Top

Wireless Personal Communications

Published in:

06-05-2024

LTE Cell Planning for Resource Allocation in Emergency Communication

Authors: Sanjoy Debnath, Wasim Arif, Debarati Sen, Srimanta Baishya

Published in: Wireless Personal Communications | Issue 2/2024

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

The role of information and communication technology infrastructure is very crucial and perhaps most important during and post disaster (DPD) scenarios where thousands of lives are at risk. Communication services are expected to operate effectively in such demanding situations with restricted resources while fulfilling their core functionalities. The absence of coordinated cell planning taking the vulnerability of the geographical zone into account is a drawback that inhibits system operations and rescue efforts of public protection and disaster relief (PPDR) units. In this paper, the major issues of cell planning are encountered, and new algorithms for optimum LTE cell planning based on the hybrid dragonfly algorithm with differential evolution (DADE) are proposed under user coverage, user association, and capacity constraints. Thereafter, the feasibility of deployment and operation of an operator-independent emergency system (ES) integrated with balloon-based lightweight LTE eNodeB is analyzed to mitigate the DPD communication challenges. Then evaluate the optimal location for the deployment of ESs to cater to the users under the aforementioned constraint. Finally, optimum cell planning considering the vulnerability of the zone is discussed. The comparative comprehensive analysis of the results shows that the proposed algorithm offers superior convergence characteristics as well as time complexity as compared to the other state-of-the-art algorithms. Comparative results of normalized sum utility depict that the proposed algorithm outperforms the grey wolf optimizer (GWO), salp swarm algorithm (SSA), differential evolution (DE), whale optimization algorithm (WOA), and particle swarm optimization (PSO) based hybrid algorithms, respectively, by 0.5%, 4.3%, 6.5%, 8.6%, and 11.8%.

previous article A New Method for Detecting the Fatigue Using Automated Deep Learning Techniques for Medical Imaging Applications

next article A Method for Designing Substitution Boxes Based on Chaos with High Nonlinearity

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Li, Z. C., & Liu, Q. (2020). Optimal deployment of emergency rescue stations in an urban transportation corridor. Transportation, 47, 445–473. https://doi.org/10.1007/s11116-018-9897-0CrossRef

Ghazzai, H., Yaacoub, E., Alouini, M.-S., Dawy, Z., & Abu-Dayya, A. (2016). Optimized LTE cell planning with varying spatial and temporal user densities. IEEE Transactions on Vehicular Technology., 65(3), 1575–1589. https://doi.org/10.1109/TVT.2015.2411579CrossRef

Lin, Z. Y., Chang, J. Y., & Jeng, J. T. (2023). An efficient intuitionistic fuzzy sets base stations deployment strategy in internet of things systems. International Journal of Fuzzy Systems, 25, 1882–1894. https://doi.org/10.1007/s40815-023-01480-7CrossRef

Zhang, Y., Dai, L., & Wong, E. W. M. (2021). Optimal BS deployment and user association for 5G millimeter wave communication networks. IEEE Transactions on Wireless Communications, 20(5), 2776–2791. https://doi.org/10.1109/TWC.2020.3044288CrossRef

Noma-Osaghae, E., John, S. N., Aragha, A. I., & Okokpujie, K. (2022, March). Optimizing Stochastic Small Base Station Deployment with Particle Swarm Technique. In Future of Information and Communication Conference (pp. 918-936). Cham: Springer International Publishing.https://doi.org/10.1007/978-3-030-98012-2_64.

Nwelih, E., Isabona, J., & Imoize, A. L. (2023). Optimization of base station placement in 4G LTE broadband networks using adaptive variable length genetic algorithm. SN COMPUT. SCI., 4, 121. https://doi.org/10.1007/s42979-022-01533-yCrossRef

Venkateswararao, K., & Swain, P. (2022). Binary-PSO-based energy-efficient small cell deployment in 5G ultra-dense network. The Journal of Supercomputing, 78, 1071–1092. https://doi.org/10.1007/s11227-021-03910-5CrossRef

Haroon, M. S., Abbas, Z. H., Muhammad, F., & Abbas, G. (2020). Analysis of coverage-oriented small base station deployment in heterogeneous cellular networks. Physical Communication, 38, 100908. https://doi.org/10.1016/j.phycom.2019.100908CrossRef

Jaiswal, K., & Anand, V. (2021). A QoS aware optimal node deployment in wireless sensor network using Grey wolf optimization approach for IoT applications. Telecommunication Systems, 78, 559–576. https://doi.org/10.1007/s11235-021-00831-9CrossRef

10.

Zhao, G., Chen, S., & Hanzo, L. (2023). Energy-Spectral-Efficient Heterogeneous Cellular Networks: Joint Optimization of Cross-Tier Inter-BS Cooperation and BS Deployment. In IEEE Transactions on Vehicular Technology. https://doi.org/10.1109/TVT.2023.3332028CrossRef

11.

