-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathsystemmodel.py
245 lines (194 loc) · 7.81 KB
/
systemmodel.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
import math
import numpy as np
np.seterr(divide='ignore', invalid='ignore')
# np.random.seed(1)
#if dataset Dk is fixed or not
# f_uav_num=5
# a=np.random.randint(800,1000,size=(f_uav_num,1))
class SystemModel(object):
def __init__(self,f_uav_num=3):
self.f_uav_num = f_uav_num # 底层无人机数，K
self.n0 = -174 # dBm/hz 噪声功率谱密度
self.beita = 1.42*10**-4 # -60db
self.power_j = 0.1
self.subbandwidth = 5*10**4
self.N_B = (10**(-3))*self.subbandwidth*(10**(self.n0/10))
# self.N_B = 10**(-9)
self.num_j = 2
self.p0=80
self.pi=89
self.U_tip=120
self.v0=4.03
self.zeta=0.6
self.s=0.05
self.rou=1.225
self.A=0.5
self.k = 0.05
self.a = 9.53
self.b = 0.41
self.Qm = 40
def p_fly(self,v):
sum = 0
e = []
for i in range(4):
P=self.p0*(1+3*v[i]**2/(self.U_tip**2))+self.pi*self.v0/v[i]+0.5*self.zeta*self.s*self.rou*self.A*v[i]**3
sum = sum+P
e.append(P)
return sum,e
#model based on location
def ch_r_jp(self,jammer_p,uav_p,id):
dis_jl = []
G_fl = []
G_jl = []
sum_J = 0
#计算干扰器与无人机的距离
for i in range(self.num_j):
dis_i_jl = (jammer_p[i][0]-uav_p[id][0])**2+(jammer_p[i][1]-uav_p[id][1])**2+(uav_p[id][2])**2
dis_i_jl = math.sqrt(dis_i_jl)
dis_jl.append(dis_i_jl-self.Qm)
Plos = []
for i in range(self.num_j):
s = math.atan(uav_p[id][2]/math.sqrt((jammer_p[i][0]-uav_p[id][0])**2+(jammer_p[i][1]-uav_p[id][1])**2))
angle = s / math.pi * 180
plos = 1/(1+self.a*math.exp(-self.b*(angle-self.a)))
Plos.append(plos)
for i in range(self.num_j):
y = 1/(Plos[i]+(1-Plos[i])*self.k)
d_il= dis_jl[i]
g_jl = y*self.beita/d_il**2
G_jl.append(g_jl)
#干扰器总干扰功率
for i in range(self.num_j): # 干扰器总干扰
j = self.power_j*G_jl[i]
sum_J = sum_J+j
return sum_J
def down_sinr(self,jammer_p, uav_p ,p,id):
channel_SNR_up = []
SINR = []
dis_fl = []
dis_jl = []
G_jl = []
G_fl = []
sum_J = 0
dis_i_fl = (uav_p[id][0]-uav_p[0][0])**2+(uav_p[id][1]-uav_p[0][1])**2+(uav_p[id][2]-uav_p[0][2])**2
dis_fl.append(dis_i_fl)
for j in range(self.num_j):
dis_i_jl = (jammer_p[j][0]-uav_p[id][0])**2+(jammer_p[j][1]-uav_p[id][1])**2+(uav_p[id][2])**2
dis_i_jl = math.sqrt(dis_i_jl)
dis_jl.append(dis_i_jl-self.Qm)
Plos = []
for i in range(self.num_j):
s = math.atan(uav_p[id][2]/math.sqrt((jammer_p[i][0]-uav_p[id][0])**2+(jammer_p[i][1]-uav_p[id][1])**2))
angle = s / math.pi * 180
plos = 1/(1+self.a*math.exp(-self.b*(angle-self.a)))
Plos.append(plos)
d_il = dis_fl[0]
g_fl = self.beita / d_il
G_fl.append(g_fl)
for i in range(self.num_j):
y = 1 / (Plos[i] + (1 - Plos[i]) * self.k)
d_il = dis_jl[i]
g_jl = y * self.beita / d_il ** 2
G_jl.append(g_jl)
# 干扰器总干扰功率
for i in range(self.num_j): # 干扰器总干扰
j = self.power_j * G_jl[i]
sum_J = sum_J + j
sinr = p * G_fl[0] / (sum_J + self.N_B)
SINR = 10 * math.log(sinr)
return SINR
def ofdma_t_up_(self, jammer_p, uav_p ,p):
sum_J = 0
sum_R = 0
channel_SNR_up = []
SINR = []
comm_rate_up = []
noise = []
G_fl = []
