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Silicon Flatirons Center, UC Boulder
Risk-informed Interference AnalysisPutting spectrum allocation decisions on a more quantitative footing
Pierre de VriesSenior Adjunct Fellow, Silicon Flatirons Center, UC Boulder
Presentation at TPRC 4326 September 2015v. 0.4
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ContextInsatiable demand for spectrum rights leads to– Squeezing services together ever more tightly– Ever-tougher harm/benefit trade-offs
This entails regulatory judgments about harmful interference – Informed by engineering, typically (unfortunately) worst case analysis
Most agencies nowadays complement worst case with quantitative risk analysis (NRC, EPA, FAA, FDA, NASA, DHS, etc.) -- but not the FCC
Project goal – Put harmful interference analysis on a more quantitative, statistical footing– … in order to yield better decisions about allocations and rules
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Worst case (deterministic extreme value) analysisDoes not represent reality accurately – Most parameters that influence harm take a range of values
Over-conservative– Provides too much protection; doesn’t serve public interest, nor
economically efficientCan lead to false confidence that the resulting rules will avert harm– There are many kinds of radio interference– e.g. LightSquared/GPS: fixated on OOBE, but ABI was the real problem
BUT: Worst case is simple, and will continue to be used– Quickly gives a black & white answer
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Risk examples: AccidentsAccident on Mount Everest– High likelihood, high
consequence– Overall risk: very high
Skydiving accident– Low likelihood, high
consequence– Overall risk: moderate
Falling off a bicycle– Low likelihood, low
consequence– Overall risk: low
Likelihood
Low Medium High
Consequence
High
Medium
Low
EverestSkydiving
BicyclingRisk
Unicycling
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Some terminologyRisk– The combination of likelihood and consequence for multiple hazards– Kaplan and Garrick’s risk triplet: What can go wrong? How likely is it? What
are the consequences? – There are other, complementary approaches: economics, psychology, socio-
cultural analysisQuantitative risk assessment (QRA)– Apply risk triplet using numerical estimates of likelihoods and consequences
Risk-informed interference assessment– A systematic analysis of the likelihood and consequence of interference
hazards caused by the interaction between radio systems
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Risk-informed interference assessmentCurrent scope – Planning, e.g. allocation, rulemaking, waivers– Not post-deployment operation (e.g. adjudication & enforcement, service provider ops)– Leave aside cost/benefit analysis
Related work in spectrum (quantitative risk analysis generally: 30+ years of literature)– Michael Marcus, IEEE-USA (2012): Noted MCL vs. stochastic modeling, flagged lack of FCC
policy– Grunwald, Alderfer & Baker (TPRC 2014): Holistic analysis of 5 GHz Wi-Fi/Globalstar
interference – Littman & De Vries (TPRC 2014): Lessons for FCC from use of QRA in nuclear regulation– FCC TAC (2015): Noted value of risk assessment in allocation decisions, proposed a
method– Cui & Weiss (TPRC 2015): QoS and monetary risk for different kinds of spectrum sharing
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Four element method
1. Make an inventory of all significant harmful interference hazard modes
2. Define a consequence metric(s) to characterize the severity of hazards
3. Assess the likelihood and consequence of each hazard mode
4. Aggregate the results to inform decision making
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Applying the method: MetSat case study
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Meteorological Satellite (MetSat) & LTE
1675–1710 MHz– weather satellite receiving earth
stations– NOAA and DoD
Focus on polar orbiting satellites – leave aside geostationary ones
1695–1710 MHz– AWS-3 cellular mobile uplink
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NTIA Fast Track, CSMAC WG-1 studiesDetermine an interference
protection criterion (IPC): aggregate i/f power not to be exceeded in MetSat receiver
Assume a “sea” of LTE mobilesCalculate the smallest radius
without mobiles that satisfies IPC
Exclude/limit mobile ops within this zone
Essentially worst case
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1. Make an inventory of hazards
Interference types– Co-channel– Out-of-band emission (OOBE)– Adjacent band interference (ABI)
Types of interferer– Point sources and aggregate
interference– Unintentional and intentional
radiators– Operators: well-meaning,
ignorant or malicious
Working taxonomy
– Interfering system (“transmitters”)
– Affected system (“receivers”)
– Coupling between transmitters & receivers
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Transmitter characteristics (LTE)
Cellular mobiles– Transmit power per mobile, co-
channel and out-of-channel – Frequency channel width– Percentage loading of base
station – Location and density of mobiles– Location and density of base
stations
CDF of total EIRP per scheduled mobile
Source: CSMAC (2013), Appendix 3-3
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Receiver characteristics (MetSat)
Source: NTIA (2010) “Fast Track Report”
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Transmitter-Receiver Coupling
– Propagation loss from transmitter to receiver
– Additional losses– Antenna heights: satellite
receiver and mobile transmitters
– Earth station antenna elevation and azimuth
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Propagation loss:field measurements and fit
Source: Phillips, Sicker & Grunwald (2012)
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2. Define consequence metric(s)Corporate, aka operational: Cost, ability to complete the mission – Receiver metrics not available (indications of high baseline
outage)Service– Availability: the percentage of time that the link margin is not
met– Quality: bit-error ratio
