def waterfall_next(self, waterfall_last, action):
waterfall_n = waterfall_last.copy()
sub_pow_ls = []
jamm_ls = copy.copy(self.jamm_pos)
self.set_user_freq(action)
w_f = usrp_spetrum_sense.main(self.tb, 1)
#waterfall_lib_mean = np.mean(self.waterfall_lib[action], 0).reshape(1, 1, 1601, 1)
#sub_waterfall = w_f - waterfall_lib_mean
jamm_ls.append(
int(self.jammer_obj.get_center_freq() - 100500000) / 500000)
"""
for i in range(self.n_actions):
pow_ = np.sum(sub_waterfall[0,0,(i + 1) * 80 - 2:(i + 1) * 80 + 3, 0])
sub_pow_ls.append(pow_)
if pow_ > 40:
jamm_ls.append(i)
"""
for i in range(self.line_num):
if i < self.line_num - 1:
waterfall_n[0, i] = waterfall_n[0, i + 1]
else:
waterfall_n[0, i] = w_f
#print(sub_pow_ls)
return waterfall_n, jamm_ls
def waterfall_lib(self):
self.main_thread()
waterfall_lib = np.zeros(shape=(self.n_actions, 50, 1601, 1),
dtype=float)
for i in range(self.n_actions):
self.set_user_freq(self.action_space[i])
waterfall = usrp_spetrum_sense.main(self.tb)
waterfall_lib[i] = waterfall
self.user_obj.stop()
return waterfall_lib
def waterfall_lib(self):
waterfall_lib = np.zeros(shape=(self.n_actions, 50, 1601, 1),
dtype=float)
for i in range(self.n_actions):
self.set_user_freq(self.action_space[i])
waterfall = usrp_spetrum_sense.main(self.tb, 50)
waterfall_lib[i] = waterfall
t = threading.Thread(target=self.main_jammer_tx)
t.start()
return waterfall_lib
def waterfall_next(self, waterfall_last, action):
waterfall_n = waterfall_last.copy()
self.set_user_freq(self.action_space[action])
w_f = usrp_spetrum_sense.main(self.tb)
for i in range(self.line_num):
if i < self.line_num - 1:
waterfall_n[0, i, :, 0] = waterfall_n[0, i + 1, :, 0]
else:
waterfall_n[0, i, :, 0] = w_f[0, 0, :, 0]
return waterfall_n
def spect_sense(self):
root = tk.Tk()
root.title("matplotlib in TK")
f = Figure(figsize=(7, 7), dpi=200)
canvas = FigureCanvasTkAgg(f, master=root)
canvas.get_tk_widget().pack(side=tk.TOP, fill=tk.BOTH, expand=1)
x = 0
while True:
x = x + 1 if x < 18 else 0
self.set_user_freq(self.action_space[x])
w_f = usrp_spetrum_sense.main(self.tb)
f.clf()
waterfall_figure = f.add_subplot(111)
waterfall_figure.plot(w_f[0, -1])
canvas.draw()
def __init__(self):
super(freq_env, self).__init__()
self.action_space = [
i for i in np.arange(100000000.0, 110000001.0, 1000000)
]
self.n_actions = len(self.action_space)
self.n_features = 1601
self.jammer_obj = jammer()
self.user_obj = user()
self.action_ls = [100000000.0]
self.start_freq = 129000000.0
self.end_freq = 130000000.0
self.tb = usrp_spetrum_sense.my_top_block()
self.tb.start()
self.wf, self.min_index, self.user_f, self.sum_ls = usrp_spetrum_sense.main(
self.tb)
def spect_sense(self):
while True:
self.set_user_freq(self.user_f)
w_f, min_i, userfreq, sumls = usrp_spetrum_sense.main(self.tb)
x = 3
if self.min_index == 0 or self.min_index == 1 or self.min_index == 2 or self.min_index == 3 or self.min_index == 4:
if sumls[self.
min_index] > x * self.sum_ls[self.min_index] or sumls[
self.min_index +
2] > x * self.sum_ls[self.min_index + 2] or sumls[
self.min_index +
4] > x * self.sum_ls[self.min_index + 4]:
self.user_f = userfreq
self.wf = w_f
self.min_index = min_i
self.sum_ls = sumls
self.set_user_freq(self.user_f)
elif self.min_index == 39 or self.min_index == 38 or self.min_index == 37 or self.min_index == 36 or self.min_index == 35:
if sumls[self.
min_index] > x * self.sum_ls[self.min_index] or sumls[
self.min_index -
2] > x * self.sum_ls[self.min_index - 2] or sumls[
self.min_index -
4] > x * self.sum_ls[self.min_index - 4]:
self.user_f = userfreq
self.wf = w_f
self.min_index = min_i
self.sum_ls = sumls
self.set_user_freq(self.user_f)
else:
if sumls[self.
