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Optimal Placement of Near Ground VHF/UHF Radio Communication Network as a Multi Objective Problem

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Abstract

Ultra high frequency (UHF) and very high frequency (VHF) bands are widely used with near ground applications especially for communication purposes. However, due to the limited antenna height, the VHF/UHF signals are very sensitive to the surroundings. The signal may attenuate, fade or loss depending on the condition of the environment. Therefore, it is a challenging task to find the optimal values for network topology planning. In this paper, three multi-objective algorithms namely NSGA-II, SPEA-II and OMOPSO are considered to mitigate the problem. This paper also intends to maximize the electromagnetic fields and signal propagation. On the other hand, it intends to minimize path loss and signal attenuation. Different environment settings such as diverse foliage depth and tree trunk height are considered to evaluate the proposed model. From the experiments, it is shown that NSGA-II outperforms other algorithms. The experiment also shows that the optimal foliage depth between sender and receiver is less or equal to 2 km and the optimal tree trunk height is less or equal to 7 m.

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References

  1. Castellanos, P., Almeida, M., Cal-Braz, J., David, R., Arnez, J., Souza, R., et al. (2015). Preliminary field tests results of ISDB-Tb digital TV transmission in the VHF-high band. In IEEE-APS topical conference on antennas and propagation in wireless communications (APWC) (pp. 1377–1380).

  2. Walker, K., & Strassel, S. (2012). The RATS radio traffic collection system. In Odyssey 2012-the speaker and language recognition workshop (pp. 1–7).

  3. Rector, C., Barrick, E., Lipa, J., & Aguilar, H. (2016). Negative pseudo-range processing with multi-static FMCW radars. U.S. patent no. 9,442,188. Washington, DC: U.S. Patent and Trademark Office.

  4. Sawada, H., Oodo, M., Kan, T., Kojima, F., Harada, H., Kobayashi, H., et al. (2015). Receiver diversity evaluation for a VHF band broadband mobile communication system. In 21st Asia-Pacific conference on communications (APCC) (pp. 104–108).

  5. Davis, E., & Pillai, U. (2014). Waveform diversity for ultra-wide band surveillance radars. IET Radar, Sonar and Navigation,8(9), 1226–1233.

    Google Scholar 

  6. Gallagher, L., Turnbull, G., & Akule, R. (1999). Telecommunications in action. London: Regency Foundation.

    Google Scholar 

  7. Le Naour, A., Pipon, F., Nahoum, B., Mérel, D., & Obrist, B. (2014). Performance of the fast net narrowband VHF frequency hopping tactical radio in challenging multipath environments. In IEEE military communications conference (MILCOM) (pp. 649–656).

  8. Slotten, H. R. (2000). Radio and television regulation: Broadcast technology in the United States. Maryland: The Jouns Hopkins University Press.

    Google Scholar 

  9. Li, L., Yeo, T., Kooi, P., Leong, M., & Koh, J. (1999). Analysis of electromagnetic wave propagation in forest environment along multiple paths. Journal of Electromagnetic Waves and Applications,23(1), 37–164.

    Google Scholar 

  10. Liao, D., & Sarabandi, K. (2007). Modeling and simulation of near-earth propagation in presence of a truncated vegetation layer. IEEE Transactions on Antennas and Propagation,55(3), 949–957.

    Google Scholar 

  11. Li, Y., & Ling, H. (2009). Numerical modeling and mechanism analysis of VHF wave propagation in forested environments using the equivalent slab model. Progress in Electromagnetics Research (PIER),91(1), 17–34.

    Google Scholar 

  12. Goldman, J., & Swenson, J. (1999). Radio wave propagation through woods. IEEE Antennas and Propagation Magazine,41(4), 34–36.

    Google Scholar 

  13. Meng, Y., Lee, Y., & Ng, B. (2008). Near ground channel characterization and modeling for a tropical forested path. In Proceedings of 29th URSI general assembly, Chicago, USA (pp. 4–9).

