Improving Data Transmission in a Wireless Communication Network Using Remote Radio Control of Different Noise Channels Technique

Wireless communication networks are increasingly pivotal in modern technology, yet they are frequently hampered by noise interference, which degrades data transmission quality. This paper introduces a novel technique that employs remote radio control to manage and mitigate different noise channels, thereby enhancing data transmission efficiency. By leveraging advanced signal processing algorithms, fuzzy logic, and artificial neural networks (ANNs), the proposed method dynamically adjusts to varying noise conditions, ensuring optimal performance. The consistent decline in data transmission in wireless communication networks has negatively impacted businesses reliant on data for daily operations. This issue arises from interference, low signal-to-noise ratio (SNR), and reduced throughput. To address this, a technique using remote radio control of different noise channels can improve data transmission. The approach involves several steps: characterizing and modeling data communication based on key performance indicators (KPIs), designing a remote-control rule base to facilitate data transmission, training an ANN within this rule base to enhance data transmission efficiency, creating a SIMULINK model for remote radio control sensors, developing an algorithm to implement the process, integrating models, and simulating the integrated model for analysis and validation. Results show that conventional interference in data transmission is 178.6 watt/m², which decreases to 148.8 watt/m² with remote control, marking a 16.7% improvement. The conventional SNR of 0.837 dB improves to 1.004 dB with remote control. Additionally, conventional throughput, which was 66.67 kbps, increases to 80 kbps with remote control, enhancing data transmission. Moreover, the conventional packet reception in April was 185 kbps, increasing to 188 kbps with remote control, reflecting a 1.62% improvement. In summary, using remote radio control of different noise channels significantly enhances data transmission in wireless communication networks, reducing interference, and increasing both SNR and throughput. This method offers a practical solution to the challenges faced by businesses relying on stable data communication.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-09-09
DOI
https://doi.org/10.5281/zenodo.13737477
Primary Topic
Internet of Things and AI
Type
article
Field-Weighted Citation Impact
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article

Improving Data Transmission in a Wireless Communication Network Using Remote Radio Control of Different Noise Channels Technique

Zenodo (CERN European Organization for Nuclear Research)
Internet of Things and AI
article

Improving Data Transmission in a Wireless Communication Network Using Remote Radio Control of Different Noise Channels Technique

article en

Abstract

Wireless communication networks are increasingly pivotal in modern technology, yet they are frequently hampered by noise interference, which degrades data transmission quality. This paper introduces a novel technique that employs remote radio control to manage and mitigate different noise channels, thereby enhancing data transmission efficiency. By leveraging advanced signal processing algorithms, fuzzy logic, and artificial neural networks (ANNs), the proposed method dynamically adjusts to varying noise conditions, ensuring optimal performance. The consistent decline in data transmission in wireless communication networks has negatively impacted businesses reliant on data for daily operations. This issue arises from interference, low signal-to-noise ratio (SNR), and reduced throughput. To address this, a technique using remote radio control of different noise channels can improve data transmission. The approach involves several steps: characterizing and modeling data communication based on key performance indicators (KPIs), designing a remote-control rule base to facilitate data transmission, training an ANN within this rule base to enhance data transmission efficiency, creating a SIMULINK model for remote radio control sensors, developing an algorithm to implement the process, integrating models, and simulating the integrated model for analysis and validation. Results show that conventional interference in data transmission is 178.6 watt/m², which decreases to 148.8 watt/m² with remote control, marking a 16.7% improvement. The conventional SNR of 0.837 dB improves to 1.004 dB with remote control. Additionally, conventional throughput, which was 66.67 kbps, increases to 80 kbps with remote control, enhancing data transmission. Moreover, the conventional packet reception in April was 185 kbps, increasing to 188 kbps with remote control, reflecting a 1.62% improvement. In summary, using remote radio control of different noise channels significantly enhances data transmission in wireless communication networks, reducing interference, and increasing both SNR and throughput. This method offers a practical solution to the challenges faced by businesses relying on stable data communication.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 46%
Internet of Things and AI
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Improving Data Transmission in a Wireless Communication Network Using Remote Radio Control of Different Noise Channels Technique · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS