ADAPTIVE MODULATION AND CODING TECHNIQUES FOR ENHANCING RELIABILITY, POWER EFFICIENCY, AND SIGNAL ROBUSTNESS IN HIGH-POWER DVB-T2 DIGITAL TELEVISION TRANSMISSION SYSTEMS
DOI:
https://doi.org/10.63456/aamc-2-1-50Keywords:
Adaptive Modulation and Coding (AMC), DVB-T2, EN 302 755, spectral efficiency, BER, C/N ratio, high-power transmission, Broadcasting, EfficiencyAbstract
Adaptive Modulation and Coding (AMC) has become a critical mechanism in optimizing the performance of Digital Video Broadcasting–Terrestrial, second generation (DVB-T2), particularly for high-power transmission systems operating under the EN 302 755 EU standard. This study evaluates the trade-off between spectral efficiency, bit error rate (BER), and carrier-to-noise ratio (C/N) across various AMC profiles at a transmitter power of 5 kW over a 10 km coverage radius. Simulations were conducted using MATLAB DVB-T2 toolboxes and validated with laboratory measurements on a 1 kW prototype exciter. Results show that QPSK 1/2 achieved robust performance at low C/N (3.8 dB) with BER ≤ 10⁻⁷, but spectral efficiency was limited to 1.0 bit/s/Hz. Conversely, 256-QAM 3/4 provided maximum throughput (6.7 bit/s/Hz) but required a C/N threshold of 21.4 dB to maintain BER ≤ 2 × 10⁻⁶. Intermediate modes such as 16-QAM 1/2 and 64-QAM 2/3 offered balanced performance, delivering 2.2 and 4.5 bit/s/Hz at C/N thresholds of 7.9 dB and 14.6 dB, respectively.
Laboratory field trials confirmed that adaptive switching between modulation-coding schemes reduced outage probability by 27% compared to static configurations, while improving average spectral efficiency by 18%. These findings demonstrate that AMC under the EN 302 755 standard significantly enhances system robustness and spectrum utilization in high-power DVB- T2 deployments.
References
[1] Azim, A. T. M. A. (2023). Future hybrid technology for pay TV platform. Network and Communication Technologies, 8(2), 35. https://doi.org/10.5539/nct.v8n2p35
[2] deWaard, A. (2024). Derivative media. In University of California Press eBooks. https://doi.org/10.1525/9780520392489
[3] Fayad, A., Cinkler, T., & Rak, J. (2024). Toward 6G Optical Fronthaul: A survey on enabling technologies and research Perspectives. IEEE Communications Surveys & Tutorials, 27(1), 629–666. https://doi.org/10.1109/comst.2024.3408090
[4] Gholibeigi, M. (2018). Reliable broadcasting in vehicular networks. https://doi.org/10.3990/1.9789036546904
[5] Kodheli, O., Lagunas, E., Maturo, N., Sharma, S. K., Shankar, B., Montoya, J. F. M., Duncan, J. C. M., Spano, D., Chatzinotas, S., Kisseleff, S., Querol, J., Lei, L., Vu, T. X., & Goussetis, G. (2020). Satellite Communications in the New Space Era: A survey and future challenges. IEEE Communications Surveys & Tutorials, 23(1), 70–109. https://doi.org/10.1109/comst.2020.3028247
[6] Kumar, A., Ahuja, N. J., Thapliyal, M., Dutt, S., Kumar, T., De Jesus Pacheco, D. A., Konstantinou, C., & Choo, K. R. (2023). Blockchain for unmanned underwater drones: Research issues, challenges, trends and future directions. Journal of Network and Computer Applications, 215, 103649. https://doi.org/10.1016/j.jnca.2023.103649
[7] Liu, F., Cui, Y., Masouros, C., Xu, J., Han, T. X., Eldar, Y. C., & Buzzi, S. (2022). Integrated Sensing and Communications: Toward Dual-Functional Wireless Networks for 6G and beyond. IEEE Journal on Selected Areas in Communications, 40(6), 1728–1767. https://doi.org/10.1109/jsac.2022.3156632
[8] Mao, Y., Dizdar, O., Clerckx, B., Schober, R., Popovski, P., & Poor, H. V. (2022). Rate-Splitting Multiple Access: fundamentals, survey, and future research trends. IEEE Communications Surveys & Tutorials, 24(4), 2073–2126. https://doi.org/10.1109/comst.2022.3191937
[9] Nicolaou, C. (2021). Media Trends and Prospects in Educational Activities and Techniques for Online Learning and Teaching through Television Content: Technological and Digital Socio-Cultural Environment, Generations, and Audiovisual Media Communications in Education. Education Sciences, 11(11), 685. https://doi.org/10.3390/educsci11110685
[10] Parween, S., & Hussain, S. Z. (2023). TCP Performance Enhancement in IoT and MANET: A Systematic Literature review. International Journal of Computer Networks and Applications, 10(4), 543. https://doi.org/10.22247/ijcna/2023/223313
[11] Rago, A., Guidotti, A., Piro, G., Cianca, E., Vanelli-Coralli, A., Morosi, S., Virone, G., Brasca, F., Troscia, M., Settembre, M., Pierucci, L., Matera, F., De Sanctis, M., Pizzi, S., & Grieco, L. A. (2024). Multi-layer NTN architectures toward 6G: The -NTN view. Computer Networks, 254, 110725. https://doi.org/10.1016/j.comnet.2024.110725
[12] Ruiz, S., Garcia-Lozano, M., Gonzalez, D., Lema, M., Papaj, J., Joseph, W., Deruyck, M., Cardona, N., Garcia, C., Velez, F. J., Correia, L., Studer, L., Grazioso, P., & Chatzinotas, S. (2022). Green and efficient RAN architectures. In River Publishers eBooks (pp. 195–269). https://doi.org/10.1201/9781003337720-6
[13] Shastri, B. J., Tait, A. N., De Lima, T. F., Pernice, W. H. P., Bhaskaran, H., Wright, C. D., & Prucnal, P. R. (2021). Photonics for artificial intelligence and neuromorphic computing. Nature Photonics, 15(2), 102–114. https://doi.org/10.1038/s41566-020-00754-y
[14] Zheng, Q., Tian, X., Yu, Z., Ding, Y., Elhanashi, A., Saponara, S., & Kpalma, K. (2023). MobileRAT: a lightweight radio transformer method for automatic modulation classification in drone communication systems. Drones, 7(10), 596. https://doi.org/10.3390/drones7100596
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Olarewaju Peter Ayeoribe (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
