Measurements at 16 central and western Thai sites across five environments produced 8,000 RSRP samples. Path-loss exponents ranged from 2.2 in rural terrain to 4.0 in forest/mountain settings, with distinct fading and shadowing. The parameters support Thai NB-IoT planning but do not represent the entire country, seasons or all operators.
Key findings
- Path-loss exponents ranged from 2.2 in rural to 4.0 in forest/mountain sites; back-calculated Nakagami-m values ranged from 0.44 to 3.51 and shadowing deviations from 4.16 to 8.38 dB. The study described a gradient from sub-Rayleigh forest, m2.
Why this matters globally
Locally calibrated models can improve base-station counts, coverage estimates and blind-spot risk for smart meters, agricultural IoT and public sensors.
Thai researcher contribution
Kittiwat Srivilas and Chaiyod Pirak of TGGS at KMUTNB designed the field measurements and channel analysis using Thai terrain.
Limitations to consider
Sixteen sites in central/western Thailand cannot cover seasonal, indoor, mobile, operator, band or network-load variability nationwide. Sample timing and site balance require the full paper, and back-calculated m depends on model assumptions.
Verify the original sources
IoTRead the original article↗DOI: 10.3390/iot7030054