From 62919d668c475a9191ff9cc8c4016a3baee1667c Mon Sep 17 00:00:00 2001
From: Daniel Friesel <daniel.friesel@uos.de>
Date: Wed, 8 May 2019 16:30:47 +0200
Subject: add cpu cycles -> cpu energy and packet size -> tx energy for
 protocolmodeling

---
 lib/size_to_radio_energy.py | 51 +++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 51 insertions(+)
 create mode 100644 lib/size_to_radio_energy.py

(limited to 'lib/size_to_radio_energy.py')

diff --git a/lib/size_to_radio_energy.py b/lib/size_to_radio_energy.py
new file mode 100644
index 0000000..0b5cfd2
--- /dev/null
+++ b/lib/size_to_radio_energy.py
@@ -0,0 +1,51 @@
+"""
+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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