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Bfee.py
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import numpy as np
import sys
import matplotlib as plt
import numpy as np
class Bfee:
def __init__(self):
pass
@staticmethod
def from_file_intel(filename, model_name_encode="shift-JIS"):
with open(filename, "rb") as f:
from functools import reduce
array = bytes(reduce(lambda x, y: x + y, list(f))) # reduce(函数，list)，将list中元素依次累加
bfee = Bfee()
# vmd.current_index = 0
bfee.file_len = len(array)
bfee.dicts = []
bfee.all_csi = []
csi_real = np.zeros((30, 100))
csi_image = np.zeros((30, 100))
# vmd.timestamp_low0 = int.from_bytes(array[3:7], byteorder='little', signed=False)
# array = array[3:]
# %% Initialize variables
# ret = cell(ceil(len/95),1); # % Holds the return values - 1x1 CSI is 95 bytes big, so this should be upper bound
cur = 0 # % Current offset into file
count = 0 # % Number of records output
broken_perm = 0 # % Flag marking whether we've encountered a broken CSI yet
triangle = [0, 1, 3] # % What perm should sum to for 1,2,3 antennas
while cur < (bfee.file_len - 3):
# % Read size and code
# % 将文件数据读取到维度为 sizeA 的数组 A 中，并将文件指针定位到最后读取的值之后。fread 按列顺序填充 A。
bfee.field_len = int.from_bytes(array[cur:cur + 2], byteorder='big', signed=False)
bfee.code = array[cur + 2]
cur = cur + 3
# there is CSI in field if code == 187，If unhandled code skip (seek over) the record and continue
if bfee.code == 187:
pass
else:
# % skip all other info
cur = cur + bfee.field_len - 1
continue
# get beamforming or phy data
if bfee.code == 187:
count = count + 1
bfee.timestamp_low = int.from_bytes(array[cur:cur + 4], byteorder='little', signed=False)
bfee.bfee_count = int.from_bytes(array[cur + 4:cur + 6], byteorder='little', signed=False)
bfee.Nrx = array[cur + 8]
bfee.Ntx = array[cur + 9]
bfee.rssi_a = array[cur + 10]
bfee.rssi_b = array[cur + 11]
bfee.rssi_c = array[cur + 12]
bfee.noise = array[cur + 13] - 256
bfee.agc = array[cur + 14]
bfee.antenna_sel = array[cur + 15]
bfee.len = int.from_bytes(array[cur + 16:cur + 18], byteorder='little', signed=False)
bfee.fake_rate_n_flags = int.from_bytes(array[cur + 18:cur + 20], byteorder='little', signed=False)
bfee.calc_len = (30 * (bfee.Nrx * bfee.Ntx * 8 * 2 + 3) + 6) / 8
bfee.csi = np.zeros(shape=(30, bfee.Nrx, bfee.Ntx), dtype=np.dtype(np.complex)) # csi初始化
bfee.perm = [1, 2, 3]
bfee.perm[0] = ((bfee.antenna_sel) & 0x3)
bfee.perm[1] = ((bfee.antenna_sel >> 2) & 0x3)
bfee.perm[2] = ((bfee.antenna_sel >> 4) & 0x3)
cur = cur + 20
# get payload
payload = array[cur:cur + bfee.len]
cur = cur + bfee.len
index = 0
# Check that length matches what it should
if (bfee.len != bfee.calc_len):
print("MIMOToolbox:read_bfee_new:size", "Wrong beamforming matrix size.")
