class Satellite:
def __init__(self):
self.frequency = 0
self.posX = 0
self.posY = 0
self.posZ = 0
self.chooseEncryption = "Hamming"
self.receiver = Receiver()
self.noiseLevel = 0.05
def sendPositionHamming(self, array):
self.receiver.decodeHamming(self.Noise(array, self.noiseLevel))
def sendPositionBCH(self, array):
self.receiver.decodeBCH(self.Noise(array, self.noiseLevel))
def Noise(self, array, noise):
amountOfMistakes = len(array) * noise
amountOfMistakes = round(amountOfMistakes)
temp = []
y = 0
while y < amountOfMistakes:
help = False
r = random.randint(0, len(array) - 1)
for z in range(len(temp)):
if temp[z] is r:
help = True
break
if help is False:
temp.append(r)
y += 1
for l in temp:
q = random.randint(0, 1)
if q == 0:
if array[l] is 1:
array[l] = 0
else:
array[l] = 1
return array
def encryptHamming(self, list):
self.receiver.analysis.setOriginal(list)
czy_dopisac = 4 - ((len(list)) % 4)
if czy_dopisac < 4:
self.dopisz(czy_dopisac)
whole_msg = np.array([], dtype=int)
iterator = 0
while iterator < len(list):
msg = self.stworz_wiadomosc(iterator, list)
iterator += 4
kod = self.kod_hamming(msg)
whole_msg = np.append(whole_msg, kod)
print("Zakodowana wiadomość: ")
print(whole_msg)
return whole_msg
def encryptBCH(selfself, array):
polynomial = 8219
t = 2
bch = bchlib.BCH(polynomial, t)
data = bytearray(array)
code = bch.encode(data)
result = data + code
result = list(result)
return result
def generatePosition(self):
while True:
self.posX = random.uniform(-180.0, 180.0)
self.posY = random.uniform(-90.0, 90.0)
self.posZ = randint(10000, 11000)
self.posX = round(self.posX, 6)
self.posY = round(self.posY, 6)
print("Pozycja X: ")
print(self.posX)
print("Pozycja Y: ")
print(self.posY)
print("Wysokość: ")
print(self.posZ)
print()
self.posX = bitstring.BitArray(float=self.posX, length=64)
self.receiver.analysis.setOriginal(self.posX)
print("Pozycja X: ")
#print(self.posX.bin)
for x in self.posX.bin:
print(x, end=' ')
print('\n')
if self.chooseEncryption == "Hamming":
self.sendPositionHamming(self.encryptHamming(self.posX))
elif self.chooseEncryption == "BCH":
self.sendPositionBCH(self.encryptBCH(self.posX))
self.posY = bitstring.BitArray(float=self.posY, length=64)
self.receiver.analysis.setOriginal(self.posY)
print()
print("Pozycja Y: ")
print(self.posY.bin)
if self.chooseEncryption == "Hamming":
self.sendPositionHamming(self.encryptHamming(self.posY))
elif self.chooseEncryption == "BCH":
self.sendPositionBCH(self.encryptBCH(self.posY))
self.posZ = bitstring.BitArray(int=self.posZ, length=64)
self.receiver.analysis.setOriginal(self.posZ)
print()
print("Wysokość: ")
print(self.posZ.bin)
if self.chooseEncryption == "Hamming":
self.sendPositionHamming(self.encryptHamming(self.posZ))
elif self.chooseEncryption == "BCH":
self.sendPositionBCH(self.encryptBCH(self.posZ))
time.sleep(self.frequency)
def kod_hamming(self, msg=[]):
G = np.array([ # macierz generująca
[1, 1, 0, 1],
[1, 0, 1, 1],
[1, 0, 0, 0],
[0, 1, 1, 1],
[0, 1, 0, 0],
[0, 0, 1, 0],
[0, 0, 0, 1],
])
kod = (G @ msg) % 2
return kod
def dopisz(self, dopisanie):
for i in range(0, dopisanie, 1):
