Dergiler / International Journal of 3D Printing Technologies and Digital Industry / 2025 / Cilt: 9 Sayı: 3

THE SOLUTION OF VOICE TRANSMISSION PROBLEMS DUE TO POOR COVERAGE AND LOW NETWORK QUALITY IN A CELLULAR NETWORK OPERATOR

Bahadır Başyiğit(ISPARTA UYGULAMALI BİLİMLER ÜNİVERSİTESİ)0000-0003-4558-5068
Sayfa
681–687
Yayın Tarihi
2025-12-28
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

The number of calls to the network busy hour call drops from 6 to 1 and the network busy number has decreased from 4 to 1.

📌 3 Maddede Bu Makale

🎯
Amaç & Hipotez:Although Long-term Evolution (LTE) technology is currently used in data and voice transmission, the GSM frequency band is still used in voice transmission because of its more resistant to both coverage and multipath fading.
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Temel Bulgular & Veri:Poor coverage problems caused by low signal level directly reduce network performance and cause undesirable cases.
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Sonuç & Katkı:The number of calls to the network busy hour call drops from 6 to 1 and the network busy number has decreased from 4 to 1.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Quality of Service · Speech Tests · Mobile Networks.

Özet

Although Long-term Evolution (LTE) technology is currently used in data and voice transmission, the GSM frequency band is still used in voice transmission because of its more resistant to both coverage and multipath fading. Poor coverage problems caused by low signal level directly reduce network performance and cause undesirable cases. Solving these problems requires relatively difficult process steps, such as hardware configuration and parameter optimization. Since the hardware configuration is not consistently repeatable, it is the preferred method to improve the self-collected parameter values either on site or by the network. In this study, Test Mobile System (TEMs) has been used to collect data. TEMs is a type of telephony that has the ability to collect/present detailed information about all quality and level of signals. The aim of this study is first to solve important problems such as poor coverage area, low signal level and bad signal quality by the improvement of the optimization parameters and changing hardware configuration in detail as a novelty and to improve the quality statistics of a region consisting of 17 base stations. These are; RxQual value from 0.61 to 0.57, average signal quality from 0.19 to 0.16, mean opinion score (MOS) for downlink from 4.01 to 4.16, uplink from 3.65 to 3.79 to increase the capacity of subscribers it is provided. The handover (HO) success rate, which is used to mean inter-cell transfer, is 96% to 99%, call set-up success rate is 95.27% to 97.13%, call retainability is 95.79% to 98.03% and call integrity is reached to 97.23% from 96.77%. The number of calls to the network busy hour call drops from 6 to 1 and the network busy number has decreased from 4 to 1.

Abstract

Although Long-term Evolution (LTE) technology is currently used in data and voice transmission, the GSM frequency band is still used in voice transmission because of its more resistant to both coverage and multipath fading. Poor coverage problems caused by low signal level directly reduce network performance and cause undesirable cases. Solving these problems requires relatively difficult process steps, such as hardware configuration and parameter optimization. Since the hardware configuration is not consistently repeatable, it is the preferred method to improve the self-collected parameter values either on site or by the network. In this study, Test Mobile System (TEMs) has been used to collect data. TEMs is a type of telephony that has the ability to collect/present detailed information about all quality and level of signals. The aim of this study is first to solve important problems such as poor coverage area, low signal level and bad signal quality by the improvement of the optimization parameters and changing hardware configuration in detail as a novelty and to improve the quality statistics of a region consisting of 17 base stations. These are; RxQual value from 0.61 to 0.57, average signal quality from 0.19 to 0.16, mean opinion score (MOS) for downlink from 4.01 to 4.16, uplink from 3.65 to 3.79 to increase the capacity of subscribers it is provided. The handover (HO) success rate, which is used to mean inter-cell transfer, is 96% to 99%, call set-up success rate is 95.27% to 97.13%, call retainability is 95.79% to 98.03% and call integrity is reached to 97.23% from 96.77%. The number of calls to the network busy hour call drops from 6 to 1 and the network busy number has decreased from 4 to 1.

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Bu Makaleye Atıf Yap

Başyiğit, B. (2025). THE SOLUTION OF VOICE TRANSMISSION PROBLEMS DUE TO POOR COVERAGE AND LOW NETWORK QUALITY IN A CELLULAR NETWORK OPERATOR. International Journal of 3D Printing Technologies and Digital Industry, Cilt: 9 Sayı: 3, 681–687. https://doi.org/10.46519/ij3dptdi.1812279

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Kaynakça (23)