Mugume, E., & So, D. K. C. (2019). Deployment optimization of small cell networks with sleep mode. IEEE Transactions on Vehicular Technology, 68(10), 10174–10186. https://doi.org/10.1109/TVT.2019.2935403CrossRef

12.

Chen, C., Zhang, J., Chu, X., & Zhang, J. (2022). On the deployment of small cells in 3D hetnets with multi-antenna base stations. IEEE Transactions on Wireless Communications, 21(11), 9761–9774. https://doi.org/10.1109/TWC.2022.3179283CrossRef

13.

Li, J., Lu, D., Zhang, G., Tian, J., & Pang, Y. (2019). Post-disaster unmanned aerial vehicle base station deployment method based on artificial bee colony algorithm. IEEE Access, 7, 168327–168336. https://doi.org/10.1109/ACCESS.2019.2954332CrossRef

14.

Pasandideh, F., Rodriguez, F. E., Cesen, P. H., Pereira, M., et al. (2023). An improved particle swarm optimization algorithm for UAV base station placement. Wireless Personal Communication, 130, 1343–1370. https://doi.org/10.1007/s11277-023-10334-2CrossRef

15.

Teixeira, F. B., Oliveira, T., Lopes, M., Leocádio, C., Salazar, P., Ruela, J., ... & Ricardo, M. (2017, June). Enabling broadband internet access offshore using tethered balloons: The BLUECOM+ experience. In OCEANS 2017-Aberdeen (pp. 1-7). IEEE. https://doi.org/10.1109/OCEANSE.2017.8084877.

16.

Bozkurt, A., Gilmour, R. F., Jr., & Lal, A. (2009). Balloon-assisted flight of radio-controlled insect biobots. IEEE Transactions on Biomedical Engineering, 56(9), 2304–2307. https://doi.org/10.1109/TBME.2009.2022551CrossRef

17.

Kayhan, Ö., & Hastaoğlu, M. A. (2013, June). Control of high altitude telecommunication balloons via transport phenomena, material and fuell cell. In 2013 6th International Conference on Recent Advances in Space Technologies (RAST) (pp. 441-444). IEEE.https://doi.org/10.1109/RAST.2013.6581248.

18.

Iapichino, G., Bonnet, C., del Rio Herrero, O., Baudoin, C., & Buret, I. (2008, October). A mobile ad-hoc satellite and wireless mesh networking approach for public safety communications. In 2008 10th international workshop on signal processing for space communications (pp. 1-6). IEEE. https://doi.org/10.1109/SPSC.2008.4686695.

19.

Doumi, T., Dolan, M. F., Taesh, S., Casati, A., & Tsirtsis, G. (2013). LTE for public safety networks. IEEE Communications Magazine, 51(2), 106–112. https://doi.org/10.1109/MCOM.2013.6461193CrossRef

20.

First Responder Network Authority (FirstNet): http://www.firstnet.gov/. Accessed 20 June 2020.

21.

Debnath, S., Arif, W., Roy, S., Baishya, S., & Sen, D. (2021). A comprehensive survey of emergency communication network and management. Wireless Personal Communications, Springer, 124, 1375–1421. https://doi.org/10.1007/s11277-021-09411-1CrossRef

22.

https://en.wikipedia.org/wiki/Terrestrial_Trunked_Radio#Radio_frequencies. Accessed 20 June 2020.

23.

https://en.wikipedia.org/wiki/1.25-meter_band. Accessed 24 June 2020.

24.

https://en.wikipedia.org/wiki/Project_25. Accessed 24 June 2020.

25.

Ferrus, R., Sallent, O., Baldini, G., & Goratti, L. (2013). LTE: The technology driver for future public safety communications. IEEE Communications Magazine, 51(10), 154–161. https://doi.org/10.1109/MCOM.2013.6619579CrossRef

26.

Viering, I., Dottling, M., & Lobinger, A. (2009, June). A mathematical perspective of self-optimizing wireless networks. In 2009 IEEE International Conference on Communications (pp. 1-6). IEEE. https://doi.org/10.1109/ICC.2009.5198628.

27.

Deruyck, M., Tanghe, E., Joseph, W., Vereecken, W., Pickavet, M., Martens, L., Dhoedt, B. (2010). Model for power consumption of wireless access networks. Measurement and Technology, IET Science, 2010https://doi.org/10.1049/iet-smt.2010.0094.

28.

Trango broadband networks - TrangoLINK - Giga, 2010.

29.

Debnath, S., Baishya, S., Sen, D., & Arif, W. (2020). A hybrid memory-based dragonfly algorithm with differential evolution for engineering application. Engineering with Computers, 37, 2775–2802. https://doi.org/10.1007/s00366-020-00958-4CrossRef

30.

Yanyun, C., Jianlin, Q., Xiang, G., Jianping, C., Dan, J., & Li, C. (2011, May). Advances in research of Fuzzy c-means clustering algorithm. In 2011 International Conference on Network Computing and Information Security (Vol. 2, pp. 28-31). IEEE.https://doi.org/10.1109/NCIS.2011.104.