list.append(0)
def stworz_wiadomosc(self, i, list=[]):
tab = []
for x in range(i, i + 4, 1):
tab.append(list[x])
return tab
class WirelessSystem:
def __init__(self, numOfInputs):
self.transmitter = Transmitter()
self.receiver = Receiver()
self.wirelessChannel = WirelessChannel(0.1)
self.numOfInputs = numOfInputs
self.sigmaValues = [10, 1, 0.1]
self.reveivedPoints = []
self.colors = ['purple', 'yellow', 'orange']
self.hammingProbs = []
self.qpskProbs = []
def runForScatterPlot(self):
u = Utils()
probabilities = []
for i in range(len(self.sigmaValues)):
self.reveivedPoints = []
input = open("input.txt", "r")
numOfCorrectOutputs = 0
AWGNsigma = self.sigmaValues[i]
self.wirelessChannel.setSigma(1/AWGNsigma)
for line in input:
data = line.rstrip()
point = self.transmitter.modulate(data)
(hI, hQ) = self.wirelessChannel.applyChannelGain(point)
self.wirelessChannel.applyAWGN(point)
self.reveivedPoints.append(point)
u.showScatterPlot(self.reveivedPoints ,AWGNsigma, self.colors[i])
input.close()
def runForScatterPlot16(self):
u = Utils()
probabilities = []
for i in range(len(self.sigmaValues)):
self.reveivedPoints = []
input = open("input.txt", "r")
numOfCorrectOutputs = 0
AWGNsigma = self.sigmaValues[i]
self.wirelessChannel.setSigma(1/AWGNsigma)
cntr = 0
for line in input:
if(cntr == 0):
data = line.rstrip()
cntr += 1
continue
else:
data += line.rstrip()
cntr = 0
point = self.transmitter.modulate16QAM(data)
(hI, hQ) = self.wirelessChannel.applyChannelGain(point)
self.wirelessChannel.applyAWGN(point)
self.reveivedPoints.append(point)
u.showScatterPlotQAM(self.reveivedPoints ,AWGNsigma, self.colors[i])
input.close()
def runForLinePlot(self):
u = Utils()
probabilities = []
for i in range(1, 100, 1):
input = open("input.txt", "r")
numOfCorrectOutputs = 0
SNR = i / 10
print('i=', i, 'for AWGNSgima =', 1/SNR)
self.wirelessChannel.setSigma(1/SNR)
for line in input:
data = line.rstrip()
point = self.transmitter.modulate(data)
(hI, hQ) = self.wirelessChannel.applyChannelGain(point)
self.wirelessChannel.applyAWGN(point)
self.receiver.removeChannelImpact(point, hI, hQ)
receiverOut = self.receiver.demodulate2(point)
if(data == receiverOut):
numOfCorrectOutputs += 1
probabilities.append(1 - (numOfCorrectOutputs/self.numOfInputs))
input.close()
print(probabilities)
self.qpskProbs = probabilities
u.probVsSNR([(i/10.0) for i in range(1, 100, 1)], probabilities)
def runForLinePlot16(self):
u = Utils()
probabilities = []
for i in range(1, 100, 1):
input = open("input.txt", "r")
numOfCorrectOutputs = 0
SNR = i / 10
print('i=', i, 'for AWGNSgima =', 1/SNR)
self.wirelessChannel.setSigma(1/SNR)
cntr = 0
for line in input:
if(cntr == 0):
data = line.rstrip()
cntr += 1
continue
else :
cntr = 0
data += line.rstrip()
point = self.transmitter.modulate16QAM(data)
(hI, hQ) = self.wirelessChannel.applyChannelGain(point)
self.wirelessChannel.applyAWGN(point)
self.receiver.removeChannelImpact(point, hI, hQ)
receiverOut = self.receiver.demodulate16(point)
if(data == receiverOut):
numOfCorrectOutputs += 1
probabilities.append(1 - (numOfCorrectOutputs/(self.numOfInputs/2)))
input.close()
