def performIapForFssBlocking(fss_record, sas_uut_fad_object,
sas_th_fad_objects):
"""Computes post IAP interference margin for FSS Blocking incumbent.
FSS protection is provided over blocking pass band.
Args:
fss_record: A FSS record (dict).
sas_uut_fad_object: FAD object from SAS UUT
sas_th_fad_object: a list of FAD objects from SAS Test Harness
Returns:
ap_iap_ref: The post-IAP allowed interference, as a dict formatted as:
{latitude : {longitude : [interference(mW/IAPBW), .., interference(mW/IAPBW)]}}
where the list holds all values per channel of that protection point.
"""
# Actual protection threshold used for IAP - calculated by applying
# a pre-defined Pre-IAP headroom (Mg) at each protection threshold(Q)
fss_blocking_iap_threshold = interf.dbToLinear(
THRESH_FSS_BLOCKING_DBM_PER_RBW - MARGIN_FSS_BLOCKING_DB)
grants = data.getGrantObjectsFromFAD(sas_uut_fad_object,
sas_th_fad_objects)
# Get number of SAS
num_sas = len(sas_th_fad_objects) + 1
# Get FSS T&C Flag value
fss_ttc_flag = fss_record['ttc']
# Get the FSS infos
fss_point, fss_info, fss_freq_range = data.getFssInfo(fss_record)
fss_low_freq, fss_high_freq = fss_freq_range
# FSS Passband is between 3700 and 4200 and TT&C flag is set to FALSE
if (fss_low_freq >= interf.FSS_TTC_LOW_FREQ_HZ
and fss_high_freq <= interf.FSS_TTC_HIGH_FREQ_HZ
and fss_ttc_flag is False):
raise Exception(
"IAP for FSS not applied for FSS Pass band 3700 to 4200 "
"and TT&C flag set to false, please check the inputs.")
logging.debug('$$$$ Calling FSS blocking Protection $$$$')
# 5MHz channelization is not required for Blocking protection
protection_channels = [(interf.CBRS_LOW_FREQ_HZ, fss_low_freq)]
iap_interfs = iapPointConstraint(fss_point, protection_channels,
interf.CBRS_LOW_FREQ_HZ, fss_low_freq,
grants, fss_info, None, None,
fss_blocking_iap_threshold,
data.ProtectedEntityType.FSS_BLOCKING)
ap_iap_ref = calculatePostIapAggregateInterference(
interf.dbToLinear(THRESH_FSS_BLOCKING_DBM_PER_RBW), num_sas,
iap_interfs)
return ap_iap_ref
def performIapForFssCochannel(fss_record, sas_uut_fad_object,
sas_th_fad_objects):
"""Computes post IAP interference margin for FSS Co-channel incumbent.
FSS protection is provided over co-channel pass band.
Args:
fss_record: A FSS record (dict).
sas_uut_fad_object: A FAD object from SAS UUT
sas_th_fad_object: A list of FAD objects from SAS Test Harness
Returns:
ap_iap_ref: The post-IAP allowed interference, as a dict formatted as:
{latitude : {longitude : [interference(mW/IAPBW), .., interference(mW/IAPBW)]}}
where the list holds all values per channel of that protection point.
