Recioui A (2016) Design and thinning of linear and planar antenna arrays using a binary teaching learning optimizer. Acta Phys Pol, A 130:7–8
Rao R (2016) Review of applications of TLBO algorithm and a tutorial for beginners to solve the unconstrained and constrained optimization problems. Decis Sci Lett 5(1):1–30
Krishna Chaitanya R, Raju GSN, Raju KVSN, Mallikarjuna Rao P (2019) Antenna pattern synthesis using the Quasi-Newton method, firefly and particle swarm optimization techniques. IETE J Res, 1–9
Balanis CA (2005) Antenna theory analysis and design. Wiley, New Jersey
Bozorg-Haddad O (2018) Advanced optimization by nature inspired algorithms. Springer, Singapore
Zadehparizi F, Jam S (2019) An improved teaching-learning–based optimization for design of frequency reconfigurable antennas. Int J Commun Syst, e4030
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Krishna Chaitanya, R., Mallikarjuna Rao, P., Raju, K.V.S.N. (2021). Multi-Beam Generation Using Quasi-Newton method and Teaching Learning Based Optimization algorithm. In: Chowdary, P., Chakravarthy, V., Anguera, J., Satapathy, S., Bhateja, V. (eds) Microelectronics, Electromagnetics and Telecommunications. Lecture Notes in Electrical Engineering, vol 655. Springer, Singapore. https://doi.org/10.1007/978-981-15-3828-5_20
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DOI: https://doi.org/10.1007/978-981-15-3828-5_20
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