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"""
Convert data length to radio TX/RX energy.
Contains classes for some embedded CPUs/MCUs. Given a configuration, each
class can convert a cycle count to an energy consumption.
"""
import numpy as np
def get_class(radio_name: str):
"""Return model class for radio_name."""
if radio_name == 'CC1200tx':
return CC1200tx
def _param_list_to_dict(device, param_list):
param_dict = dict()
for i, parameter in enumerate(sorted(device.parameters.keys())):
param_dict[parameter] = param_list[i]
return param_dict
class CC1200tx:
name = 'CC1200tx'
parameters = {
'symbolrate' : [6, 12, 25, 50, 100, 200, 250], # ksps
'txbytes' : [],
'txpower' : [10, 20, 30, 40, 47], # dBm = f(txpower)
}
default_params = {
'symbolrate' : 100,
'txpower' : 47,
}
def get_energy(params):
if type(params) != dict:
return CC1200tx.get_energy(_param_list_to_dict(CC1200tx, params))
power = 8.18053941e+04
power -= 1.24208376e+03 * np.sqrt(params['symbolrate'])
power -= 5.73742779e+02 * np.log(params['txbytes'])
power += 1.76945886e+01 * (params['txpower'])**2
power += 2.33469617e+02 * np.sqrt(params['symbolrate']) * np.log(params['txbytes'])
power -= 6.99137635e-01 * np.sqrt(params['symbolrate']) * (params['txpower'])**2
power -= 3.31365158e-01 * np.log(params['txbytes']) * (params['txpower'])**2
power += 1.32784945e-01 * np.sqrt(params['symbolrate']) * np.log(params['txbytes']) * (params['txpower'])**2
duration = 3.65513500e+02
duration += 8.01016526e+04 * 1/(params['symbolrate'])
duration -= 7.06364515e-03 * params['txbytes']
duration += 8.00029860e+03 * 1/(params['symbolrate']) * params['txbytes']
return power * 1e-6 * duration * 1e-6
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