u.probVsSNR([i/10.0 for i in range(1, 100, 1)], probabilities)
def runWithHammingCode(self):
u = Utils()
probabilities = []
self.encodeAllWithHamming()
for i in range(1, 100, 1):
allDemodulated = open('demodulated.txt', 'w')
SNR = i / 10.0
print('for AWGNSgima =', 1/SNR)
self.wirelessChannel.setSigma(1/SNR)
content_file = open('encoded.txt', 'r')
content = content_file.read()
for data in [content[i:i+2] for i in range(0, len(content), 2)] :
point = self.transmitter.modulate(data)
(hI, hQ) = self.wirelessChannel.applyChannelGain(point)
self.wirelessChannel.applyAWGN(point)
self.receiver.removeChannelImpact(point, hI, hQ)
receiverOut = self.receiver.demodulate2(point)
allDemodulated.write(receiverOut)
allDemodulated.close()
self.decodeAll()
numOfCorrectOutputs = self.reconstructAndCalcCorrectOutputs()
probabilities.append(1 - (numOfCorrectOutputs/(self.numOfInputs)))
self.hammingProbs = probabilities
u.probVsSNR([i/10.0 for i in range(1, 100, 1)], probabilities)
#plt.plot([i/10.0 for i in range(1, 100, 1)], probabilities, color='green')
#plt.plot([i/10.0 for i in range(1, 100, 1)], self.qpskProbs)
#plt.show()
def runForScatterPlotHamming(self):
u = Utils()
probabilities = []
self.receivedPoints = []
for i in range(len(self.sigmaValues)):
AWGNsigma = self.sigmaValues[i]
self.wirelessChannel.setSigma(1/AWGNsigma)
content_file = open('encoded.txt', 'r')
content = content_file.read()
for data in [content[x:x+2] for x in range(0, len(content), 2)] :
point = self.transmitter.modulate(data)
(hI, hQ) = self.wirelessChannel.applyChannelGain(point)
self.wirelessChannel.applyAWGN(point)
self.reveivedPoints.append(point)
u.showScatterPlot(self.reveivedPoints , AWGNsigma, self.colors[i])
content_file.close()
def encodeAllWithHamming(self):
input = open("input.txt", "r")
output = open("encoded.txt", "w")
cntr = 0
for line in input:
if(cntr == 0):
data = line.rstrip()
cntr +=1
continue
else:
data += line.rstrip()
cntr = 0
encoded = self.transmitter.encodeHamming(map(int, data))
mystring = ""
for bit in encoded:
mystring += str(bit)
output.write(mystring)
input.close()
output.close()
def decodeAll(self):
demod = open('demodulated.txt', 'r')
decodedFile = open("decoded.txt", "w")
lines = demod.read()
for data in [lines[i:i+7] for i in range(0, len(lines), 7)] :
decoded = self.receiver.decodeHamming(map(int, data))
actualData = data[0:4]
mystring = ""
for bit in decoded:
mystring += str(bit)
decodedFile.write(actualData + mystring)
decodedFile.close()
demod.close()
def reconstructAndCalcCorrectOutputs(self):
numOfCorrects = 0
counter = 0
decodedFile = open('decoded.txt', 'r')
lines = tuple(open('input.txt', 'r'))
content = decodedFile.read()
for line in [content[i:i+7] for i in range(0, len(content), 7)] :
actualData = line[0 : 4]
syndromes = line[4:7]
inputLine1 = lines[counter].rstrip()
inputLine2 = lines[counter + 1].rstrip()
correctedOutput = self.receiver.findAndCorrectError(syndromes, actualData)
if(correctedOutput[0 : 2] == inputLine1):
numOfCorrects += 1
if(correctedOutput[2 : 4] == inputLine2):
numOfCorrects += 1
counter += 2
return numOfCorrects