# Compute CSI from all this crap :
# import struct
for i in range(30):
index += 3
remainder = index % 8
for j in range(bfee.Nrx):
for k in range(bfee.Ntx):
real_bin = bytes([(payload[int(index / 8)] >> remainder) | (
payload[int(index / 8 + 1)] << (8 - remainder)) & 0b11111111])
real = int.from_bytes(real_bin, byteorder='little', signed=True)
imag_bin = bytes([(payload[int(index / 8 + 1)] >> remainder) | (
payload[int(index / 8 + 2)] << (8 - remainder)) & 0b11111111])
imag = int.from_bytes(imag_bin, byteorder='little', signed=True)
tmp = np.complex(float(real), float(imag))
# print(tmp)
bfee.csi[i, j, k] = tmp
index += 16
# % matrix does not contain default values
if sum(bfee.perm) != triangle[bfee.Nrx - 1]:
q = 1
# print('WARN ONCE: Found CSI (',filename,') with Nrx=', bfee.Nrx,' and invalid perm=[',bfee.perm,']\n' )
else:
temp_csi = np.zeros(bfee.csi.shape, dtype=np.dtype(np.complex))
# bfee.csi[:,bfee.perm[0:bfee.Nrx],:] = bfee.csi[:,0:bfee.Nrx,:]
for r in range(bfee.Nrx):
temp_csi[:, bfee.perm[r], :] = bfee.csi[:, r, :]
bfee.csi = temp_csi
# print phy data
# print(vmd.file_len,
# vmd.field_len,
# vmd.code,
# vmd.timestamp_low,
# vmd.bfee_count,
# vmd.Nrx,
# vmd.Ntx,
# vmd.rssi_a,
# vmd.rssi_b,
# vmd.rssi_c,
# vmd.noise,
# vmd.agc,
# vmd.antenna_sel,
# vmd.len,
# vmd.fake_rate_n_flags,
# vmd.calc_len,
# vmd.perm,
# vmd.csi.shape
# )
# 将类属性导出为dict，并返回
bfee_dict = {}
bfee_dict['timestamp_low'] = bfee.timestamp_low
bfee_dict['bfee_count'] = bfee.bfee_count
bfee_dict['Nrx'] = bfee.Nrx
bfee_dict['Ntx'] = bfee.Ntx
bfee_dict['rssi_a'] = bfee.rssi_a
bfee_dict['rssi_b'] = bfee.rssi_b
bfee_dict['rssi_c'] = bfee.rssi_c
bfee_dict['noise'] = bfee.noise
bfee_dict['agc'] = bfee.agc
bfee_dict['antenna_sel'] = bfee.antenna_sel
bfee_dict['perm'] = bfee.perm
bfee_dict['len'] = bfee.len
bfee_dict['fake_rate_n_flags'] = bfee.fake_rate_n_flags
bfee_dict['calc_len'] = bfee.calc_len
bfee_dict['csi'] = bfee.csi
bfee.dicts.append(bfee_dict)
bfee.all_csi.append(bfee.csi)
csi_complex = bfee.csi
# print(csi_complex.real)
# print(csi_complex.imag)
# print("#")
return bfee
@staticmethod
def bit_convert(data, maxbit):
if data & (1 << (maxbit - 1)):
data = data - (1 << maxbit)
return data
@staticmethod
def fill_csi_matrix(array, cur, Nrx, Ntx, num_tones):
csi = np.zeros(shape=(num_tones, Nrx, Ntx), dtype=np.dtype(np.complex)) # csi初始化 ~~
# we process 16 bits at a time
bits_left = 16
bitmask = (1 << 10) - 1
idx = 0
h_data = array[idx] + (array[idx + 1] << 8)
idx = idx + 2
current_data = h_data & ((1 << 16) - 1)
for k in range(num_tones):
for nc_idx in range(Ntx):
for nr_idx in range(Nrx):
if bits_left - 10 < 10:
h_data = array[cur + idx] + (array[cur + idx + 1] << 8)
idx = idx + 2
current_data = current_data + (h_data << bits_left)
bits_left = bits_left + 16
imag = current_data & bitmask
imag = Bfee.bit_convert(imag, 10)
bits_left = bits_left - 10
current_data = current_data >> 10
if bits_left - 10 < 0:
h_data = array[cur + idx] + (array[cur + idx + 1] << 8)
idx = idx + 2
current_data = current_data + (h_data << bits_left)
bits_left = bits_left + 16
real = current_data & bitmask
real = Bfee.bit_convert(real, 10)
bits_left = bits_left - 10
current_data = current_data >> 10
csi[k, nr_idx, nc_idx] = np.complex(float(real), float(imag))
# print("(", real, " ", imag, ")", end=', ')
# print("\n")
return csi
@staticmethod
def from_file_atheros(filename, model_name_encode="shift-JIS"):
with open(filename, "rb") as f:
from functools import reduce
array = bytes(reduce(lambda x, y: x + y, list(f))) # reduce(函数，list)，将list中元素依次累加
bfee = Bfee()
bfee.file_len = len(array)
bfee.dicts = []
bfee.all_csi = []
bfee.all_rssi = []
bfee.all_timestamp = []
csi_st_len = 23
# %% Initialize variables
cur = 0 # % Current offset into file
file_pointer = 0
while file_pointer < bfee.file_len - 3:
cur = file_pointer
bfee.field_len = int.from_bytes(array[cur:cur + 2], byteorder='big', signed=False)
bfee.cnt = int.from_bytes(array[cur + 2: cur + 4], byteorder='big', signed=False)
cur = cur + 2
if bfee.field_len != 50600 or bfee.cnt != 504:
file_pointer = file_pointer + bfee.field_len + 2
continue
try:
for ii in range(int(bfee.field_len / bfee.cnt)):
# % Read size and code
# % 将文件数据读取到维度为 sizeA 的数组 A 中，并将文件指针定位到最后读取的值之后。fread 按列顺序填充 A。
# bfee.cnt = int.from_bytes(array[cur: cur + 2], byteorder='big', signed=False)
cur_init = cur
cur = cur + 2
# get beamforming or phy data
bfee.timestamp_low = int.from_bytes(array[cur: cur + 8], byteorder='little', signed=False) # timestamp
bfee.csi_len = int.from_bytes(array[cur + 8: cur + 10], byteorder='little', signed=False)
bfee.agc = array[cur + 14] # ??????