RF– Fraction of interference-free margin consumed by interference– Interfering signal power levels (IPC) to be exceeded no more
than 20% or 0.0125% of the time
– Interference-to-noise ratio in the receiver
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3. Assess likelihood & consequenceConsider co-channel interference, a la Fast Track and
CSMAC WG-1Calculate received interfering power for each exclusion
radiusDetermine the probability a given power is exceeded1. Choose -121
dBm interference protection criterion (IPC)
2. Select 80th percentile, so that IPC is exceeded no more than 20% of the time
3. Results in a 34 km protection radius
4. Vertical “slice” through distribution yields distribution of interfering power at the 34 km radius; see next slide
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Probability of exceeding IPC versus radiusVertical slice through
range/interference chart
Choose -121 dBm interference protection criterion (IPC)
Meets ITU-R SA.1026 long-term IPC:– Below IPC more than
80% of time – i.e. exceeded less
than 20% of the time
Satisfies -121 dBm IPC at 34 km exclusion distance
Interference limit met > 80% of the time
Likelihood
Consequence
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4. Aggregate risks Non-RF: equipment failure,
operator error, …Co-channel interference– sunspot activity– long-term low-level i/f– short-term high-level i/f
Interference from adjacent band– OOBE– ABI
OOBE (hypothetical)
ITU-R long-term criterion: with 34 km exclusion, -121 dBm exceeded less than 20% of time
ITU-R short-term criterion: with 34 km exclusion, -118 dBm exceeded less than 0.0125% of time (hypothetical)
Likelihood
Consequence
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Conclusions
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Benefits of risk-informed interference assessmentA common currency for comparing – different interference mechanisms– competing assessments
More comprehensive analysis – increases the chances of identifying unexpected harmful
interference mechanismsObjective information for decision makers – balancing the benefits of a new service and its adverse
technical impact on existing services
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Action items for regulatorsEducate– Get the community thinking & talking via papers, workshops and consultations– Develop know-how through lectures and in-house training
Set a good example– Quantify likelihoods and consequences in own findings – Request (ideally, require) disclosure and analysis of likelihood & consequence
in filingsStart small, but start soon– Changing the culture is going to take a long time– Pilot approach on low risk/impact proceedings, e.g. waivers for services at
fixed locations
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Action items for the Executive & Legislature
Oversight– Make risk-informed assessment an oversight requirement– Don’t fall for nightmare scenarios– Support and encourage regulators that use risk-informed
interference assessmentsRequire spectrum regulators to do risk analysis– US: Extend existing requirements for risk and cost/benefit
analysis (cf. Executive Orders, OMB directives) to independent agencies
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Summary
Risk analysis considers the likelihood-consequence combinations for multiple hazards, and complements a “worst case” analysis
This will yield better spectrum allocation decisionsFour element method: (1) inventory hazards; (2) define
metrics; (3) assess likelihood & consequence; (4) aggregateAdding this to the toolkit requires culture change, so start
small – but start soon
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We are not able in life to avoid risk but only to choose between risks
Stanley Kaplan & John Garrick (1981)
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Backup
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Risk Chart
Likelihood
Qualitative descriptors Rare Unlikely Possible Likely Certain
Quantscales Determined case by case
Consequence
Very High Severity
Determined case by case
High Severity
Medium Severity
Low Severity
Very Low Severity
Risk
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Deterministic methods and worst case analysisDeterministic methods: evaluate risk in terms of a predetermined set of
causes characterized by single-valued parameters– potentially interfering transmitter operating at a fixed distance – at a fixed transmit power– to a specific receiver– single-valued path loss
“Worst” case: parameters take extreme values– transmitter at closest distance – maximum allowed transmit power– the least interference-resistant receiver on the market– direct path without any intervening obstructions
Deterministic method doesn’t necessarily entail using extreme values (but usually does)
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Utility of extreme value analysis
Extreme value analysis can be useful– if worst case assumptions show that a particular hazard
doesn’t pose a risk, it can be omitted from subsequent analysis
– if best case assumptions indicate that a hazard poses risks even in favorable circumstances, further analysis is needed
Typically, though, worst case is used “illogically”– worst case assumptions showing harm used to justify
further analysis, and perhaps even determine rules
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Interference analysis: a schematic
– Interfering (transmitting) system
– Affected (receiving) system
– Coupling between transmitters & receivers
Affected System Characteristics
Interfering System Characteristics
Affected System Locations
Interfering System Locations
CouplingCharacteristics
Likelihood and Consequence Metrics
Risk Assessment
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Probability of exceeding IPC versus radiusHorizontal slice through
range/interference chartAs radius increases,
probability that IPC will met increases
Choose -121 dBm interference
Meeting IPC 80% of time means exceeded 20% of the time: ITU-R SA.1026 criterion
34 km exclusion distance
Interference limit met > 80% of the time