G_jl = []
dis_fl = []
dis_jl = []
#计算底层无人机与顶层无人机距离
for i in range(self.f_uav_num):
dis_i_fl = (uav_p[i+1][0]-uav_p[0][0])**2+(uav_p[i+1][1]-uav_p[0][1])**2+(uav_p[i+1][2]-uav_p[0][2])**2
dis_fl.append(dis_i_fl)
#计算干扰器与顶层无人机的距离
for i in range(self.num_j):
dis_i_jl = (jammer_p[i][0]-uav_p[0][0])**2+(jammer_p[i][1]-uav_p[0][1])**2+(uav_p[0][2])**2
dis_i_jl = math.sqrt(dis_i_jl)
dis_jl.append(dis_i_jl-self.Qm)
Plos = []
for i in range(self.num_j):
s = math.atan(uav_p[0][2]/math.sqrt((jammer_p[i][0]-uav_p[0][0])**2+(jammer_p[i][1]-uav_p[0][1])**2))
angle = s / math.pi * 180
plos = 1/(1+self.a*math.exp(-self.b*(angle-self.a)))
Plos.append(plos)
# # 计算白噪声
# for i in range(self.f_uav_num):
# noise.append(10**(-3)*b[i]*10**(self.n0/10))
#计算信道增益
for i in range(self.f_uav_num):
d_il= dis_fl[i]
g_fl = self.beita/d_il
G_fl.append(g_fl)
for i in range(self.num_j):
y = 1/(Plos[i]+(1-Plos[i])*self.k)
d_il= dis_jl[i]
g_jl = y*self.beita/d_il**2
G_jl.append(g_jl)
#干扰器总干扰功率
for i in range(self.num_j): # 干扰器总干扰
j = self.power_j*G_jl[i]
sum_J = sum_J+j
# 通信模型,上行信道
# 计算每个底层无人机与顶层无人机之间的SNR
for i in range(self.f_uav_num):
sinr = p[i]* G_fl[i] / (sum_J + self.N_B)
channel_SNR_up.append(sinr)
SINR.append(10*math.log(sinr))
channel_SNR_up= np.array(channel_SNR_up).reshape(self.f_uav_num, 1)
SINR = np.array(SINR).reshape(self.f_uav_num, 1)
# 计算每个底层无人机与顶层无人机之间数据的传输速率
for i in range(self.f_uav_num):
rate_up= 0.001*self.subbandwidth* math.log2(1+channel_SNR_up[i]) #标量bit/s
comm_rate_up.append(rate_up)
comm_rate_up= np.array(comm_rate_up).reshape(self.f_uav_num, 1)
for i in range(self.f_uav_num):
sum_R = sum_R + comm_rate_up[i][0]
return sum_R, SINR, comm_rate_up
def safe_dis(self, start_loaction,dmin):
uav1 = start_loaction[0]
uav2 = start_loaction[1]
uav3 = start_loaction[2]
uav4 = start_loaction[3]
sum = 0
d23 = math.sqrt((uav2[0]-uav3[0])**2+(uav2[1]-uav3[1])**2+(uav2[2]-uav3[2])**2)
d24 = math.sqrt((uav2[0]-uav4[0])**2+(uav2[1]-uav4[1])**2+(uav2[2]-uav4[2])**2)
d34 = math.sqrt((uav3[0]-uav4[0])**2+(uav3[1]-uav4[1])**2+(uav3[2]-uav4[2])**2)
d = [d23,d24,d34]
for i in range(3):
if d[i] < dmin:
sum = sum + 1
return sum
# def safe_dis(self, start_loaction,i,dmin):
# uav1 = start_loaction[0]
# uav2 = start_loaction[1]
# uav3 = start_loaction[2]
# uav4 = start_loaction[3]
# sum = 0
# if i == 1:
# d = [math.sqrt((uav2[0]-uav3[0])**2+(uav2[1]-uav3[1])**2+(uav2[2]-uav3[2])**2), math.sqrt((uav2[0]-uav4[0])**2+(uav2[1]-uav4[1])**2+(uav2[2]-uav4[2])**2)]
# for j in range(2):
# if d[j] < dmin:
# sum = sum +1
# if i == 2:
# d = [math.sqrt((uav3[0]-uav2[0])**2+(uav3[1]-uav2[1])**2+(uav3[2]-uav2[2])**2), math.sqrt((uav3[0]-uav4[0])**2+(uav3[1]-uav4[1])**2+(uav3[2]-uav4[2])**2)]
# for j in range(2):
# if d[j] < dmin:
# sum = sum +1
# if i == 3:
# d = [math.sqrt((uav4[0]-uav2[0])**2+(uav4[1]-uav4[1])**2+(uav4[2]-uav2[2])**2), math.sqrt((uav4[0]-uav3[0])**2+(uav4[1]-uav3[1])**2+(uav4[2]-uav3[2])**2)]
# for j in range(2):
# if d[j] < dmin:
# sum = sum +1
# return sum