bfee.Nrx = array[cur + 17] # nr ~~
bfee.Ntx = array[cur + 18] # tx ~~
bfee.rssi_a = array[cur + 20]
bfee.rssi_b = array[cur + 21]
bfee.rssi_c = array[cur + 22]
bfee.num_tones = array[cur + 16]
bfee.noise = array[cur + 13] - 256 # noise ~~
bfee.buf_len = int.from_bytes(array[cur + 8: cur + 10], byteorder='little', signed=False)
bfee.len = int.from_bytes(array[cur + csi_st_len: cur + csi_st_len + 2], byteorder='little',
signed=False) # payload_len ~~
# bfee.csi = np.zeros(shape=(bfee.num_tones, bfee.Nrx, bfee.Ntx), dtype=np.dtype(np.complex)) # csi初始化 ~~
# get payload
# payload = array[cur + csi_st_len + bfee.csi_len + 2: cur + csi_st_len + bfee.csi_len + 2 + bfee.len] # ~~
# extract the CSI and fill the complex matrix
# we have 10 bit resolution for each real and image value
cur = cur + csi_st_len + 2
try:
bfee.csi = Bfee.fill_csi_matrix(array, cur, bfee.Nrx, bfee.Ntx, bfee.num_tones)
except Exception as e:
foo = 1
# print(e)
cur = cur_init + bfee.cnt + 2
# 将类属性导出为dict，并返回
bfee_dict = {}
bfee_dict['timestamp_low'] = bfee.timestamp_low
bfee_dict['Nrx'] = bfee.Nrx
bfee_dict['Ntx'] = bfee.Ntx
bfee_dict['rssi_a'] = bfee.rssi_a
bfee_dict['rssi_b'] = bfee.rssi_b
bfee_dict['rssi_c'] = bfee.rssi_c
bfee_dict['noise'] = bfee.noise
bfee_dict['len'] = bfee.len
bfee_dict['csi'] = bfee.csi
bfee_dict['agc'] = bfee.agc
bfee.dicts.append(bfee_dict)
bfee.all_csi.append(bfee.csi)
bfee.all_rssi.append([bfee.rssi_a, bfee.rssi_b, bfee.rssi_c])
bfee.all_timestamp.append(bfee.timestamp_low)
# bfee.all_timestamp.append(bfee.timestamp_low)
file_pointer = file_pointer + bfee.field_len + 2
except:
file_pointer = file_pointer + bfee.field_len + 2
return bfee
@staticmethod
def from_stream_atheros(data_byte, data_len):
array = data_byte # reduce(函数，list)，将list中元素依次累加
bfee = Bfee()
bfee.file_len = len(array)
bfee.dicts = []
bfee.all_csi = []
bfee.all_aver_rssi = []
bfee.all_timestamp = []
csi_st_len = 23
# %% Initialize variables
cur = 0 # % Current offset into file
count = 0 # % Number of records output
while cur < (data_len - 3):
# % Read size and code
# % 将文件数据读取到维度为 sizeA 的数组 A 中，并将文件指针定位到最后读取的值之后。fread 按列顺序填充 A。
# bfee.field_len = int.from_bytes(array[cur:cur + 2], byteorder='big', signed=False)
bfee.cnt = int.from_bytes(array[cur: cur + 2], byteorder='big', signed=False)
cur_init = cur
cur = cur + 2
# get beamforming or phy data
bfee.timestamp_low = int.from_bytes(array[cur: cur + 8], byteorder='little', signed=False) # timestamp
bfee.csi_len = int.from_bytes(array[cur + 8: cur + 10], byteorder='little', signed=False)
bfee.agc = array[cur + 14] # ??????