min_index] > x * self.sum_ls[self.min_index] or sumls[
self.min_index -
2] > x * self.sum_ls[self.min_index - 2] or sumls[
self.min_index - 4] > x * self.sum_ls[
self.min_index - 4] or sumls[
self.min_index + 2] > x * self.sum_ls[
self.min_index + 2] or sumls[
self.min_index +
4] > x * self.sum_ls[
self.min_index + 4]:
self.user_f = userfreq
self.wf = w_f
self.min_index = min_i
self.sum_ls = sumls
self.set_user_freq(self.user_f)
time.sleep(2)
def waterfall_background(self):
self.jamm_pos = []
self.freq_pow = []
waterfall_bg = usrp_spetrum_sense.main(self.tb)
for i in range(self.n_actions):
sum_freq_1 = np.sum(waterfall_bg[0, -1,
(2 * i + 1) * 40:(2 * i + 3) * 40,
0])
self.freq_pow.append(sum_freq_1)
#sum_freq_2 = np.sum(waterfall_bg[0, 0, (2 * i + 1) * 40:(2 * i + 3) * 40, 0])
#sum_freq_3 = np.sum(waterfall_bg[0, 24, (2 * i + 1) * 40:(2 * i + 3) * 40, 0])
if sum_freq_1 > 450:
self.jamm_pos.append(i)
print(self.freq_pow)
print(self.jamm_pos)
return waterfall_bg
def step(self, action):
# ---------------------------------define reward------------------------------
jammer_freq = self.get_jammer_freq()
print("jammer_freq---------------------", jammer_freq)
if self.action_space[action] - jammer_freq > 100000.0:
if self.action_ls[-1] == self.action_space[action]:
reward = 1
done = True
else:
reward = 0.8
done = True
else:
reward = -1
done = False
self.action_ls.append(self.action_space[action])
#---------------------------------define s_ ----------------------------------
self.set_user_freq(self.action_space[action])
s_ = usrp_spetrum_sense.main()
return s_, reward, done
def waterfall_background(self):
self.jamm_pos = []
self.freq_pow = []
waterfall_bg = usrp_spetrum_sense.main(self.tb, 100)
self.waterfall_bg_mean = np.mean(waterfall_bg[0],
0).reshape(1, 1, 1601, 1)
for i in range(self.n_actions):
sum_freq_1 = np.sum(
self.waterfall_bg_mean[0, 0,
(i + 1) * 80 - 40:(i + 1) * 80 + 41, 0])
self.freq_pow.append(sum_freq_1)
# sum_freq_2 = np.sum(waterfall_bg[0, 0, (2 * i + 1) * 40:(2 * i + 3) * 40, 0])
# sum_freq_3 = np.sum(waterfall_bg[0, 24, (2 * i + 1) * 40:(2 * i + 3) * 40, 0])
if sum_freq_1 > 280:
self.jamm_pos.append(i)
#print(self.freq_pow)
#print(self.jamm_pos)
return waterfall_bg
def waterfall_reset(self):
self.current_line = -50
self.jamm_pos = []
self.freq_pow = []
rand_int = random.randint(0, self.n_actions - 1)
self.action_last = rand_int
waterfall_reset = np.zeros(shape=(1, 50, 1601, 1), dtype=float)
self.line_num = list(waterfall_reset.shape)[1]
self.set_user_freq(self.action_space[rand_int])
w_f_reset = usrp_spetrum_sense.main(self.tb)
for i in range(self.line_num):
self.current_line += 1
waterfall_reset[0, i, :,
0] = self.power_ls[(self.index_end[0] + 1) *
i:(self.index_end[0] + 1) * i +
self.index_end[0] + 1]
for i in range(self.n_actions):
sum_freq = np.sum(waterfall_reset[0, -1, (2 * i + 1) *
40:(2 * i + 3) * 40, 0])
self.freq_pow.append(sum_freq)
if sum_freq > 400:
self.jamm_pos.append(i)
#print(self.freq_pow)
#print(self.jamm_pos)
#plt.subplot(211)
#for i in range(19):
#plt.axvline((i+1)*80,color='red')
#plt.plot(waterfall_reset[0,-1])
waterfall_reset[0, -1, :, 0] = w_f_reset[0, 0, :, 0]
#plt.subplot(212)
#plt.plot(w_f[0, -1])
#plt.show()
return waterfall_reset
pass
def reset(self):
self.action_ls = [100000000.0]
self.set_user_freq(100000000.0)
self.s, self.userfreq = usrp_spetrum_sense.main()
return self.s
