On forecasting overlay channel quality

Recieved: 04/09/2025

Accepted: 05/08/2025

Keywords: time series forecasting, vector autoregression (VAR), weighted quantiles, adaptive parameter tuning, data transmission channel quality

To cite this article

Guo Fengrui, Korolev V.Yu., Smelyanskii R.L. On forecasting overlay channel quality. // Moscow University Journal. Series 15. Computational Mathematics and Cybernetics. 2025. N 4, p.17-25 https://doi.org/10.55959/MSU/0137–0782–15–2025–49–4–17–25.

This work is licensed under a Сreative Commons Atribiution - NonCommercial 4.0 International (CC BY-NC 4.0)

Guo Fengrui (Lomonosov Moscow State University (MSU))
Korolev V.Yu. (Lomonosov Moscow State University (MSU))
Smelyanskii R.L. (Lomonosov Moscow State University (MSU))

Abstract

This study presents a modified vector autoregression (VAR) method for forecasting the quality metrics of overlay channels. The modification involves the introduction of weighted coefficients for time series quantiles, with two distinct approaches proposed for calculating these weights: exponential weighting (EVAR) and linear weighting (LVAR). Experimental results demonstrate that the proposed method improves prediction accuracy by 2.6% to 25.2% compared to classical AR and VAR methods, albeit at the expense of higher computational complexity.