bfee.Nrx = array[cur + 17] # nr ~~
bfee.Ntx = array[cur + 18] # tx ~~
bfee.rssi_a = array[cur + 20]
bfee.rssi_b = array[cur + 21]
bfee.rssi_c = array[cur + 22]
bfee.num_tones = array[cur + 16]
bfee.noise = array[cur + 13] - 256 # noise ~~
bfee.buf_len = int.from_bytes(array[cur + 8: cur + 10], byteorder='little', signed=False)
bfee.len = int.from_bytes(array[cur + csi_st_len: cur + csi_st_len + 2], byteorder='little',
signed=False) # payload_len ~~
# bfee.csi = np.zeros(shape=(bfee.num_tones, bfee.Nrx, bfee.Ntx), dtype=np.dtype(np.complex)) # csi初始化 ~~
# get payload
# payload = array[cur + csi_st_len + bfee.csi_len + 2: cur + csi_st_len + bfee.csi_len + 2 + bfee.len] # ~~
# extract the CSI and fill the complex matrix
# we have 10 bit resolution for each real and image value
cur = cur + csi_st_len + 2
try:
bfee.csi = Bfee.fill_csi_matrix(array, cur, bfee.Nrx, bfee.Ntx, bfee.num_tones)
except Exception as e:
foo = 1
# print(e)
cur = cur_init + bfee.cnt + 2
# print('###########################next csi#####################################')
# 将类属性导出为dict，并返回
bfee_dict = {}
bfee_dict['timestamp_low'] = bfee.timestamp_low
bfee_dict['Nrx'] = bfee.Nrx
bfee_dict['Ntx'] = bfee.Ntx
bfee_dict['rssi_a'] = bfee.rssi_a
bfee_dict['rssi_b'] = bfee.rssi_b
bfee_dict['rssi_c'] = bfee.rssi_c
bfee_dict['noise'] = bfee.noise
bfee_dict['len'] = bfee.len
bfee_dict['csi'] = bfee.csi
bfee_dict['agc'] = bfee.agc
bfee.dicts.append(bfee_dict)
bfee.all_csi.append(bfee.csi)
bfee.all_aver_rssi.append((bfee.rssi_a + bfee.rssi_b + bfee.rssi_c) / bfee.Nrx)
bfee.all_timestamp.append(bfee.timestamp_low)
bfee.all_csi = np.array(bfee.all_csi)
return bfee
@staticmethod
def from_stream_intel(data_byte):
from functools import reduce
array = data_byte # reduce(函数，list)，将list中元素依次累加
bfee = Bfee()
# vmd.current_index = 0
bfee.file_len = len(array)
bfee.dicts = []
bfee.all_csi = []
bfee.all_timestamp = []
# vmd.timestamp_low0 = int.from_bytes(array[3:7], byteorder='little', signed=False)
# array = array[3:]
# %% Initialize variables
# ret = cell(ceil(len/95),1); # % Holds the return values - 1x1 CSI is 95 bytes big, so this should be upper bound
cur = 0 # % Current offset into file
count = 0 # % Number of records output
broken_perm = 0 # % Flag marking whether we've encountered a broken CSI yet
triangle = [0, 1, 3] # % What perm should sum to for 1,2,3 antennas
while cur < (bfee.file_len - 3):
# % Read size and code
# % 将文件数据读取到维度为 sizeA 的数组 A 中，并将文件指针定位到最后读取的值之后。fread 按列顺序填充 A。
bfee.field_len = int.from_bytes(array[cur:cur + 2], byteorder='big', signed=False)
bfee.code = array[cur + 2]
cur = cur + 3
# there is CSI in field if code == 187，If unhandled code skip (seek over) the record and continue
if bfee.code == 187:
pass
else:
# % skip all other info
cur = cur + bfee.field_len - 1
continue
# get beamforming or phy data
if bfee.code == 187:
count = count + 1
bfee.timestamp_low = int.from_bytes(array[cur:cur + 4], byteorder='little', signed=False)
bfee.bfee_count = int.from_bytes(array[cur + 4:cur + 6], byteorder='little', signed=False)
bfee.Nrx = array[cur + 8]
bfee.Ntx = array[cur + 9]
bfee.rssi_a = array[cur + 10]
bfee.rssi_b = array[cur + 11]
bfee.rssi_c = array[cur + 12]
bfee.noise = array[cur + 13] - 256
bfee.agc = array[cur + 14]
bfee.antenna_sel = array[cur + 15]
bfee.len = int.from_bytes(array[cur + 16:cur + 18], byteorder='little', signed=False)
bfee.fake_rate_n_flags = int.from_bytes(array[cur + 18:cur + 20], byteorder='little', signed=False)
bfee.calc_len = (30 * (bfee.Nrx * bfee.Ntx * 8 * 2 + 3) + 6) / 8
bfee.csi = np.zeros(shape=(30, bfee.Nrx, bfee.Ntx), dtype=np.dtype(np.complex)) # csi初始化
bfee.perm = [1, 2, 3]
bfee.perm[0] = ((bfee.antenna_sel) & 0x3)
bfee.perm[1] = ((bfee.antenna_sel >> 2) & 0x3)
bfee.perm[2] = ((bfee.antenna_sel >> 4) & 0x3)
cur = cur + 20
# get payload
payload = array[cur:cur + bfee.len]
cur = cur + bfee.len
index = 0
# Check that length matches what it should
if (bfee.len != bfee.calc_len):
print("MIMOToolbox:read_bfee_new:size", "Wrong beamforming matrix size.")
