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Continuous-Wave Propagation Channel-Sounding Measurement System - Testing, Verification, and Measurements
Published on: June 25, 2021
Performance analysis of improved path loss models for millimeter-wave wireless network channels at 28 GHz and 38 GHz
Tolulope T Oladimeji1, Pradeep Kumar1, Mohamed K Elmezughi1
1Discipline of Electrical, Electronic and Computer Engineering, University of KwaZulu-Natal, Durban, South Africa.
This study enhances millimeter wave path loss models for 5G networks. Improved Close In (CI) and Floating Intercept (FI) models offer greater accuracy and consistency in enclosed environments.
Area of Science:
- Wireless Communications
- Electromagnetics
- Signal Propagation
Background:
- Path loss is critical for millimeter wave (mmWave) network deployment, design, and performance assessment.
- Accurate path loss models are essential for high-fidelity wireless channel performance evaluation.
- Existing statistical and empirical models require further refinement for mmWave frequencies.
Purpose of the Study:
- To validate and assess improved versions of the Close In (CI) and Floating Intercept (FI) path loss models.
- To evaluate model performance at 28 and 38 GHz frequency bands in an enclosed environment.
- To analyze the impact of antenna polarization on path loss prediction accuracy.
Main Methods:
- Validation of enhanced CI and FI path loss models using measurement data.
- Testing in an enclosed passageway with Vertical-Horizontal (V-H) and Vertical-Vertical (V-V) antenna polarizations.
- Analysis of Mean Prediction Error (MPE) and Standard Deviation Error (SDE) for model accuracy assessment.
Main Results:
- Enhanced CI and FI models demonstrate superior consistency and accuracy compared to standard models.
- Significant improvements in path loss prediction were observed across different antenna polarizations.
- Improved models exhibit better parameter responsiveness to polarization changes and reduced shadow fading.
Conclusions:
- Modified CI and FI path loss models provide more accurate predictions in enclosed environments for 5G mmWave networks.
- The enhanced models offer improved reliability and reduced prediction errors.
- These validated models are crucial for effective 5G network planning and deployment.
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