"""
fss_cochannel_thresh_q = THRESH_FSS_CO_CHANNEL_DBM_PER_IAPBW
# Actual protection threshold used for IAP - calculated by applying
# a pre-defined Pre-IAP headroom (Mg) at each protection threshold(Q)
fss_cochannel_iap_threshold = interf.dbToLinear(fss_cochannel_thresh_q -
MARGIN_FSS_CO_CHANNEL_DB)
grants = data.getGrantObjectsFromFAD(sas_uut_fad_object,
sas_th_fad_objects)
# Get number of SAS
num_sas = len(sas_th_fad_objects) + 1
# Get the FSS infos
fss_point, fss_info, fss_freq_range = data.getFssInfo(fss_record)
fss_low_freq, fss_high_freq = fss_freq_range
# Get channels for co-channel CBSDs
if fss_high_freq < interf.CBRS_HIGH_FREQ_HZ:
raise ValueError(
'FSS high frequency should not be less than CBRS high frequency(Hz)'
)
protection_channels = interf.getProtectedChannels(fss_low_freq,
interf.CBRS_HIGH_FREQ_HZ)
# FSS Co-channel algorithm
logging.debug('$$$$ Calling FSS co-channel Protection $$$$')
iap_interfs = iapPointConstraint(fss_point, protection_channels,
fss_low_freq, interf.CBRS_HIGH_FREQ_HZ,
grants, fss_info, None, None,
fss_cochannel_iap_threshold,
data.ProtectedEntityType.FSS_CO_CHANNEL)
ap_iap_ref = calculatePostIapAggregateInterference(
interf.dbToLinear(fss_cochannel_thresh_q), num_sas, iap_interfs)
return ap_iap_ref
def performIapForEsc(esc_record, sas_uut_fad_object, sas_th_fad_objects):
"""Computes post IAP interference margin for ESC.
IAP algorithm is run over ESC passband 3550-3660MHz for Category A CBSDs and
3550-3680MHz for Category B CBSDs.
Args:
esc_record: An ESC record (dict of schema |EscSensorRecord|).
sas_uut_fad_object: FAD object from SAS UUT
sas_th_fad_objects: A list of FAD objects from SAS Test Harness
Returns:
ap_iap_ref: The post-IAP allowed interference, as a dict formatted as:
{latitude : {longitude : [interference(mW/IAPBW), .., interference(mW/IAPBW)]}}
where the list holds all values per channel of that protection point.
"""
esc_thresh_q = THRESH_ESC_DBM_PER_IAPBW
# Actual protection threshold used for IAP - calculated by applying
# a pre-defined Pre-IAP headroom (Mg) at each protection threshold(Q)
esc_iap_threshold = interf.dbToLinear(esc_thresh_q - MARGIN_ESC_DB)
grants = data.getGrantObjectsFromFAD(sas_uut_fad_object,
sas_th_fad_objects)
# Get number of SAS
num_sas = len(sas_th_fad_objects) + 1
# Get the ESC infos
protection_point, esc_antenna_info = data.getEscInfo(esc_record)
# Get ESC passband 3550-3680 MHz protection channels
protection_channels = interf.getProtectedChannels(interf.ESC_LOW_FREQ_HZ,
interf.ESC_HIGH_FREQ_HZ)
logging.debug('$$$$ Calling ESC Protection $$$$')
# ESC algorithm
iap_interfs = iapPointConstraint(protection_point, protection_channels,
interf.ESC_LOW_FREQ_HZ,
interf.ESC_HIGH_FREQ_HZ, grants, None,
esc_antenna_info, None, esc_iap_threshold,
data.ProtectedEntityType.ESC)
ap_iap_ref = calculatePostIapAggregateInterference(
interf.dbToLinear(esc_thresh_q), num_sas, iap_interfs)
return ap_iap_ref
def generatePurgeListForFssPoint(cbsds, fss_point, fss_info):
"""Generates the FSS purge list.
Implementation of algorithm described in R2-SGN-29.
The list of grants to be purged based on the interference caused by their
out of band emission are identified and returned.
Args:
cbsds: The list of |CbsdData| objects that are in the neighborhood to an FSS.
fss_point: The FSS location as a (longitude, latitude) tuple.
fss_info: The |data.FssInformation| of the FSS.
Returns:
A list of dictionaries, each holding keys:
'grant': the grants to be purged
'cbsd': the corresponding |CbsdData| object.
A list of multiple key-value pairs with keys "grantData", "cbsd" and values as grants to be
purged and corresponding cbsd data object respectively.
