Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal The Indonesian Journal of Computer Science
Du Chunling
Unknown Affiliation
Computer Science & IT Electrical & Electronics Engineering Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
RTSO: Comprehensive Framework for Real-Time Frequency Channel Occupancy and Spectrum Hole Detection Ntuli, Elesa; Du Chunling
The Indonesian Journal of Computer Science Vol. 14 No. 4 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i4.4878

Abstract

Efficient spectrum utilization remains a key challenge in modern wireless communications, especially in dynamic environments with limited spectrum availability. This paper introduces Real-Time Spectrum Optimization (RTSO), a framework that combines Geo-Location Spectrum Databases (GLSDBs) with real-time spectrum sensing to detect frequency channel occupancy and identify spectrum holes. RTSO uses advanced energy detection techniques, including Additive White Gaussian Noise (AWGN) modelling, to distinguish between idle and occupied channels accurately. It incorporates mathematical tools such as occupancy time and Frequency Channel Occupation (FCO) metrics for effective spectrum analysis. A notable feature is a revisit-time-based sensing mechanism that infers channel status during intermittent scans. Practical evaluations demonstrated improved detection accuracy, reduced false alarms, and better decision-making for dynamic access to available channels. Key performance metrics, including latency, bandwidth, and error rate, were compared with baseline methods, showing substantial gains in efficiency. This work provides a valuable contribution to cognitive radio systems and dynamic spectrum access, paving the way for more intelligent and adaptive spectrum management strategies in real-time communication networks.
A Dynamic Framework for Optimizing Spectrum Utilization and Interference Mitigation in White Space Networks Ntuli, Elesa; Du Chunling; Moshe Timothy Masonta
The Indonesian Journal of Computer Science Vol. 14 No. 4 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i4.4880

Abstract

This study presents a framework for optimizing spectrum utilization and reducing interference in White Space (WS) networks using the Interference Mitigation Decision Framework (IMDF). The IMDF combines Geo-Location Spectrum Databases (GLSDs), reactive spectrum sensing, and Software Defined Radios (SDRs) to address the limitations of traditional spectrum allocation methods. The IMDF enhances allocation, reduces interference, and improves network performance by monitoring real-time spectrum usage. Simulations comparing IMDF with traditional GLSD-based methods show a 70% bandwidth saving, compared to 40% in traditional approaches. Additionally, IMDF reduces interference events by 30%, improving Quality of Service (QoS) and mitigating Cross Network Interference (CNI). With dynamic spectrum management, IMDF achieves 70% spectrum utilization, while traditional systems only reach 40%. These results demonstrate IMDF's effectiveness in dynamic environments, offering a robust solution for wireless service demand and interference mitigation in increasingly WS networks. The IMDF’s adaptability, combined with its efficient resource management, makes it a promising framework for the future of spectrum allocation in increasingly congested network environments.
Co-Authors Moshe Timothy Masonta Ntuli, Elesa