31.

Mirjalili, S. (2016). Dragonfly algorithm: A new meta-heuristic optimization technique for solving single-objective, discrete, and multi-objective problems. Neural Computing and Applications, 27(4), 1053–1073. https://doi.org/10.1007/s00521-015-1920-1CrossRef

32.

Blum, C., & Li, X. (2008). Swarm intelligence in optimization. In Swarm intelligence: introduction and applications (pp. 43-85). Berlin, Heidelberg: Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-74089-6_2.

33.

Storn, R., & Price, K. (1997). Differential evolution– a simple and efficient Heuristic for global optimization over continuous spaces. Journal Global Optimization, 11, 341–359. https://doi.org/10.1023/A:1008202821328MathSciNetCrossRef

34.

Hata, M. (1980). Empirical formula for propagation loss in land mobile radio services. IEEE Transactions on Vehicular Technology, 29(3), 317–325. https://doi.org/10.1109/T-VT.1980.23859CrossRef

35.

Okumura, T., Ohmori, E., & Fukuda, K. (1968). Field strength and its variability in VHF and land-mobile radio service. Review of the Electrical communication Laboratory, 16, 825–873.

36.

Holma, H., & Toskala, A. (Eds.). (2009). LTE for UMTS: OFDMA and SC-FDMA Based Radio Access. NY: John Wiley & Sons.

37.

Johnson, C. (2012) Long Term Evolution in Bullets, 2nd ed. Northhampton, U.K.: CreateSpace, 2012.

38.

Mirjalili, S., Mirjalili, S. M., & Lewis, A. (2014). Grey wolf optimizer. Advances in Engineering Software, 69, 46–61. https://doi.org/10.1016/j.advengsoft.2013.12.007CrossRef

39.

Kennedy, J., & Eberhart, R. (1995, November). Particle swarm optimization. In Proceedings of ICNN'95-International Conference on Neural Networks (Vol. 4, pp. 1942-1948). ieee.https://doi.org/10.1109/ICNN.1995.488968.

40.

Mirjalili, S., & Lewis, A. (2016). The whale optimization algorithm. Advances in Engineering Software, 95, 51–67. https://doi.org/10.1016/j.advengsoft.2016.01.008CrossRef

41.

Mirjalili, S., Gandomi, A. H., Mirjalili, S. Z., Saremi, S., Faris, H., & Mirjalili, S. M. (2017). Salp Swarm Algorithm. Advances in engineering software, 114, 163–191. https://doi.org/10.1016/j.advengsoft.2017.07.002CrossRef

42.

Doocy, S., Daniels, A., Packer, C., Dick, A., & Kirsch, T. D. (2013). The human impact of earthquakes: A historical review of events 1980–2009 and systematic literature review. PLOS Currents Disasters. https://doi.org/10.1371/currents.dis.67bd14fe457f1db0b5433a8ee20fb833CrossRef

43.

Ono, A. (2015). How do natural disasters affect the economy?. www.weforum.org. available at: https://www.weforum.org/agenda/2015/02/how-do-natural-disasters-affect-the-economy/. Accessed 24 June 2020.

44.

Debnath, S., Roy, S., Baishya, S., Sen, D., & Arif, W. (2017, December). Approaches for Disaster Communication Backbone Network in Operator Independent Scenario. In 2017 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC) (pp. 1-6). IEEE. https://doi.org/10.1109/ICCIC.2017.8524393.

45.

Prasad, R., & Kegel, A. (1991). Improved assessment of interference limits in cellular radio performance. IEEE Transactions on Vehicular Technology, 40(2), 412–419. https://doi.org/10.1109/25.289422CrossRef

Title: LTE Cell Planning for Resource Allocation in Emergency Communication
Authors: Sanjoy Debnath
Wasim Arif
Debarati Sen
Srimanta Baishya
Publication date: 06-05-2024
Publisher: Springer US
Published in: Wireless Personal Communications / Issue 2/2024
Print ISSN: 0929-6212
Electronic ISSN: 1572-834X
DOI: https://doi.org/10.1007/s11277-024-11103-5

Springer Professional

Abstract

Please log in to get access to your license.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Technik"

Springer Professional "Wirtschaft+Technik"

Springer Professional "Wirtschaft"

Other articles of this Issue 2/2024

Scalable and Cost-Efficient PoA Consensus-Based Blockchain Solution for Vaccination Record Management

A Review and Comparative Analysis of PAPR Reduction Techniques of OFDM System

Spectrum Sensing Using Intelligent Reflecting Surfaces with Multi-antennas Energy Harvesting

Instantaneous and Average Throughput Maximization with Solar Energy Harvesting

Concealed Information Test Using Neuro Evolution of Augmenting Topologies

A Novel Approach for Premature Detection of Alzheimer’s Disease Using Convolutional Neural Network in Deep Learning Technique