"""
# List of grants to be purged for the fss entity.
final_purge_list = []
# List of dictionaries containing the grant_info based on the highest grant
# from FSS OOBE calculation
grants_cbsds_info_for_oobe_calculation = getGrantInfoListForFssOobeCalculation(
cbsds)
# Calculate the threshold value in dBm for the OOBE interference
oobe_threshold_value = -129 + 10 * np.log10(
REF_BW / interf.MHZ) - FSS_OOBE_MARGIN
while True:
logging.info(
'Starting another loop of the FSS purge list; current purge list: %s',
final_purge_list)
# Calculate the OOBE interference value for each grant.
calculateOobeInterference(grants_cbsds_info_for_oobe_calculation,
fss_point, fss_info)
# Sort the grants based on the calculated interference value.
sorted_grants_cbsds_info = sorted(
grants_cbsds_info_for_oobe_calculation,
key=lambda grant: grant['oobe_interference'])
# Find the largest index such that aggregation of the interferences are not equal
# to or higher than the OOBE threshold.
oobe_interferences = [
interf.dbToLinear(grant['oobe_interference'])
for grant in sorted_grants_cbsds_info
]
cumulated_interference = np.cumsum(oobe_interferences)
index = np.searchsorted(cumulated_interference,
interf.dbToLinear(oobe_threshold_value))
grants_to_purge = sorted_grants_cbsds_info[index:]
grants_cbsds_info_for_oobe_calculation = sorted_grants_cbsds_info[:
index]
# If no grants are identified for purging in this iteration then break the loop
if not grants_to_purge:
logging.info('No grants to purge.')
break
# Otherwise update purge list
for purged_grant in grants_to_purge:
remaining_grants = []
for grant in purged_grant['cbsd']['grants']:
# Find the grants matching mcbsd value and add it to the purge list
if purged_grant['mcbsd'] == getMcbsdValue(grant):
final_purge_list.append(
grants_cbsds_namedtuple(grant, purged_grant['cbsd']))
elif purged_grant['mcbsd'] > getMcbsdValue(grant):
# Find the grants with mcbsd value less than the max_grant mcbsd value
# and add it to the remaining grants list
remaining_grants.append(grant)
# Identify the grant with the highest highFrequency value among the remaining
# grants for the CBSD and add it to the grants_cbsds_info_for_oobe_calculation
# list for next iteration.
if remaining_grants:
max_grant = max(remaining_grants,
key=lambda x: x['operationParam']
['operationFrequencyRange']['highFrequency'])
grants_cbsds_info_for_oobe_calculation.append({
'mcbsd':
getMcbsdValue(max_grant),
'cbsd':
purged_grant['cbsd']
})
return final_purge_list
def iapPointConstraint(protection_point, channels, low_freq, high_freq, grants,
fss_info, esc_antenna_info, region_type, threshold,
protection_ent_type):
"""Computes aggregate interference(Ap and ASASp) from authorized grants.
This routine is applicable for FSS Co-Channel and ESC Sensor protection points,
and PPA/GWPZ protection areas. It calculates aggregate interference over all
5MHz channels, and feeds post-IAP assessment of allowed interference margins.
Args:
protection_point: A protection point as a tuple (longitude, latitude).
channels: The 5MHz channels as a list of (low_freq, high_freq) tuples.
low_freq: low frequency of protection constraint (Hz)
high_freq: high frequency of protection constraint (Hz)
grants: An iterable of |data.CbsdGrantInfo| grants.
fss_info: The FSS information of type |data.FssInformation|.
esc_antenna_info: ESC antenna information of type |data.EscInformation|.
region_type: Region type of the protection point: 'URBAN', 'SUBURBAN' or 'RURAL'.
threshold: The protection threshold (mW).
protection_ent_type: The entity type (|data.ProtectedEntityType|).
Returns:
A tuple (latitude, longitude, asas_interference, agg_interference) where:
asas_interference: a list of interference (per channel) for managing SAS.
agg_interference: a list of total interference (per channel).