  14. Joshi, G., Dietrich, C., Anderson, C., Newhall, W., Davis, W., Isaacs, J., et al. (2005). Near-ground channel measurements over line-of-sight and forested paths. IEEE Microwaves, Antennas and Propagation,152(6), 589–596.

    Google Scholar 

  15. Meng, Y., Lee, Y., & Ng, B. (2009). Empirical near ground path loss modeling in a forest at VHF and UHF bands. IEEE Transactions on Antennas and Propagation,57(5), 1461–1468.

    Google Scholar 

  16. Tamir, T. (1967). On radio wave propagation in forest environments. IEEE Transactions on Antennas and Propagation,15(6), 806–817.

    Google Scholar 

  17. Karlsson, S., Grenvall, M., Kvick, A., Eugensson, L., Grahn, F., & Pettersson, L. (2013). Co-site interference analysis and antenna system integration on a swedish combat vehicle platform. In IEEE military communications conference (MILCOM), San Diego, CA, USA (pp. 369–374).

  18. Silver, W. (2004). Ham radio for dummies. Hoboken: Wiley.

    Google Scholar 

  19. USA Army. (1984). Technical manual of antenna AS-1729/VRC. The Pentagon: Department of the United States Army.

    Google Scholar 

  20. Olufemi, A., Famoriji, O., & Olasoji, O. (2013). Evaluation and modelling of UHF radio wave propagation in a forested environment. Evaluation,2(12), 101–106.

    Google Scholar 

  21. Penttinen, A. (1999). Chapter 10—network planning and dimensioning. In Lecture notes: S-38.145-introduction to teletraffic theory. Helsinki: Helsinki University of Technology Press.

  22. Pal, S., & Misra, S. (2016). Soft computing applications in sensor networks. New York: CRC Press.

    Google Scholar 

  23. Yijia, Z. (1996). Research on mobile wireless network planning. In IEEE international conference on communication technology proceedings ICCT’96 (pp. 342–346).

  24. Andréasson, N., Evgrafov, A., & Patriksson, M. (2005). An introduction to optimization: Foundations and fundamental algorithms. Goteborg: Chalmers University of Technology Press.

    Google Scholar 

  25. Meng, Y., Lee, Y., & Ng, B. (2010). Path loss modeling for near-ground VHF radio-wave propagation through forests with tree-canopy reflection effect. Progress in Electromagnetics Research,12(1), 131–141.

    Google Scholar 

  26. Ibdah, Y., & Ding, Y. (2017). Path loss models for low-height mobiles in forest and urban. An International Journal of Wireless Personal Communications,92(2), 455–465.

    Google Scholar 

  27. Sabri, N., Aljunid, S., Salim, R., Kamaruddin, M., Ahmad, R., & Malek, M. (2013). Path loss analysis of WSN wave propagation in vegetation. Journal of Physics: Conference Series,423(1), 012063.

    Google Scholar 

  28. Michael, A. (2013). Further investigation into VHF radio wave propagation loss over long forest channel. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering,2(1), 705–710.

    Google Scholar 

  29. Amalu, P., & Alade, M. (2016). Empirical modelling of very high frequency radio propagation loss in tropical forest. The Pacific Journal of Science and Technology,17(2), 37–44.

    Google Scholar 

  30. Al Salameh, M. (2014). Lateral ITU-R foliage and maximum attenuation models combined with relevant propagation models for forest at the VHF and UHF bands. International journal of Networking and Communication,1(2), 55–63.

    Google Scholar 

  31. Kumar, D. (2009). Classical and advanced techniques for optimization. Optimization Methods,5(2), 1–12.

    Google Scholar 

  32. Paulinas, M., & Ušinskas, A. (2015). A survey of genetic algorithms applications for image enhancement and segmentation. Information Technology and Control,36(3), 278–284.

