Improved Stochastic-Based Interference Avoidance Algorithm for Fifth Generation Communication

• Published in: Journal of engineering and sustainable development (Online) Vol. 29; no. 5; pp. 643 - 652
• Main Authors: Ahmed Saeed Obied, Hind Mowafaq Taha, Ahmad Shahidan Abdullah
• Format: Journal Article
• Language: Arabic; English
• Published: Mustansiriyah University/College of Engineering 31.08.2025
• Subjects: Fifth generation communication; Interference; Spectral efficiency; Ultra-dense networks
• ISSN: 2520-0917; 2520-0925
• DOI: 10.31272/jeasd.2648

Interference cancellation is a prominent concern in 5G communication. In 5G wireless architecture, self-interference cancellation may double the spectral and energy efficiency of ultra-dense networks using the full-duplex approach if implemented successfully. Various circuit blocks and optimization algorithms have been proposed to mitigate self-interference caused by transmitted signals, as described in the literature. However, addressing self-interference effectively during data transmission in ultra-dense networks remains a challenge. This issue has been addressed by developing an Improved Stochastic-Based Interference Avoidance (ISIA) algorithm that primarily targets the minimization of self-interference and error rates in 5G communication. The ISIA algorithm employs stochastic optimization strategies to adjust power control and other transmission parameters based on monitored channel conditions and interference. It provides efficient optimization in the spatial and frequency domains while considering the hardware setup. In particular, it employs mean field approximation and thresholding for interference management and resource control to optimize spectral and power usage. Numerical and analytical evaluations reveal better efficiency, accuracy, interference reduction, and throughput compared to existing techniques. Results demonstrate a throughput improvement of up to 30% and a 25% reduction in interference, validating the effectiveness of the proposed approach.