# Compute CSI from all this crap :
# import struct
for i in range(30):
index += 3
remainder = index % 8
for j in range(bfee.Nrx):
for k in range(bfee.Ntx):
real_bin = bytes([(payload[int(index / 8)] >> remainder) | (
payload[int(index / 8 + 1)] << (8 - remainder)) & 0b11111111])
real = int.from_bytes(real_bin, byteorder='little', signed=True)
imag_bin = bytes([(payload[int(index / 8 + 1)] >> remainder) | (
payload[int(index / 8 + 2)] << (8 - remainder)) & 0b11111111])
imag = int.from_bytes(imag_bin, byteorder='little', signed=True)
tmp = np.complex(float(real), float(imag))
# print(tmp)
bfee.csi[i, j, k] = tmp
index += 16
# % matrix does not contain default values
if sum(bfee.perm) != triangle[bfee.Nrx - 1]:
q = 1
# print('WARN ONCE: Found CSI (',filename,') with Nrx=', bfee.Nrx,' and invalid perm=[',bfee.perm,']\n' )
else:
temp_csi = np.zeros(bfee.csi.shape, dtype=np.dtype(np.complex))
# bfee.csi[:,bfee.perm[0:bfee.Nrx],:] = bfee.csi[:,0:bfee.Nrx,:]
for r in range(bfee.Nrx):
temp_csi[:, bfee.perm[r], :] = bfee.csi[:, r, :]
bfee.csi = temp_csi
# 将类属性导出为dict，并返回
# 需要提取：c, carrier_frequency, rx_loc, sample_rate, tx_loc, xb, yb, csi_data, ground_truth, time_stamp,
bfee_dict = {}
bfee_dict['timestamp'] = bfee.timestamp_low # timestamp_low：时间戳，相连两包此值差单位为微秒，通过验证发现100hz的发包频率此差值为10000,20hz的发包频率此差值为50000，此参数可以确定出波形的横轴时间
bfee_dict['bfee_count'] = bfee.bfee_count
bfee_dict['Nrx'] = bfee.Nrx # 接收天线数量
bfee_dict['Ntx'] = bfee.Ntx # 发射天线数量
bfee_dict['rssi_a'] = bfee.rssi_a
bfee_dict['rssi_b'] = bfee.rssi_b
bfee_dict['rssi_c'] = bfee.rssi_c
bfee_dict['noise'] = bfee.noise
bfee_dict['agc'] = bfee.agc
bfee_dict['antenna_sel'] = bfee.antenna_sel
bfee_dict['perm'] = bfee.perm
bfee_dict['len'] = bfee.len
bfee_dict['fake_rate_n_flags'] = bfee.fake_rate_n_flags
bfee_dict['calc_len'] = bfee.calc_len
bfee_dict['csi'] = bfee.csi
bfee.dicts.append(bfee_dict)
bfee.all_csi.append(bfee.csi)
bfee.all_timestamp.append(bfee.timestamp_low)
return bfee
if __name__ == '__main__':
inputfile = ''
inputfile = str(sys.argv[1])
bfee = Bfee.from_file_intel(inputfile, model_name_encode="gb2312")
# print(len(bfee.dicts))
# print(len(bfee.all_csi))
# print(bfee.all_csi)