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Areas Commun., vol.35, no.6, pp.1201-1221, June 2017. 10.1109\/jsac.2017.2692307","DOI":"10.1109\/JSAC.2017.2692307"},{"key":"4","doi-asserted-by":"publisher","unstructured":"[4] L. Jorguseski, A. Pais, F. Gunnarsson, A. Centonza, and C. Willcock, \u201cSelf-organizing networks in 3GPP: standardization and future trends,\u201d IEEE Commun. Mag., vol.52, no.12, pp.28-34, Dec. 2014. 10.1109\/mcom.2014.6979983","DOI":"10.1109\/MCOM.2014.6979983"},{"key":"5","unstructured":"[5] Self-configuring and self-optimizing network (SON) use cases and solutions, Third-Generation Partnership Project, Cedex, France, 3GPP TR 36.902, ver. 9.3.0. [Online]. Available: www.3gpp.org"},{"key":"6","doi-asserted-by":"crossref","unstructured":"[6] S. Hamalainen, H. Sanneck, and C. 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Long, \u201cAn efficient stochastic gradient descent algorithm to maximize the coverage of cellular networks,\u201d IEEE Trans. Wirel. Commun., vol.18, no.7, pp.3424-3436, July 2019. 10.1109\/twc.2019.2914040","DOI":"10.1109\/TWC.2019.2914040"},{"key":"10","doi-asserted-by":"crossref","unstructured":"[10] S. Dastoor, U. Dalal, and J. Sarvaiya, \u201cComparative analysis of optimization techniques for optimizing the radio network parameters of next generation wireless mobile communication,\u201d Proc. 14th Int. Conf. Wireless Opt. Commun. Netw., pp.1-6, Feb. 2017. 10.1109\/wocn.2017.8065843","DOI":"10.1109\/WOCN.2017.8065843"},{"key":"11","doi-asserted-by":"crossref","unstructured":"[11] J. Ramiro and K. Hamied, Self-Organizing Networks (SON): Self-Planning, Self-Optimization and Self-Healing for GSM, UMTS and LTE, 1st ed., Wiley, Hoboken, NJ, USA, 2012. 10.1002\/9781119954224","DOI":"10.1002\/9781119954224"},{"key":"12","doi-asserted-by":"crossref","unstructured":"[12] H. Eckhardt, S. Klein, and M. Gruber, \u201cVertical antenna tilt optimization for LTE base stations,\u201d 2011 IEEE 73rd Vehicular Technology Conference (VTC Spring), Yokohama, pp.1-5, 2011. 10.1109\/vetecs.2011.5956370","DOI":"10.1109\/VETECS.2011.5956370"},{"key":"13","doi-asserted-by":"crossref","unstructured":"[13] F. Kasem, A. Haskou, and Z. Dawy, \u201cOn antenna parameters self optimization in LTE cellular networks,\u201d 2013 Third International Conference on Communications and Information Technology (ICCIT), Beirut, pp.44-48, 2013. 10.1109\/iccitechnology.2013.6579520","DOI":"10.1109\/ICCITechnology.2013.6579520"},{"key":"14","doi-asserted-by":"publisher","unstructured":"[14] S. Berger, M. Simsek, A. Fehske, P. Zanier, I. Viering, and G. Fettweis, \u201cJoint downlink and uplink tilt-based self-organization of coverage and capacity under sparse system knowledge,\u201d IEEE Trans. Veh. Technol., vol.65, no.4, pp.2259-2273, April 2016. 10.1109\/tvt.2015.2419079","DOI":"10.1109\/TVT.2015.2419079"},{"key":"15","doi-asserted-by":"publisher","unstructured":"[15] A. Engels, M. Reyer, X. Xu, R. Mathar, J. Zhang, and H. Zhuang, \u201cAutonomous self-optimization of coverage and capacity in LTE cellular networks,\u201d IEEE Trans. Veh. Technol., vol.62, no.5, pp.1989-2004, June 2013. 10.1109\/tvt.2013.2256441","DOI":"10.1109\/TVT.2013.2256441"},{"key":"16","doi-asserted-by":"crossref","unstructured":"[16] R. Razavi, S. Klein, and H. Claussen, \u201cSelf-optimization of capacity and coverage in LTE networks using a fuzzy reinforcement learning approach,\u201d 21st Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, Instanbul, pp.1865-1870, 2010. 10.1109\/pimrc.2010.5671622","DOI":"10.1109\/PIMRC.2010.5671622"},{"key":"17","doi-asserted-by":"crossref","unstructured":"[17] M.N. ul Islam and A. Mitschele-Thiel, \u201cCooperative fuzzy Q-learning for self-organized coverage and capacity optimization,\u201d 2012 IEEE 23rd International Symposium on Personal, Indoor and Mobile Radio Communications-(PIMRC), Sydney, NSW, pp.1406-1411, 2012. 10.1109\/pimrc.2012.6362568","DOI":"10.1109\/PIMRC.2012.6362568"},{"key":"18","doi-asserted-by":"publisher","unstructured":"[18] J. Li, J. Zeng, X. Su, W. Luo, and J. Wang, \u201cSelf-optimization of coverage and capacity in LTE networks based on central control and decentralized fuzzy Q-learning,\u201d International Journal of Distributed Sensor Networks, vol.8, no.8, 2012. 10.1155\/2012\/878595","DOI":"10.1155\/2012\/878595"},{"key":"19","doi-asserted-by":"publisher","unstructured":"[19] N. Dandanov, H. Al-Shatri, A. Klein, and V. Poulkov, \u201cDynamic self optimization of the antenna tilt for best trade-off between coverage and capacity in mobile networks,\u201d Wireless Pers. Commun., vol.92, no.1, pp.251-278, Jan. 2017. 10.1007\/s11277-016-3849-9","DOI":"10.1007\/s11277-016-3849-9"},{"key":"20","doi-asserted-by":"publisher","unstructured":"[20] M. Ben Hcine and R. Bouallegue, \u201cOn the dimensioning of LTE and LTE-advanced networks,\u201d Trans. Emerg. Telecommun. Technol., vol.28, no.3, p.2957, 2017. 10.1002\/ett.2957","DOI":"10.1002\/ett.2957"},{"key":"21","unstructured":"[21] Further Advancements for E-UTRA Physical Layer Aspects, document TR 36.814, Evolved Universal Terrestrial Radio Access (E-UTRA), 3GPP, 2017."},{"key":"22","doi-asserted-by":"publisher","unstructured":"[22] A. Asghar, H. Farooq, and A. Imran, \u201cConcurrent optimization of coverage, capacity, and load balance in HetNets through soft and hard cell association parameters,\u201d IEEE Trans. Veh. Technol., vol.67, no.9, pp.8781-8795, Sept. 2018. 10.1109\/tvt.2018.2846655","DOI":"10.1109\/TVT.2018.2846655"},{"key":"23","doi-asserted-by":"crossref","unstructured":"[23] M. 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