mytec
defa3ad440
Major refactoring of RFCP backend: - Modular propagation models (8 models) - SharedMemoryManager for terrain data - ProcessPoolExecutor parallel processing - WebSocket progress streaming - Building filtering pipeline (351k → 15k) - 82 unit tests Performance: Standard preset 38s → 5s (7.6x speedup) Known issue: Detailed preset timeout (fix in 3.1.0)
63 lines
1.7 KiB
Python
63 lines
1.7 KiB
Python
"""
|
|
COST-231 Hata model (extension of Okumura-Hata).
|
|
|
|
Valid for:
|
|
- Frequency: 1500-2000 MHz
|
|
- Distance: 1-20 km
|
|
|
|
Better for LTE bands than original Okumura-Hata.
|
|
"""
|
|
|
|
import math
|
|
from app.propagation.base import PropagationModel, PropagationInput, PropagationOutput
|
|
|
|
|
|
class Cost231HataModel(PropagationModel):
|
|
|
|
@property
|
|
def name(self) -> str:
|
|
return "COST-231-Hata"
|
|
|
|
@property
|
|
def frequency_range(self) -> tuple:
|
|
return (1500, 2000)
|
|
|
|
@property
|
|
def distance_range(self) -> tuple:
|
|
return (100, 20000)
|
|
|
|
def calculate(self, input: PropagationInput) -> PropagationOutput:
|
|
f = input.frequency_mhz
|
|
d = max(input.distance_m / 1000, 0.1)
|
|
hb = max(input.tx_height_m, 1.0)
|
|
hm = max(input.rx_height_m, 1.0)
|
|
|
|
# Mobile antenna correction (medium city)
|
|
a_hm = (1.1 * math.log10(f) - 0.7) * hm - (1.56 * math.log10(f) - 0.8)
|
|
|
|
# Metropolitan center correction
|
|
C_m = 3 if input.environment == "urban" else 0
|
|
|
|
L = (
|
|
46.3
|
|
+ 33.9 * math.log10(f)
|
|
- 13.82 * math.log10(hb)
|
|
- a_hm
|
|
+ (44.9 - 6.55 * math.log10(hb)) * math.log10(d)
|
|
+ C_m
|
|
)
|
|
|
|
return PropagationOutput(
|
|
path_loss_db=L,
|
|
model_name=self.name,
|
|
is_los=False,
|
|
breakdown={
|
|
"base_loss": 46.3,
|
|
"frequency_term": 33.9 * math.log10(f),
|
|
"height_gain": -13.82 * math.log10(hb),
|
|
"mobile_correction": -a_hm,
|
|
"distance_term": (44.9 - 6.55 * math.log10(hb)) * math.log10(d),
|
|
"metro_correction": C_m,
|
|
},
|
|
)
|