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)
115 lines
3.2 KiB
Python
115 lines
3.2 KiB
Python
"""
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COST-231 Walfisch-Ikegami model.
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Valid for:
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- Frequency: 800-2000 MHz
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- Distance: 20m-5km
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- Urban microcell environments
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Accounts for building heights, street widths, and building separation.
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Reference: COST 231 Final Report, Chapter 4.
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"""
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import math
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from app.propagation.base import PropagationModel, PropagationInput, PropagationOutput
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class Cost231WIModel(PropagationModel):
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@property
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def name(self) -> str:
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return "COST-231-WI"
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@property
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def frequency_range(self) -> tuple:
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return (800, 2000)
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@property
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def distance_range(self) -> tuple:
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return (20, 5000)
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def calculate(self, input: PropagationInput) -> PropagationOutput:
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f = input.frequency_mhz
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d = max(input.distance_m / 1000, 0.02) # km
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hb = max(input.tx_height_m, 4.0)
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hm = max(input.rx_height_m, 1.0)
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# Building parameters (defaults for typical urban)
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h_roof = input.building_height_m or 15.0 # avg building height
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w = input.street_width_m or 20.0 # street width
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b = input.building_separation_m or 30.0 # building separation
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delta_hb = hb - h_roof # TX above rooftop
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delta_hm = h_roof - hm # rooftop above RX
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# Free space loss
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L_fs = 32.45 + 20 * math.log10(d) + 20 * math.log10(f)
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# LOS case
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if delta_hb > 0 and d < 0.5:
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L = L_fs
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return PropagationOutput(
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path_loss_db=L,
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model_name=self.name,
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is_los=True,
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breakdown={"free_space": L_fs, "rooftop_diffraction": 0, "multiscreen": 0},
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)
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# Rooftop-to-street diffraction (L_rts)
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phi = 90.0 # street orientation angle (worst case)
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if phi < 35:
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L_ori = -10 + 0.354 * phi
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elif phi < 55:
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L_ori = 2.5 + 0.075 * (phi - 35)
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else:
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L_ori = 4.0 - 0.114 * (phi - 55)
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L_rts = (
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-16.9
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- 10 * math.log10(w)
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+ 10 * math.log10(f)
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+ 20 * math.log10(delta_hm)
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+ L_ori
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)
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# Multi-screen diffraction (L_msd)
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if delta_hb > 0:
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L_bsh = -18 * math.log10(1 + delta_hb)
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k_a = 54
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k_d = 18
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else:
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L_bsh = 0
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k_a = 54 - 0.8 * abs(delta_hb)
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if d >= 0.5:
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k_a = max(k_a, 54 - 0.8 * abs(delta_hb) * (d / 0.5))
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k_d = 18 - 15 * abs(delta_hb) / h_roof
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k_f = -4 + 0.7 * (f / 925 - 1) # medium city
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if input.environment == "urban":
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k_f = -4 + 1.5 * (f / 925 - 1)
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L_msd = (
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L_bsh
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+ k_a
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+ k_d * math.log10(d)
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+ k_f * math.log10(f)
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- 9 * math.log10(b)
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)
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# Total NLOS loss
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if L_rts + L_msd > 0:
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L = L_fs + L_rts + L_msd
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else:
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L = L_fs
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return PropagationOutput(
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path_loss_db=L,
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model_name=self.name,
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is_los=False,
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breakdown={
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"free_space": L_fs,
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"rooftop_diffraction": max(L_rts, 0),
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"multiscreen": max(L_msd, 0),
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},
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)
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