Loader and tester swarming drones for cellular phone network loading and field test: non-stochastic particle swarm optimization

Journal: Journal of Autonomous Intelligence DOI: 10.32629/jai.v2i2.46

Mohammad Shekaramiz1, Amir Mirzaeinia2, Mostafa Hassanalian3, Mehdi Mirzaeinia4

1. ECE, UTAH STATE UNIVERSITY, Graduate Research Assistant
2. Department of Computer Science and Engineering, New Mexico Inst. of Mining and Tech., Socorro, NM, USA
3. Department of Mechanical and Aerospace Engineering, New Mexico Inst. of Mining and Tech., Socorro, NM, USA
4. Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran


Cellular network operators have problems to test their network without affecting their user experience. Testing network performance in a loaded situation is a challenge for the network operator because network performance differs when it has more load on the radio access part. Therefore, in this paper, deploying swarming drones is proposed to load the cellular network and scan/test the network performance more realistically. Besides, manual swarming drone navigation is not efficient enough to detect problematic regions. Hence, particle swarm optimization is proposed to be deployed on swarming drone to find the regions where there are performance issues. Swarming drone communications helps to deploy the PSO method on them. Loading and testing swarm separation helps to have almost non-stochastic received signal level as objective function. Moreover, there are some situations that more than one network parameter should be used to find a problematic region in the cellular network. It is also proposed to apply multi-objective PSO to find more multi-parameter network optimization at the same time.


Particle swarm optimization; swarming drone; cellular network; radio optimization; loaded network test


1Yu, C.H., Doppler, K., Ribeiro, C.B. and Tirkkonen, O., “Resource sharing optimization for device-to-device communication underlaying cellular networks”, IEEE Transactions on Wireless communications, Vol. 10, No. 8, pp. 2752-2763, 2011.
2Sharma, P., “Evolution of mobile wireless communication networks-1G to 5G as well as future prospective of next generation communication network”, International Journal of Computer Science and Mobile Computing, Vol. 2, No. 8, pp.47-53, 2013.
3Jamalabdollahi, M., Mirzaeinia, A. and Salari, S., “RLS-based frequency synchronization and channel estimation in OFDMA systems”, In Advanced Communication Technology (ICACT), 14th International Conference on, pp. 832-836, IEEE, 2012.
4Chin, W.H., Fan, Z. and Haines, R., “Emerging technologies and research challenges for 5G wireless networks”, IEEE Wireless Communications, Vol. 21, No. 2, pp.106-112, 2014.
5Kora, A.D., Ongbwa, B.A.E., Cances, J.P. and Meghdadi, V, “Accurate radio coverage assessment methods investigation for 3G/4G networks”, Computer Networks, Vol. 107, pp. 246-257, 2016.
6Mariappan, P.M, Raghavan, D.R., Aleem, S.H.A. and Zobaa, A.F, “Effects of electromagnetic interference on the functional usage of medical equipment by 2G/3G/4G cellular phones: A review”, Journal of Advanced Research, Vol. 7, No. 5, pp.727-738, 2016.
7Sanders, A.D., Linder, P.S.L. and Dave, D., Telecom Network Optimization Inc, “System and method for identifying co-channel interference in a radio network”, U.S. Patent 7,301,920, 2007.
8 Chow, P.E.K. and Krizman, K.J., “Carriercomm Inc, Radio network performance management”, U.S. Patent 6,873,601, 2005.
9Kline, P.A. and Dickey, S.L., Dynamic Telecommunications Inc, “Method and apparatus for co-channel interference measurements and base station color code decoding for drive tests in TDMA, cellular, and PCS networks”, U.S. Patent 6,931,235, 2005.
10Swift, L.W. and Dickey, S., PCTEL Inc, “Methodology and system for generating a three-dimensional model of interference in a cellular wireless communication network”, U.S. Patent 6,950,665, 2005.
13Hassanalian, M. and Abdelkefi, A., “Classifications, applications, and design challenges of drones: A review”, Progress in Aerospace Sciences, Vol. 91, pp.99-131, 2017.
14Mirzaeinia, A.,Hassanalian, M., Lee., K., Mirzaeinia, M., “Performance Enhancement and Load Balancing of Swarming Drones through Position Reconfiguration”, 2019 AIAA Aviation Forum, Dallas, TX, 17-21 June, 2019.
15Mirzaeinia, A.,Hassanalian, M., Mirzaeinia, M., “Distributed Adaptive Drone Radar to Detect More Accurate Obstacle and Target Parameters”, 2019 AIAA Aviation Forum, Dallas, TX, 17-21 June, 2019.
16Hassanalian, M., Rice, D. and Abdelkefi, A., “Evolution of space drones for planetary exploration: A review”, Progress in Aerospace Sciences, 97, pp.61-105, 2018.
17Hassanalian, M., Salazar, R., Abdelkefi, A., “Analysis and optimization of a tilt rotor unmanned air vehicle for long distances delivery and payload transportation”, 2018 AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, Kissimmee, Florida, 8–12 January 2018.
18Hassanalian, M. and Abdelkefi, A., “Design, manufacturing, and flight testing of a fixed wing micro air vehicle with Zimmerman planform”, Meccanica, Vol. 52, No. 6, pp.1265-1282, 2017.
19Hassanalian, M., Quintana, A. and Abdelkefi, A., “Morphing and growing micro unmanned air vehicle: Sizing process and stability”, Aerospace Science and Technology, Vol. 78, pp.130-146, 2018.
20Sappington, R., Acosta, G., Hassanalian, M., Lee, K., Morelli, R., “Drone Stations in Airports for Runway and Airplane Inspection Using Image Processing Techniques”, 2019 AIAA Aviation Forum, Dallas, TX, 17-21 June, 2019.
21Hassanalian, M., Rice, D., Johnstone, S. and Abdelkefi, A., “Performance analysis of fixed wing space drones in different solar system bodies” Acta Astronautica, Vol. 152, pp.27-48, 2018.
22Hassanalian, M., Abdelkefi, A., “Conceptual design and analysis of separation flight for an unmanned air vehicle to five micro air vehicles”, In 55th AIAA Aerospace Sciences Meeting, Grapevine, Texas, 9–13 January 2017.
23Roy, S., Biswas, S., Chaudhuri, S.S., “Nature-inspired swarm intelligence and its applications”, Int. J. Mod. Educ. Comput. Sci., Vol. 6, No. 12, p. 55, 2014
24Hassanalian,M., Radmanesh, M., Ziaei-Rad, S., “Sending instructions and receiving the data from MAVs using telecommunication Networks”, International Micro Air Vehicle 2012 Conference, Braunschweig, Germany, 3-6 July 2012.
25Kendoul, F., “Survey of advances in guidance, navigation, and control of unmanned rotorcraft systems”, J. Field Robot, Vol. 29, No. 2, pp. 315-378, 2012.
26Shi, Y. and Eberhart, R.C., “Empirical study of particle swarm optimization”. In Proceedings of the Congress on Evolutionary Computation-CEC99, IEEE, Vol. 3, pp. 1945-1950, 1999.
27Shahriari, B., Swersky, K., Wang, Z., Adams, R.P. and De Freitas, N.,. “Taking the human out of the loop: A review of Bayesian optimization.” Proceedings of the IEEE, Vol. 104, No. 1, pp.148-175, 2015.

Copyright © 2019 Mohammad Shekaramiz, Amir Mirzaeinia, Mostafa Hassanalian, Mehdi Mirzaeinia

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