A Deep Learning Framework for Evaluating the Over-the-Air Performance of the Antenna in Mobile Terminals
Abstract
:1. Introduction
- The proposed framework introduces a novel antenna performance prediction model, which can be used for preliminary assessment of SAR and EIRP while reducing the number of repetitive simulations with commercial software on the specialized computational platform;
- The study converts the features of the antenna and the internal components of the mobile phone into a near-field EMF distribution on the Huygens’ box, which simplifies the input of the DL model;
- A DL model based on the divide-and-conquer method [15] is proposed. It divides the estimation for SAR and EIRP into eight modules, reducing the training complexity and enhancing the convergence rate;
2. The Proposed Method
2.1. The Workflow of the Proposed Method
- A phone in FS;
- A phone mounted in the “cheek” position on the head phantom (this includes the “cheek” position for both the left and right ears);
- PDA (Personal Digital Assistant) grip in “data” mode (for both the left and right hand);
- “Talk” mode (which includes configurations for the left and right head and hand).
- Additionally, four SAR evaluation configurations are created, including:
- The cheek (left and right) positions of the phone against the Specific Anthropomorphic Mannequin (SAM) phantom;
- Tilt (left and right) positions of the phone against the SAM phantom.
2.2. RTEEMF-PhoneAnts Architecture
3. Experiment Configurations
3.1. Dataset Generation
3.2. Data Preprocessing for RTEEMF-PhoneAnts
3.3. Training Configurations for RTEEMF-PhoneAnts
3.4. Evaluation Criteria and Numerical Validation
4. Experiment Results
4.1. Performance of the Proposed Model
4.2. Efficiency of the Proposed Model
4.3. Model Generalization across Diverse Antenna Types
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
RTEEMF-PhoneAnts | Real-Time Evaluation Electromagnetic Field–Phone Antennas | DL | Deep Learning |
NEMF | Near-field Electromagnetic Field | EMF | Electromagnetic Field |
EIRP | Effective Isotropic Radiated Power | TRP | Total Radiated Power |
SAR | Specific Absorption Rate | WBSAR | Whole-Body Average SAR |
SAR-1g | averaged peak SAR in 1g | SAR-10g | averaged peak SAR in 10g |
WSR | Wilcoxon Signed Rank Test | FSV | Feature Selection Validation Method |
R&D | Research and Development | CTIA | Cellular Telecommunications and Internet Association |
IEC | International Electrotechnical Commission | IEEE | Institute of Electrical and Electronics Engineers Engineers |
CAD | Computer-Aided Design | FS | Free Space |
