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channel.py
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import numpy as np
import math
import cmath
from math_tool import *
class mmWave_channel(object):
"""
generate MmWave under UMi open
input: distance, angle, pair entity object
output: Instantaneous CSI
"""
def __init__(self, transmitter, receiver, frequncy):
"""
transmitter: object in entity.py
receiver: object in entity.py
"""
self.channel_name = ''
self.n = 0
self.sigma = 0
self.transmitter = transmitter
self.receiver = receiver
self.channel_type = self.init_type() # 'UAV_RIS', 'UAV_user', 'UAV_attacker', 'RIS_user', 'RIS_attacker'
# self.distance = np.linalg.norm(transmitter.coordinate - receiver.coordinate)
self.frequncy = frequncy
# init & updata path loss
self.path_loss_normal = self.get_channel_path_loss()
self.path_loss_dB = normal_to_dB(self.path_loss_normal)
# init & update channel CSI matrix
self.channel_matrix = self.get_estimated_channel_matrix()
def init_type(self):
channel_type = self.transmitter.type+'_'+self.receiver.type
if channel_type == 'UAV_RIS' or channel_type == 'RIS_UAV':
self.n = 2.2
self.sigma = 3
self.channel_name = 'H_UR'
elif channel_type == 'UAV_user' or channel_type == 'UAV_attacker':
self.n = 3.5
self.sigma = 3
if channel_type =='UAV_user':
self.channel_name = 'h_U_k,' + str(self.transmitter.index)
elif channel_type == 'UAV_attacker':
self.channel_name = 'h_U_p,' + str(self.transmitter.index)
elif channel_type == 'user_UAV' or channel_type == 'attacker_UAV':
self.n = 3.5
self.sigma = 3
if channel_type =='user_UAV':
self.channel_name = 'h_U_k,' + str(self.transmitter.index)
elif channel_type == 'attacker_UAV':
self.channel_name = 'h_U_p,' + str(self.transmitter.index)
elif channel_type == 'RIS_user' or channel_type == 'RIS_attacker':
self.n = 2.8
self.sigma = 3
if channel_type =='RIS_user':
self.channel_name = 'h_R_k,' + str(self.transmitter.index)
elif channel_type == 'RIS_attacker':
self.channel_name = 'h_R_p,' + str(self.transmitter.index)
elif channel_type == 'user_RIS' or channel_type == 'attacker_RIS':
self.n = 2.8
self.sigma = 3
if channel_type =='user_RIS':
self.channel_name = 'h_R_k,' + str(self.transmitter.index)
elif channel_type == 'attacker_RIS':
self.channel_name = 'h_R_p,' + str(self.transmitter.index)
return channel_type
def get_channel_path_loss(self):
"""
calculate the path loss including shadow fading
(in normal form)
"""
distance = np.linalg.norm(self.transmitter.coordinate - self.receiver.coordinate)
PL = -20 * math.log10(4*math.pi/(3e8/self.frequncy)) - 10*self.n*math.log10(distance)
shadow_loss = np.random.normal() * self.sigma
# return dB_to_normal(PL - shadow_loss)
return dB_to_normal(PL)
def get_estimated_channel_matrix(self):
"""
init & update channel matrix
"""
# init matrix
N_t = self.transmitter.ant_num
N_r = self.receiver.ant_num
channel_matrix = np.mat(np.ones(shape=(N_r,N_t),dtype=complex), dtype=complex)
# get relevant coordinate receiver under transmitter system
r_under_t_car_coor = get_coor_ref(\
self.transmitter.coor_sys, \
self.receiver.coordinate - self.transmitter.coordinate)
# get relevant spherical_coordinate
r_t_r, r_t_theta, r_t_fai = cartesian_coordinate_to_spherical_coordinate(\
cartesian_coordinate=r_under_t_car_coor\
)
# get relevant coordinate transmitter under receiver system
t_under_r_car_coor = get_coor_ref(\
# remmber to Meet channel direction restrictions
[-self.receiver.coor_sys[0], self.receiver.coor_sys[1], -self.receiver.coor_sys[2]],\
self.transmitter.coordinate - self.receiver.coordinate)
# get relevant spherical_coordinate
t_r_r, t_r_theta, t_r_fai = cartesian_coordinate_to_spherical_coordinate(\
cartesian_coordinate=t_under_r_car_coor\
)
# calculate array response
t_array_response = self.generate_array_response(self.transmitter, r_t_theta, r_t_fai)
r_array_response = self.generate_array_response(self.receiver, t_r_theta, t_r_fai)
array_response_product = r_array_response * t_array_response.H
# get H_LOS
# get LOS path loss
PL = self.path_loss_normal
# get LOS phase shift
LOS_fai = 2 * math.pi * self.frequncy * np.linalg.norm(self.transmitter.coordinate - self.receiver.coordinate) / 3e8
channel_matrix = cmath.exp(1j*LOS_fai)* math.pow(PL, 0.5) * array_response_product
return channel_matrix
def generate_array_response(self, transceiver, theta, fai):
"""
if the ant_type is 'UPA'
generate_UPA_response
if the ant_type is 'ULA'
generate_ULA_response
if the ant_type is 'single'
generate_singleant_response
"""
ant_type = transceiver.ant_type
ant_num = transceiver.ant_num
if ant_type == 'UPA':
row_num = int(math.sqrt(ant_num))
Planar_response = np.mat(np.ones(shape=(ant_num, 1)), dtype=complex)
for i in range(row_num):
for j in range(row_num):
Planar_response[j+i*row_num,0] = cmath.exp(1j *\
(math.sin(theta) * math.cos(fai)*i*math.pi + math.sin(theta)*math.sin(fai))\
)
return Planar_response
elif ant_type == 'ULA':
Linear_response = np.mat(np.ones(shape=(ant_num,1)), dtype=complex)
for i in range(ant_num):
Linear_response[i, 0] = cmath.exp(1j * math.sin(theta) * math.cos(fai)*i*math.pi)
return Linear_response
elif ant_type == 'single':
return np.mat(np.array([1]))
else:
return False
def update_CSI(self):
"""
update pathloss and channel matrix
"""
# init & updata path loss
self.path_loss_normal = self.get_channel_path_loss()
self.path_loss_dB = normal_to_dB(self.path_loss_normal)
# init & update channel CSI matrix
self.channel_matrix = self.get_estimated_channel_matrix()