Plasma State-Aware Adaptive Filtration (PSA-AF): A Hybrid stochastic modeling for multi-band satellite communication systems.
DOI:
https://doi.org/10.65405/bbsf4c18الكلمات المفتاحية:
Solar plasma effects, satellite links, adaptive signal processing, stochastic channel modeling, Markov processes, signal-to-noise ratio (SNR), bit error rate (BERالملخص
the propagation of radio signals through the solar plasma environment introduces random fluctuations that can severely impair the e-performance of satellite and deep-space communication links. Plasma turbulence generates time varying scintillation and waveform distortion, which in turn reduce signal quality and increase error rates, particularly during periods of intense solar activity. In response to these challenges, this study is proposed technique employs a Continuous-Time Markov Chain (CTMC) to model the probabilistic evolution of solar plasma conditions, categorized into Calm, Moderate, and Stormy states. This stochastic representation is combined with a frequency-dependent scattering model to continuously estimate the noise characteristics of the propagation channel. Based on this estimate, the plasma state-aware adaptive filter algorithm (PSA-AF) that dynamically mitigates plasma noise and updates its parameters to improve the received signal quality. Performance evaluations conducted over the L, C, X, and Ka bands confirm L-band is the highest scattering (~3×10¹³ m²) with high variability and Ka-band is Lowest scattering (~1×10¹⁵ m²) with relative stability this matched with theoretical relationship: σ ∝ 1/f² for coefficient of determination R2=0.999. Relative to conventional fixed-gain receivers, the PSA-AF algorithm an average SNR gain of 4.95 dB for a target BER of ×110-6, and 52.4% reduction in Bit Error Rate (BER) under stormy plasma conditions.
التنزيلات
المراجع
[1] A. C. K. Soong et al., “A novel continuous-time Markov chain-based model for performance analysis of hybrid free space optics and radio frequency communications”, Applied Sciences, vol. 15, no. 4, p. 1935, Feb. 2025.
[2] B. Biswas, J. Guterl, and S. Poletti, “A hybrid full-wave Markov chain approach to calculating radio-frequency wave scattering from scrape-off layer filaments, ” Journal of Plasma Physics, vol. 87, no. 6, 2021.
[3] B. E. Proctor, “The impact of space weather on satellite communications and navigation systems,” Journal of Space Weather and Space Climate, vol. 12, p. 30, 2022.
[4] C. C. Ko and C. H. Wu, “Variable step-size LMS algorithm with a gradient-based weighted average,” IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 58, no. 6, pp. 351–355, 2011. DOI: 10.1109/TCSII.2011.2158730
[5] C. S. Carrano et al., “Impacts of ionospheric scintillations on GPS receivers
Intended for equatorial aviation applications,” Radio Sci., 47, RS4007, doi:10.1029/2012RS004995, July 2012.
[6] D. D. Morabito, “Solar corona amplitude scintillation modeling and comparison to measurements at X-band and Ka-band,” The Interplanetary Network Progress Report, vol. 42-153, pp. 1–35, May 2003.
[7] F. Alimenti, A. Battistini, and B. Neri, “K/Ka-Band Very High Data-Rate Receivers: A Viable Solution for Future Moon Exploration Missions,” Electronics, vol. 8, no. 3, p. 349, Mar. 2019.
[8] F. F. Chen, “Introduction to Plasma Physics and Controlled Fusion”, 3rd ed. Cham, Switzerland: Springer, 2016.
[9] J. G. Proakis and M. Salehi, “Digital Communications, ” 5th ed. New York: McGraw-Hill, 2007.
[10] J. M. Kelrich et al., “Modeling of Plasma Turbulence Effects on Radio Wave Propagation for Space Communications,” IEEE Trans. Antennas Propagation., vol. 69, no. 4, pp. 2105–2118, Apr. 2021.
[11] M. J. Bentum et al., “A Roadmap Towards a Space-Based Radio Telescope for Low-Frequency Radio Astronomy,” Adv. Space Res., vol. 65, no. 2, pp. 856–867, Jan. 2020.
[12] M. M. Bisi et al., “Advances in space weather modeling and forecasting for satellite communications,” Frontiers in Astronomy and Space Sciences, vol. 9, 2022.
[13] S. Haykin, “Adaptive Filter Theory,” 5th ed. Upper Saddle River, NJ, USA: Pearson Education, 2014.
[14] X. Pan, Y. Zhan, P. Wan, and J. Lu, "Review of channel models for deep space communications,” Science China Information Sciences, vol. 61, no. 4, p. 040304, 2018.
[15] Y. Feria, M. Belongie, and S. Butman, “Solar Scintillation Effects on Telecommunication Links at Ka-band and X-band, ” The Telecommunications and Data Acquisition Progress Report, vol. 42-129, pp. 1-12, Jan.-Mar. 1997.
[16] NOAA Space Weather Prediction Center. (2023). Planetary K-index. Boulder, CO: National Oceanic and Atmospheric Administration. Retrieved from https://www.swpc.noaa.gov/products/planetary-k-index
bcxta fomnbxxnis support and b
التنزيلات
منشور
إصدار
القسم
الرخصة
الحقوق الفكرية (c) 2026 مجلة العلوم الشاملة

هذا العمل مرخص بموجب Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.