    Google Scholar 

  33. Meete, K. A. (2014). Survey: swarm intelligence vs. genetic algorithm. International Journal of Science and Research,3(5), 231–235.

    Google Scholar 

  34. Kennedy, J., Eberhart, R. (1995). Particle swarm optimization. In IEEE international conference on neural networks, Perth, Western Australia (pp. 113–120).

  35. Hamdy, M., Nguyen, A., & Hensen, J. A. (2016). Performance comparison of multi-objective optimization algorithms for solving nearly-zero-energy-building design problems. Energy and Buildings,121(1), 57–71.

    Google Scholar 

  36. Acampora, G., Ishibuchi, H., & Vitiello A. (2014). A comparison of multi-objective evolutionary algorithms for the ontology meta-matching problem. In IEEE congress on evolutionary computation (CEC) (pp. 413–420).

  37. Azarhoosh, M. J., Ebrahim, H. A., & Pourtarah, S. H. (2016). Simulating and optimizing auto-thermal reforming of methane to synthesis gas using a non-dominated sorting genetic algorithm II method. Chemical Engineering Communications,203(1), 53–63.

    Google Scholar 

  38. Coello, C., Lamont, G., & Van Veldhuizen, D. (2007). Evolutionary algorithms for solving multi-objective problems (2nd ed.). Berlin: Springer.

    MATH  Google Scholar 

  39. Zitzler, E., Laumanns, M., & Thiele, L. (2002). SPEA2: Improving the strength pareto evolutionary algorithm for multi objective optimization. In Proceedings of the EUROGEN evolutionary methods for design, volume optimization and control with applications to industrial problems, Barcelona, Spain (pp. 1–21).

  40. Theophila, B. (2008). Study of hardware and software optimizations of SPEA2 on hybrid FPGAs. New York: Rochester Institute of Technology, ProQuest Dissertations Publishing.

    Google Scholar 

  41. Bandyopadhyay, S., & Bhattacharya, R. (2013). On some aspects of nature-based algorithms to solve multi-objective problems. In X.-S. Yang (Ed.), Artificial intelligence, evolutionary computing and metaheuristics (pp. 477–524). Berlin: Springer.

    Google Scholar 

  42. Sierra, M., & Coello, C. (2005). Improving PSO-based multi-objective optimization using crowding, mutation and ∈-dominance. In International conference on evolutionary multi-criterion optimization. Berlin: Springer (pp. 505–519).

  43. Al-Nuaimi, O., & Stephens, L. (1998). Measurements and prediction model optimization for signal attenuation in vegetation media at centimeter wave frequencies. In IEEE proceedings-microwaves, antennas and propagation (pp. 201–206).

  44. Ndzi, L., Kamarudin, M., Muhammad Ezanuddin, A., Zakaria, A., Ahmad, B., Malek, A., et al. (2012). Vegetation attenuation measurements and modeling in plantations for wireless sensor network planning. Progress in Electromagnetics Research B,36(1), 283–301.

    Google Scholar 

  45. Kovács, Z., Eggers, C., & Olesen, K. (1999). Radio channel characterization for forest environments in the VHF and UHF frequency bands. In IEEE VTS 50th vehicular technology conference, Amsterdam, Netherlands (pp. 1387–1391).

  46. Majidi, M., & Maghsoudi, Y. (2013). Investigation of polarization phase difference related to forest fields characterizations. ISPRS-International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences,3(1), 273–276.

    Google Scholar 

  47. Linsenmair, E. (2001). Tropical forest canopies: Ecology and management. Berlin: Springer.

    Google Scholar 

  48. Boland, J., Brooker, H., Chippendale, M., Hall, N., Hyland, M., Johnston, D., et al. (2006). Forest trees of Australia (5th ed.). Clayton: CSIRO Publishing.

    Google Scholar 

  49. Larsen, A. (2012). The northern forest border in Canada and Alaska: Biotic communities and ecological relationships. Berlin: Springer.