  1. Ling, R., Donner, J., “Mobile Communication”, pages 92-94, Polity Press, Cambridge, 2013.
  2. Stüber, G.L., “Principles of Mobile Communication”, pages 117-121 Springer International Publishing, Cham, 2017.
  3. Fazio, P., De Rango, F., Tropea, M., “Prediction and QoS enhancement in new generation cellular networks with mobile hosts: A survey on different protocols and conventional/unconventional approaches”, IEEE Communications Surveys & Tutorials, Vol. 19, Issue 3, Pages 1822-1841, 2017.
  4. Abd El-atty, S. M., Gharsseldien, Z. M., “Performance analysis of an advanced heterogeneous mobile network architecture with multiple small cell layers”, Wireless Networks, Vol. 23, Issue 4, Pages 1169-1190, 2017.
  5. Švraka, R., Mitić, D., Lebl, A., Markov, Ž., “Calculating Limits of Base Station Emission Power in GSM”, Automatika, Vol. 57, Issue 3, Pages 774-781, 2016.
  6. Li, D., Li X., Wan, J., “A cloud-assisted handover optimization strategy for mobile nodes in industrial wireless networks”, Computer Networks, Vol. 128, Issue 9, Pages 133-141, 2017.
  7. Lebl, A., Mitic, D., Trenkic, B., Markov, Z., “Determination of Base Station Emission Power Change in a Mobile Network Cell with Movable Users”, Radioengineering, Vol. 27, Issue 7, Pages 1174-1182, 2018.
  8. Qin, M., Yang, Q., Cheng, N., Zhou, H., Rao, R. R., Shen, X., “Machine Learning Aided Context-Aware Self-Healing Management for Ultra Dense Networks with QoS Provisions”, IEEE Transactions on Vehicular Technology, Vol. 67, Issue 12, Pages 12339-12351, 2018.
  9. Rouskas, A., Kyriazis, G., Komnakos, D. I., “Green Optimization Schemes for Mobile Network Design and Operation”, Wireless Personal Communications, Vol. 96, Issue 2, Pages 3227-3247, 2017.
  10. Fraimis, I. G., Kotsopoulos, S. A., “QoS-based proportional fair allocation algorithm for OFDMA wireless cellular systems”, IEEE Communications Letters, Vol. 15, Issue 10, Pages 1091-1093, 2011.
  11. Chang, I. K., Kim, J. P., Hong, J. S., Lie, C. H., “Design of location areas with QoS considerations in a cellular network”, Telecommunication Systems, Vol. 44, Issue 3-4, Pages 333-345, 2010.
  12. Kadioğlu, R., Dalveren, Y., Kara, A., “Quality of service assessment: a case study on performance benchmarking of cellular network operators in Turkey”, Turkish Journal of Electrical Engineering & Computer Sciences, Vol. 23, Issue 2, Pages 548-559, 2015.
  13. Kora, A. D., Ongbwa B. A. E., Cances, J. P., Meghdadi V., “Accurate radio coverage assessment methods investigation for 3G/4G networks”, Computer Networks, Vol. 107, Issue 6, Pages 246-257, 2016.
  14. Pous, M., Azpúrua, M. A., Silva, F., “Measurement and evaluation techniques to estimate the degradation produced by the radiated transients interference to the GSM system”, IEEE Transactions on Electromagnetic Compatibility, Vol. 57, Issue 6, Pages 1382-1390, 2015.
  15. Salem, Y., Ivanek, L., “Propagation modelling of path loss models for wireless communication in urban and rural environments at 1800 GSM frequency band”, Advances in Electrical and Electronic Engineering, Vol. 14, Issue 2, Pages 139-144, 2016.
  16. Zhang, X., Andrews, J. G., “Downlink Cellular Network Analysis with Multi-Slope Path Loss Models”, IEEE Trans. Communications, Vol. 63, Issue 5, Pages 1881-1894, 2015.
  17. Han, S. Y., Abu-Ghazaleh, N. B., Lee, D., “Efficient and consistent path loss model for mobile network simulation”, IEEE/ACM Transactions on Networking (TON), Vol. 24, Issue 3, Pages 1774-1786, 2016.
  18. Zhekov, S. S., Nazneen, Z., Franek, O., Pedersen, G. F., “Measurement of Attenuation by Building Structures in Cellular Network Bands”, IEEE Antennas and Wireless Propagation Letters, Vol. 17, Issue 12, Pages 2260-2263, 2018.
  19. Das, M., Sahu, B., Bhanja, U., “Coverage Analysis of Mobile Network in Nakagami Fading Channel”, Wireless Personal Communications, Vol. 97, Issue 2, Pages 3261-3276, 2017.
  20. Wang, S., & Ran, C., Nazneen, Z., Franek, O., Pedersen, G. F., “Rethinking cellular network planning and optimization”, IEEE Wireless Communications, Vol. 23, Issue 2, Pages 118-125, 2016.
  21. Tütüncü, B., Kösem, M., “Substrate analysis on the design of wide-band antenna for sub-6 GHz 5G communication”, Wireless Personal Communications, Vol. 125, Issue 2, Pages 1523-1535, 2022.
  22. Imeci, Ş.T., Tütüncü, B., Herceg, L., “Performance-enhanced S-shaped slotted patch antenna for X band/Ku band applications”, Wireless Personal Communications, Vol. 129, Issue 2, Pages 1069-1082, 2023.
  23. Kasar, Ö., Durdağ, U.M., “Realization of A Double-Ridge Horn Antenna with 3D Printing and Aluminum Coating Study For 5G Indoor Applications”, International Journal of 3D Printing Technologies and Digital Industry, Vol. 7, Issue 3, Pages 499-504, 2023