Adaptive Resource Allocation in SDR-Based LTE Networks Using Harmonic Analysis and Predictive Load Modeling

Abstract

This paper presents a mathematical framework for adaptive resource allocation in SDR-based LTE networks using harmonic analysis and predictive load modeling. The relevance of the study is determined by the need to improve the efficiency of limited network resources under increasing traffic volumes and growing quality-of-service requirements. The aim of the research is to develop a comprehensive resource optimization approach that integrates harmonic analysis methods with adaptive control algorithms. A modified harmonic analysis model is proposed to account for the non-stationary and multifractal nature of telecommunication traffic by introducing amplitude and phase modulation of harmonic components and applying the generalized Hurst exponent. Model parameters are estimated using an adaptive least squares algorithm with exponential forgetting. The resource allocation task is formulated as a multi-criteria nonlinear optimization problem that accounts for resource utilization efficiency, energy performance, and quality-of-service indicators. The effectiveness of the proposed framework is confirmed by comparative analysis, demonstrating up to a 20% improvement in time–frequency resource utilization, up to a 30% reduction in computational load on the SDR platform, and up to a 20% increase in energy efficiency. The practical significance of the results lies in improving the performance and adaptability of SDR-based LTE networks in dynamic traffic environments.