FDTD | Finite Difference Time Domain | PDA | Personal Digital Assistant |
SAM | Specific Anthropomorphic Mannequin | IFAs | Inverted-F Antennas |
PIFAs | Printed IFAs | Ant | Antenna |
RMSE | Root Mean Squared Error | RMS | Root Mean Square |
SS | Stratified Sampling | LOAO | Leave-One-Antenna-Out |
ADM | Amplitude Difference Measure | FDM | Feature Difference Measure |
GDM | Global Difference Measure | 3GPP | 3rd Generation Partnership Project |
UE | User Equipment | UL | Uplink |
OLED | Organic Light-Emitting Diode |
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fre (MHz) | Bands | Ant. | |||||
---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | ||
850 | GSM850,WCDMA | √ | √ | √ | √ | √ | √ |
900 | GSM900,UMTS900 | √ | √ | √ | √ | √ | √ |
1800 | GSM1800, WCDMA,FDD-LTE | √ | √ | √ | √ | √ | √ |
1900 | GSM1900,TD-SCDMA,TDD-LTE | √ | √ | √ | √ | √ | √ |
2000 | TD-SCDMA | √ | √ | √ | √ | √ | |
2100 | WCDMA,CDMA2000 | √ | √ | √ | √ | √ | √ |
2600 | TDD-LTE | √ | √ | √ | |||
Number of antennas | 10 | 1 | 1 | 7 | 1 | 14 | |
Number of samples | 2400 | 200 | 220 | 1600 | 180 | 2400 |
Configurations | 25th Percentile | 75th percentile | Z-Value | p-Value | ||||
---|---|---|---|---|---|---|---|---|
SEMCAD | RTEEMF-PhoneAnts | SEMCAD | RTEEMF-PhoneAnts | |||||
“cheek” position (W/kg) | left | WBSAR | 0.05 | 0.05 | 0.13 | 0.12 | −0.20 | 0.84 |
SAR-1g | 6.35 | 6.74 | 20.43 | 20.84 | −0.06 | 0.95 | ||
SAR-10g | 1.81 | 1.79 | 13.66 | 13.78 | −1.77 | 0.08 | ||
right | WBSAR | 0.05 | 0.05 | 0.13 | 0.13 | −0.71 | 0.48 | |
SAR-1g | 14.50 | 13.31 | 38.40 | 40.35 | −0.20 | 0.84 | ||
SAR-10g | 7.70 | 7.40 | 16.99 | 16.65 | −0.22 | 0.83 | ||
“tilt” position (W/kg) | left | WBSAR | 0.06 | 0.06 | 0.13 | 0.13 | −0.20 | 0.84 |
SAR-1g | 2.18 | 2.26 | 13.89 | 15.11 | −0.59 | 0.56 | ||
SAR-10g | 1.27 | 1.27 | 5.80 | 5.92 | −1.07 | 0.29 | ||
right | WBSAR | 0.06 | 0.06 | 0.13 | 0.12 | −0.82 | 0.41 | |
SAR-1g | 7.92 | 7.41 | 23.37 | 20.89 | 0.00 | 1.00 | ||
SAR-10g | 2.15 | 2.03 | 8.30 | 8.05 | −0.47 | 0.64 | ||
free space (dB) | TRP | 2.53 | 1.69 | 3.56 | 3.91 | 0.00 | 1.00 | |
“cheek” position (dB) | left | TRP | −6.02 | −5.04 | −0.08 | −0.04 | 0.00 | 1.00 |
right | TRP | −5.59 | −5.42 | 0.10 | 0.11 | −1.37 | 0.17 | |
“data” mode (dB) | left | TRP | 0.32 | 0.18 | 1.65 | 1.55 | −1.77 | 0.08 |
right | TRP | −0.36 | −0.33 | 1.80 | 1.96 | 0.00 | 1.00 | |
“talk” mode (dB) | left | TRP | −0.34 | −0.34 | 2.00 | 1.95 | −0.63 | 0.53 |
right | TRP | −8.70 | −8.43 | −4.37 | −2.93 | −1.37 | 0.17 |
Configurations | Time Cost (min) | ||||
