def __init__(self, playerObject, txNodeId, rxNodeId, coordinatorId, gameFreq, cost, gameType=3):
"""
Create a physical layer object and initialize internal parameters.
Keyword arguments:
coordinatorId -- Numerical cluster id.
cost -- Energy cost.
gateType -- Type of game played.
"""
self.playerObject = playerObject
self.coordinatorId = coordinatorId
self.gameFreq = gameFreq
self.cost = cost
self.gameType = gameType
# configure tx and rx nodes
self.txNode = GameNode(coordinatorId, txNodeId)
self.rxNode = GameNode(coordinatorId, rxNodeId)
# configure sense node. Just need to do this once.
self.rxNode.setSenseConfiguration(gameFreq, gameFreq, 400e3)
self.currentTxPower = random.choice(self.availableTxPowers)
self.previousTxPower = self.currentTxPower
self.bestResponseUntouched = self.currentTxPower
# initialize sense and transmit objects
self.transmitObject = PlayerTransmitLayer(self, self.gameFreq)
self.senseObject = PlayerSenseLayer(self, self.gameType)
class PlayerPhysicalLayer:
"""
Control transmission and spectrum sensing for a player.
"""
# VESNA power generating list. This must be sorted. Powers are in dBm
#minimum output power for cc2500 according to texas instruments in -30dBm
availableTxPowers = [0, -2, -4, -6, -8, -10, -12, -14, -16, -18, -20, -22, -24, -26, -28, -30]
# current transmitting power [dBm]
currentTxPower = random.choice(availableTxPowers)
# previous transmitted_power [dBm]
previousTxPower = currentTxPower
bestResponseUntouched = 0
# direct and cross gains
directGain = 0
crossGain = 0
# used for sending data
transmitObject = None
# used for sensing the spectrum
senseObject = None
# game type - can be: 1, 2, 3 . Depends on the implementation you want to use
gameType = 3
# neighborPowerEvent. When this is True, It means that neighbor player changed its power
neighborPowerEvent = False
# When this is triggered (=True) then it means that equilibrium has been reached and the threads stops here.
equilibriumDetected = False
def __init__(self, playerObject, txNodeId, rxNodeId, coordinatorId, gameFreq, cost, gameType=3):
"""
Create a physical layer object and initialize internal parameters.
Keyword arguments:
coordinatorId -- Numerical cluster id.
cost -- Energy cost.
gateType -- Type of game played.
"""
self.playerObject = playerObject
self.coordinatorId = coordinatorId
self.gameFreq = gameFreq
self.cost = cost
self.gameType = gameType
# configure tx and rx nodes
self.txNode = GameNode(coordinatorId, txNodeId)
self.rxNode = GameNode(coordinatorId, rxNodeId)
# configure sense node. Just need to do this once.
self.rxNode.setSenseConfiguration(gameFreq, gameFreq, 400e3)
self.currentTxPower = random.choice(self.availableTxPowers)
self.previousTxPower = self.currentTxPower
self.bestResponseUntouched = self.currentTxPower
# initialize sense and transmit objects
self.transmitObject = PlayerTransmitLayer(self, self.gameFreq)
self.senseObject = PlayerSenseLayer(self, self.gameType)
def isPrevTxDone(self):
"""Check if previous transmission has finished"""
if self.transmitObject.isSendingData():
self.transmitObject.sleepUntilSignalGenerationStops()
return
def setCost(self,newCost):
self.cost=newCost
def setInitialBestResponseUntouched(self):
"""Set best response as current tx power, best response untouched in [W]."""
self.bestResponseUntouched = self.currentTxPower
def setDirectGain(self, hii):
"""Set player direct gain"""
self.directGain = hii
def getPracticalBestResponseForm1(self, txPowerDBm, rxPowerDBm):
"""
Compute best response strategy based current game state.
Return best response power in dBm. Best response = 1/c_i + (I + n_0) / h_ii.
I + n_0 = receivedPower - usefulReceivedPower
Keyword arguments:
txPowerDBm -- players' transmitting power.
rxPowerDBm -- player received power.