"""
# Get protection constraint of protected entity
protection_constraint = data.ProtectionConstraint(
latitude=protection_point[1],
longitude=protection_point[0],
low_frequency=low_freq,
high_frequency=high_freq,
entity_type=protection_ent_type)
# Get all the grants inside neighborhood of the protection entity
grants_inside = interf.findGrantsInsideNeighborhood(
grants, protection_point, protection_ent_type)
# Get all the grants inside neighborhood of the protection entity, and
# with frequency overlap to the protection point.
neighbor_grants = interf.findOverlappingGrants(grants_inside,
protection_constraint)
if not neighbor_grants:
return (protection_point[1], protection_point[0], [0] * len(channels),
[0] * len(channels))
# Get number of grants, IAP protection threshold and fairshare per channel.
num_unsatisfied_grants = len(neighbor_grants)
# Initialize list of aggregate interference from all the grants
# (including grants from managing and peer SAS )
aggr_interf = [0] * len(channels)
# Initialize list of aggregate interference from managing SAS grants.
asas_interf = [0] * len(channels)
# Algorithm to calculate interference within IAPBW using EIRP obtained for all
# the grants through application of IAP
num_unsatisfied_grants_channels = []
iap_threshold_channels = []
fairshare_channels = []
for index, channel in enumerate(channels):
# Get protection constraint over 5MHz channel range
channel_constraint = data.ProtectionConstraint(
latitude=protection_point[1],
longitude=protection_point[0],
low_frequency=channel[0],
high_frequency=channel[1],
entity_type=protection_ent_type)
# Identify CBSD grants overlapping with frequency range of the protection entity
# in the neighborhood of the protection point and channel
channel_neighbor_grants = interf.findOverlappingGrants(
neighbor_grants, channel_constraint)
num_unsatisfied_grants_channel = len(channel_neighbor_grants)
# Computes interference quota for this protection_point and channel.
iap_threshold = threshold
# Calculate the fair share per channel based on unsatisfied grants
fairshare_channel = 0
if num_unsatisfied_grants_channel > 0:
fairshare_channel = float(
iap_threshold) / num_unsatisfied_grants_channel
num_unsatisfied_grants_channels.append(num_unsatisfied_grants_channel)
iap_threshold_channels.append(iap_threshold)
fairshare_channels.append(fairshare_channel)
# List of grants initialized with max EIRP
grants_eirp = [grant.max_eirp for grant in neighbor_grants]
# Initialize list of grants_satisfied to False
grants_satisfied = [False] * num_unsatisfied_grants
# Initialize list of grants_removed to False
grants_removed = [False] * num_unsatisfied_grants
# Initialize grant overlap and interference per channel dictionary
# Values will be stored in the format of key as tuple (grant_id, channel_id)
# and respective value as:
# overlap_flag: True/False based on grant overlaps with channel
# interference: respective interference value for the key
grants_overlap_flag = {}
grants_interference = {}
with cache.CacheManager(wf_hybrid.CalcHybridPropagationLoss):