---|---|---|---|---|---|
Full-Wave Simulation for One Band | RTEEMF-PhoneAnts | ||||
Position of Phone | Simulation | Training (Number of Training Data = 7000, Batch Size = 4, Epoch = 200) | Inference (Batch Size = 1) | ||
SAR evaluation | Left cheek | 0.5 | 20 | 29,167 | 2.025 |
Left tilt | 2 | 24 | |||
Right cheek | 0.5 | 20 | |||
Right tilt | 2 | 24 | |||
OTA evaluation | Phone in free space | 0 | 2 | ||
Left cheek | 0 | 0 | |||
Right cheek | 0 | 0 | |||
Left hand in “data” mode | 3 | 30 | |||
Right hand in “data” mode | 3 | 30 | |||
Left hand and head in “talk” mode | 4 | 65 | |||
Right hand and head in “talk” mode | 4 | 65 |
Configurations | Mean ± Std of Deviation (%), | ||||||||
---|---|---|---|---|---|---|---|---|---|
Stratified Sampling | Leave-One-Antenna-Out | ||||||||
Ant.1 | Ant.2 | Ant.3 | Ant.4 | Ant.5 | Ant.6 | ||||
“cheek” position | left | WBSAR | 5.84 ± 2.52 | 6.35 ± 4.25 | 7.82 ± 4.61 | 4.97 ± 4.07 | 9.5 ± 3.66 | 8.51 ± 3.58 | 9.06 ± 3.94 |
SAR-1g | 5.71 ± 2.84 | 5.99 ± 5.59 | 5.98 ± 3.87 | 5.75 ± 3.36 | 8.25 ± 3.14 | 5.76 ± 4.52 | 8.85 ± 3.61 | ||
SAR-10g | 3.71 ± 0.28 | 5.3 ± 0.43 | 3.73 ± 0.46 | 3.71 ± 0.5 | 4.33 ± 0.56 | 4.58 ± 0.39 | 5.76 ± 0.55 | ||
right | WBSAR | 4.93 ± 2.29 | 6.63 ± 4.04 | 5.09 ± 3.05 | 5.54 ± 2.74 | 8.74 ± 2.95 | 5.26 ± 3.41 | 7.64 ± 4.25 | |
SAR-1g | 2.15 ± 0.75 | 2.5 ± 1.09 | 3.61 ± 1.18 | 2.68 ± 1.12 | 3.92 ± 1.19 | 3.61 ± 1.02 | 3.34 ± 0.77 | ||
SAR-10g | 3.22 ± 1.88 | 3.82 ± 2.81 | 3.24 ± 2.25 | 3.7 ± 2.09 | 5.7 ± 3.76 | 4.36 ± 2.53 | 4.99 ± 2.99 | ||
“tilt” position | left | WBSAR | 5.26 ± 2.63 | 6.07 ± 2.84 | 7.36 ± 4.21 | 7.76 ± 4.72 | 9.69 ± 4.82 | 7.51 ± 3.59 | 8.16 ± 3.61 |
SAR-1g | 7.17 ± 3.97 | 10.5 ± 4.67 | 7.35 ± 5.48 | 7.28 ± 4.23 | 9.98 ± 5.25 | 7.71 ± 7.8 | 11.11 ± 4.69 | ||
SAR-10g | 6.04 ± 2.96 | 7.97 ± 4.7 | 7.35 ± 3.52 | 6.97 ± 4.15 | 10.86 ± 4.6 | 7.39 ± 4.29 | 9.36 ± 3.32 | ||
right | WBSAR | 3.46 ± 1.83 | 4.61 ± 2.93 | 5.57 ± 2.51 | 4.03 ± 2.23 | 4.35 ± 1.97 | 4.21 ± 3.27 | 5.36 ± 2.93 | |
SAR-1g | 6.09 ± 2.88 | 8.43 ± 4.97 | 8.21 ± 3.9 | 8.31 ± 4.13 | 9.79 ± 4.1 | 7.21 ± 5.03 | 9.44 ± 3.22 | ||
SAR-10g | 5.07 ± 2.8 | 6.32 ± 4.25 | 6.22 ± 5.24 | 6.78 ± 3.37 | 7.86 ± 5.49 | 6.67 ± 2.91 | 7.86 ± 4.48 | ||
free space | TRP | 0.24±0.12 | 1.91 ± 0.93 | 2.49 ± 1.16 | 2.97 ± 1.04 | 2.15 ± 1.31 | 2.1 ± 1.03 | 3.32 ± 1.56 | |
“cheek” position | left | TRP | 3.92 ± 1.16 | 5.26 ± 1.82 | 5.24 ± 1.95 | 4.09 ± 2.05 | 6.92 ± 2.32 | 4.08 ± 2.05 | 6.08 ± 2.24 |
right | TRP | 3.48 ± 1.55 | 4.78 ± 3.08 | 3.75 ± 2.66 | 4.76 ± 2.24 | 4.8 ± 2.22 | 4.47 ± 1.67 | 5.4 ± 2.2 | |