    Google Scholar 

  50. Manokaran N. (1995). South-east Asian dipterocarp forest ecosystems. In IUFRO XX world congress sub plenary sessions caring for the forest: research in a changing world, Tampere, Finland (pp. 6–12).

  51. Stokes, C., & Howden, M. (2010). Adapting agriculture to climate change: Preparing Australian agriculture, forestry and fisheries for the future. Clayton: CSIRO Publishing.

    Google Scholar 

  52. French, C. (2012). Jordan. Guilford: Bradt Travel Guides.

    Google Scholar 

  53. Storm, R., & Wedzel, S. (1997). Hiking Michigan. Michigan: Human Kinetics.

    Google Scholar 

  54. Hamdan. M., Yassein. M., & Shehadeh. H. A. (2015). Multi-objective optimization modeling of interference in home health care sensors. In IEEE 11th international conference on innovations in information technology (IIT), Dubai, UAE (pp. 219–224).

  55. Hamdan, M., Yassein, M., & Shehadeh, H. A. (2017). Multi-objective optimization modeling. In L. Ismail & Z. Liren (Eds.), Information innovation technology in smart cities (pp. 321–350). Singapore: Springer.

    Google Scholar 

  56. Engelbrecht, A. (2005). Fundamentals of computational swarm. Milton: Wiley.

    Google Scholar 

  57. Shehadeh, H. A., Idris, M. Y. I., Ahmedy, I., Ramli, R., & Noor, N. M. (2018). The multi-objective optimization algorithm based on sperm fertilization procedure (MOSFP) method for solving wireless sensor networks optimization problems in smart grid applications. Energies,11(1), 97.

    Google Scholar 

  58. Shehadeh, H. A., Idris, M. Y. I., & Ahmedy, I. (2017). Multi-objective optimization algorithm based on sperm fertilization procedure (MOSFP). Symmetry,9(1), 241.

    Google Scholar 

  59. Deb, K., & Gupta, S. (2011). Understanding knee points in bicriteria problems and their implications as preferred solution principles. Engineering Optimization,43(11), 1175–1204.

    MathSciNet  Google Scholar 

  60. Shehadeh, H. A., Idris, M.Y.I., & Ahmedy, I. (2018). Sperm swarm optimization algorithm for optimizing wireless sensor network challenges. In ACM international conference on communications and broadband networking (ICCBN 2018), Singapore, Singapore (pp. 53–69).

  61. Shehadeh, H. A., Idris, M. Y. I., & Ahmedy, I. (2018). Empirical study of sperm swarm optimization algorithm. In K. Arai, et al. (Eds.), Volume 869 of the advances in intelligent systems and computing series edition. IntelliSys 2018, London, UK, AISC 869, 2019 (pp. 1082–1104). Cham: Springer.

    Google Scholar 

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Acknowledgements

We acknowledge that we are getting University of Malaya Research Grant GPF005D-2018 to publish this paper.

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Authors and Affiliations

  1. Department of Computer System and Technology, Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, Malaysia

    Hisham A. Shehadeh, Mohd. Yamani Idna Idris & Ismail Ahmedy

  2. School of Mathematical and Computer Sciences, Heriot Watt University, Edinburgh, UK

    Hani Ragab Hassen

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  1. Hisham A. Shehadeh
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  2. Mohd. Yamani Idna Idris
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  4. Hani Ragab Hassen
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The work was deduced from Hisham’s Ph.D. thesis as Dr. Mohd. Yamani Idna Idris and Dr. Ismail Ahmedy supervised him along his study. The following section shows the information about the authors.

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Correspondence to Mohd. Yamani Idna Idris.

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Shehadeh, H.A., Idris, M.Y.I., Ahmedy, I. et al. Optimal Placement of Near Ground VHF/UHF Radio Communication Network as a Multi Objective Problem. Wireless Pers Commun 110, 1169–1197 (2020). https://doi.org/10.1007/s11277-019-06780-6

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