# Using memoizing cache manager only for lengthy calculation (hybrid on PPA/GWPZ).
while num_unsatisfied_grants > 0:
for g_idx, grant in enumerate(neighbor_grants):
if grants_satisfied[g_idx]:
continue
for idx, channel in enumerate(channels):
# Check if grant overlaps with protection point, channel
grant_overlap_check = interf.grantFrequencyOverlapCheck(
grant, channel[0], channel[1], protection_ent_type)
grants_overlap_flag[(g_idx, idx)] = grant_overlap_check
if not grant_overlap_check:
continue
# Get protection constraint over 5MHz channel range
channel_constraint = data.ProtectionConstraint(
latitude=protection_point[1],
longitude=protection_point[0],
low_frequency=channel[0],
high_frequency=channel[1],
entity_type=protection_ent_type)
# Compute interference that grant causes to protection point over channel
interference = interf.dbToLinear(
interf.computeInterference(grant, grants_eirp[g_idx],
channel_constraint,
fss_info, esc_antenna_info,
region_type))
# If calculated interference is more than fair share of interference
# to which the grants are entitled then grant is considered unsatisfied
if interference < fairshare_channels[idx]:
# Add the interference caused by all the grants in a 5MHz channel
grants_interference[(g_idx, idx)] = interference
grants_satisfied[g_idx] = True
else:
grants_satisfied[g_idx] = False
break
num_grants_good_overall_channels = 0
for gr_idx, grant in enumerate(neighbor_grants):
if grants_removed[gr_idx]:
continue
if not grants_satisfied[gr_idx]:
continue
if num_unsatisfied_grants > 0:
num_unsatisfied_grants -= 1
for ch_idx, channel in enumerate(channels):
# Grant interferes with protection point over channel
if grants_overlap_flag[(gr_idx, ch_idx)]:
iap_threshold_channels[ch_idx] = (
iap_threshold_channels[ch_idx] -
grants_interference[(gr_idx, ch_idx)])
num_unsatisfied_grants_channels[ch_idx] -= 1
# Re-calculate fairshare for a channel
if num_unsatisfied_grants_channels[ch_idx] > 0:
fairshare_channels[ch_idx] = (
float(iap_threshold_channels[ch_idx]) /
num_unsatisfied_grants_channels[ch_idx])
aggr_interf[ch_idx] += grants_interference[(gr_idx,
ch_idx)]
if grant.is_managed_grant:
asas_interf[ch_idx] += grants_interference[(
gr_idx, ch_idx)]
# Removing grants from future consideration
grants_removed[gr_idx] = True
# Increase number of grants good over all channels
num_grants_good_overall_channels += 1
if num_grants_good_overall_channels == 0:
for grant_idx, grant in enumerate(neighbor_grants):
# Reduce power level of all the unsatisfied grants
if not grants_satisfied[grant_idx]:
grants_eirp[grant_idx] -= 1
logging.debug('IAP point_constraint @ point %s: %s',
(protection_point[1], protection_point[0]),
zip(asas_interf, aggr_interf))
# Return the computed data
return protection_point[1], protection_point[0], asas_interf, aggr_interf
def performIapForPpa(ppa_record, sas_uut_fad_object, sas_th_fad_objects,
pal_records):
"""Computes post IAP interference margin for PPA incumbents.
Routine to get protection points within PPA protection area and perform
IAP algorithm on each protection point.
Args:
ppa_record: A PPA record dict.
sas_uut_fad_object: A FAD object from SAS UUT.
sas_th_fad_object: A list of FAD objects from SAS Test Harness
pal_records: PAL records associated with a PPA protection area
Returns:
ap_iap_ref: The post-IAP allowed interference, as a dict formatted as:
{latitude : {longitude : [interference(mW/IAPBW), .., interference(mW/IAPBW)]}}
where the list holds all values per channel of that protection point.
"""
ppa_thresh_q = THRESH_PPA_DBM_PER_IAPBW
# Actual protection threshold used for IAP - calculated by applying
# a pre-defined Pre-IAP headroom (Mg) at each protection threshold(Q)
ppa_iap_threshold = interf.dbToLinear(ppa_thresh_q - MARGIN_PPA_DB)
grants = data.getGrantObjectsFromFAD(sas_uut_fad_object,
sas_th_fad_objects, ppa_record)
# Get number of SAS
num_sas = len(sas_th_fad_objects) + 1
logging.debug('$$$$ Getting GRID points for PPA Protection Area $$$$')
# Get Fine Grid Points for a PPA protection area
protection_points = utils.GridPolygon(
ppa_record['zone']['features'][0]['geometry'], PPA_GRID_RES_ARCSEC)
# Get the region type of the PPA protection area
ppa_region = ppa_record['ppaInfo']['ppaRegionType']
# Find the PAL records for the PAL_IDs defined in PPA records
ppa_pal_ids = ppa_record['ppaInfo']['palId']
matching_pal_records = [
pr for pr in pal_records if pr['palId'] == ppa_pal_ids[0]
]
if not matching_pal_records:
raise ValueError('No matching PAL record, please check input')
pal_record = matching_pal_records[0]
# Get the frequencies from the PAL records
ppa_freq_range = pal_record['channelAssignment']['primaryAssignment']
ppa_low_freq = ppa_freq_range['lowFrequency']
ppa_high_freq = ppa_freq_range['highFrequency']
# Get channels over which area incumbent needs partial/full protection
protection_channels = interf.getProtectedChannels(ppa_low_freq,
ppa_high_freq)