“data” mode | left | TRP | 1.9 ± 1.18 | 2.22 ± 2.17 | 3.05 ± 2.11 | 2.8 ± 1.22 | 3.39 ± 2.05 | 2.97 ± 1.58 | 2.95 ± 1.78 |
right | TRP | 1.81 ± 0.82 | 2.35 ± 1.53 | 2.83 ± 1.45 | 2.13 ± 1.41 | 2.06 ± 1.4 | 2.09 ± 1.29 | 2.8 ± 1.09 | |
“talk” mode | left | TRP | 2.87 ± 1.37 | 3.71 ± 1.73 | 2.98 ± 2.35 | 3.05 ± 1.46 | 3.43 ± 2.17 | 3.89 ± 2.09 | 4.44 ± 2.55 |
right | TRP | 7.88 ± 4.49 | 9.41 ± 8.72 | 8.79 ± 6.11 | 8.54 ± 6.72 | 9.83 ± 7.93 | 7.93 ± 8.16 | 12.21 ± 8.4 |
Configurations | 25th Percentile | 75th Percentile | Z-Value | p-Value | ||||
---|---|---|---|---|---|---|---|---|
SEMCAD | RTEEMF-PhoneAnts | SEMCAD | RTEEMF-PhoneAnts | |||||
“cheek” position (W/kg) | left | WBSAR | 0.04 | 0.05 | 0.13 | 0.13 | −1.34 | 0.18 |
SAR-1g | 13.05 | 13.34 | 41.37 | 42.90 | −0.42 | 0.68 | ||
SAR-10g | 5.92 | 5.97 | 18.50 | 18.06 | −0.39 | 0.69 | ||
right | WBSAR | 0.02 | 0.02 | 0.08 | 0.08 | −0.77 | 0.44 | |
SAR-1g | 1.75 | 1.71 | 13.88 | 13.57 | −0.67 | 0.50 | ||
SAR-10g | 1.13 | 1.20 | 7.97 | 7.67 | −0.22 | 0.83 | ||
“tilt” position (W/kg) | left | WBSAR | 0.05 | 0.06 | 0.13 | 0.13 | −0.72 | 0.47 |
SAR-1g | 13.56 | 13.55 | 35.55 | 34.76 | −0.98 | 0.33 | ||
SAR-10g | 7.36 | 7.54 | 17.04 | 18.10 | −2.37 | 0.02 | ||
right | WBSAR | 0.02 | 0.02 | 0.08 | 0.08 | −1.13 | 0.26 | |
SAR-1g | 2.27 | 2.16 | 14.37 | 14.24 | −0.38 | 0.70 | ||
SAR-10g | 1.27 | 1.34 | 8.18 | 7.61 | −0.44 | 0.66 | ||
free space (dB) | TRP | 2.99 | 2.92 | 3.60 | 3.73 | −0.04 | 0.97 | |
“cheek” position (dB) | left | TRP | −6.43 | −6.89 | −0.09 | −0.09 | −0.05 | 0.96 |
right | TRP | −5.95 | −5.37 | 0.11 | 0.11 | −1.66 | 0.10 | |
“data” mode (dB) | left | TRP | 0.37 | 0.32 | 1.72 | 1.79 | −1.17 | 0.24 |
right | TRP | −0.35 | −0.34 | 2.40 | 2.36 | −1.09 | 0.28 | |
“talk” mode (dB) | left | TRP | −0.33 | −0.34 | 2.36 | 2.25 | −0.17 | 0.86 |
right | TRP | 4.64 | 4.43 | 9.11 | 8.02 | −0.16 | 0.87 |
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Chen, Y.; Qi, D.; Yang, L.; Wu, T.; Li, C. A Deep Learning Framework for Evaluating the Over-the-Air Performance of the Antenna in Mobile Terminals. Sensors 2024, 24, 5646. https://doi.org/10.3390/s24175646
Chen Y, Qi D, Yang L, Wu T, Li C. A Deep Learning Framework for Evaluating the Over-the-Air Performance of the Antenna in Mobile Terminals. Sensors. 2024; 24(17):5646. https://doi.org/10.3390/s24175646
Chicago/Turabian StyleChen, Yuming, Dianyuan Qi, Lei Yang, Tongning Wu, and Congsheng Li. 2024. "A Deep Learning Framework for Evaluating the Over-the-Air Performance of the Antenna in Mobile Terminals" Sensors 24, no. 17: 5646. https://doi.org/10.3390/s24175646