"""
# convert powers in W
txPowerWatts = 1e-3 * math.pow(10.00, float(txPowerDBm) / 10.00)
rxPowerWatts = 1e-3 * math.pow(10.00, float(rxPowerDBm) / 10.00)
usefulReceivedPowerWatts = txPowerWatts * self.directGain
if txPowerDBm < -1000:
# Player does not transmit useful data, consider only noise and interference
bestResponse = (1.00 / float(self.cost)) - rxPowerWatts / float(self.directGain)
else:
bestResponse = (1.00 / float(self.cost)) - (rxPowerWatts - usefulReceivedPowerWatts) / float(self.directGain)
# Transform in dBm
try:
return 10.00 * math.log10(bestResponse / 1e-3)
except:
print "Player %d: negative best response" % (self.playerObject.playerNumber)
return None
def getPracticalBestResponseForm2(self, rxPowerDBm):
"""
Compute best response strategy based current game state.
Return best response power in dBm. This power is the best power in interference condition.
This method use the practically formula which will be used in empirical games
This formula is based on the received power dBm, which must be only noise and interference
"""
# convert received power in W
rxPowerWatts = 1e-3 * math.pow(10.00, float(rxPowerDBm) / 10.00)
bestResponse = (1.00 / float(self.cost)) - rxPowerWatts / float(self.directGain)
# return in dBm
try:
return 10.00 * math.log10(bestResponse / 1e-3)
except:
print "Player %d: negative best response" % (self.playerObject.playerNumber)
return None
def computeBestResponseForm1(self, pj, hjiList):
"""
Compute practical best response based on current tx power a list containing opponents tx
powers and a list containing cross gains h_ji for player i.
Assume hjiList contains gains in [W].
Do not consider noise!!!
Return best response in [W]
Keyword arguments:
pj -- list with player j tx power, in bBm
hjiList -- list with cross gains in [W] for player i.
"""
# compute sum(h_ji*pJ)
crossGainSum = 0
# must transform each elem of pj in [W]
temp = [math.pow(10.00, float(x) / 10.00) * 1e-3 for x in pj]
for index, elem in enumerate(temp):
crossGainSum += elem * hjiList[index]
bestResp = (1.00 / float(self.cost) - crossGainSum / float(self.directGain))
# return power in dBm
try:
# sometimes the difference is negative, in that case return none
return 10.00 * math.log10(bestResp / 1.e-3)
except:
print "Player %d: negative best response" % (self.playerObject.playerNumber)
return None
def computeBestResponseForm2(self, receivedPower):
"""
Compute practical best response based on received power and direct gain.
Return best response in [W]
Keyword arguments:
receivedPower -- Measured receiving power, i.e. sum(h_ji * p_j) + n_0
"""
powerInW = math.pow(10.00, float(receivedPower)/10.00) * 1e-3
bestResp = (1.00 / float(self.cost) - powerInW/float(self.directGain))
# return power in dBm
try:
# sometimes the difference is negative, in that case return none
return 10.00 * math.log10(bestResp / 1.e-3)
except:
print "Player %d: negative best response" % (self.playerObject.playerNumber)
return None
def computeBestResponseForm3(self, recP):
"""
Compute practical best response based on received power and direct gain.
Return best response in [dBm]
Keyword arguments:
receivedPower -- Measured receiving power, i.e. sum(h_ji * p_j) + n_0
"""
bestResp = (1.00 / float(self.cost) - recP/float(self.directGain))
# return power in dBm
try:
# sometimes the difference is negative, in that case return none
return 10.00 * math.log10(bestResp / 1.e-3)
except:
print "Player %d: negative best response" % (self.playerObject.playerNumber)
return None
def getAvailTxPower(self, desiredPower):
"""From the available power list get a transmission power.
Method will return the closest power from the available ones to the desired power.
Keywords arguments:
desiredPower -- Desired transmitting power.
"""
minDist = float("inf")
rez = None
for i in range(0, len(self.availableTxPowers)):
if math.fabs(desiredPower - self.availableTxPowers[i]) < minDist:
minDist = math.fabs(desiredPower - self.availableTxPowers[i])
rez = self.availableTxPowers[i]
return rez
def getCrtTxPower(self):
"""Get current transmission power"""
return self.currentTxPower
def getBestRespUntouched(self):
"""Return best response as real value, not discrete one"""
return self.bestResponseUntouched
def changeTxPowerRandomly(self):
"""Change current tx power randomly"""
self.currentTxPower = random.choice(self.availableTxPowers)
self.previousTxPower = self.currentTxPower
self.bestResponseUntouched = self.currentTxPower
def changeTxPower(self, newBestResponse):
"""
Change current tx power, save previous tx power
Keyword arguments:
newTxPower -- new transmitting power
"""
self.previousTxPower = self.currentTxPower
self.bestResponseUntouched = newBestResponse
self.currentTxPower = self.getAvailTxPower(newBestResponse)