# Apply IAP for each protection constraint with a pool of parallel
# processes.
logging.debug('$$$$ Calling PPA Protection $$$$')
iapPoint = partial(iapPointConstraint,
channels=protection_channels,
low_freq=ppa_low_freq,
high_freq=ppa_high_freq,
grants=grants,
fss_info=None,
esc_antenna_info=None,
region_type=ppa_region,
threshold=ppa_iap_threshold,
protection_ent_type=data.ProtectedEntityType.PPA_AREA)
pool = mpool.Pool()
iap_interfs = pool.map(iapPoint, protection_points)
ap_iap_ref = calculatePostIapAggregateInterference(
interf.dbToLinear(ppa_thresh_q), num_sas, iap_interfs)
return ap_iap_ref
def performIapForGwpz(gwpz_record, sas_uut_fad_object, sas_th_fad_objects):
"""Computes post IAP interference margin for GWPZ incumbents.
Routine to get protection points within GWPZ protection area and perform
IAP algorithm on each protection point.
Args:
gwpz_record: A GWPZ record dict.
sas_uut_fad_object: FAD object from SAS UUT
sas_th_fad_objects: A list of FAD objects from SAS Test Harness
Returns:
ap_iap_ref: The post-IAP allowed interference, as a dict formatted as:
{latitude : {longitude : [interference(mW/IAPBW), .., interference(mW/IAPBW)]}}
where the list holds all values per channel of that protection point.
"""
gwpz_thresh_q = THRESH_GWPZ_DBM_PER_IAPBW
# Actual protection threshold used for IAP - calculated by applying
# a pre-defined Pre-IAP headroom (Mg) at each protection threshold(Q)
gwpz_iap_threshold = interf.dbToLinear(gwpz_thresh_q - MARGIN_GWPZ_DB)
grants = data.getGrantObjectsFromFAD(sas_uut_fad_object,
sas_th_fad_objects)
# Get number of SAS
num_sas = len(sas_th_fad_objects) + 1
logging.debug('$$$$ Getting GRID points for GWPZ Protection Area $$$$')
# Get Fine Grid Points for a GWPZ protection area
protection_points = utils.GridPolygon(
gwpz_record['zone']['features'][0]['geometry'], GWPZ_GRID_RES_ARCSEC)
gwpz_freq_range = gwpz_record['record']['deploymentParam'][0]\
['operationParam']['operationFrequencyRange']
gwpz_low_freq = gwpz_freq_range['lowFrequency']
gwpz_high_freq = gwpz_freq_range['highFrequency']
gwpz_region = gwpz_record['landCategory']
# Get channels over which area incumbent needs partial/full protection
protection_channels = interf.getProtectedChannels(gwpz_low_freq,
gwpz_high_freq)
logging.debug('$$$$ Calling GWPZ Protection $$$$')
iapPoint = partial(iapPointConstraint,
channels=protection_channels,
low_freq=gwpz_low_freq,
high_freq=gwpz_high_freq,
grants=grants,
fss_info=None,
esc_antenna_info=None,
region_type=gwpz_region,
threshold=gwpz_iap_threshold,
protection_ent_type=data.ProtectedEntityType.GWPZ_AREA)
pool = mpool.Pool()
iap_interfs = pool.map(iapPoint, protection_points)
ap_iap_ref = calculatePostIapAggregateInterference(
interf.dbToLinear(gwpz_thresh_q), num_sas, iap_interfs)
return ap_iap_ref
def convertAndSumInterference(cbsd_interference_list):
"""Converts interference in dBm to mW to calculate aggregate interference"""
interferences_in_dbm = np.array(cbsd_interference_list)
return np.sum(interf.dbToLinear(interferences_in_dbm))