1. Coherence Time Measurement for TGac Channel Model
November 2009
doc.: IEEE /1173r0
November 2009
Coherence Time Measurement for TGac Channel Model
Date:
Authors:
Greg Breit, Qualcomm Incorporated
Greg Breit, Qualcomm Incorporated

2. November 2009
doc.: IEEE /1173r0
November 2009
Abstract
A channel aging metric of 0.5 correlation was used to assess channel coherence time in recent measurement campaigns. For channels with stationary users, this metric is highly insensitive and in many cases may be unachievable in measured data. Consequently, the coherence time measurements to date in support of the TGac channel model appear biased downward, suggesting an unnecessarily high level of channel Doppler. This contribution discusses alternative analytical methods which may produce more accurate and unbiased estimates of channel coherence time from existing measurement data.
Greg Breit, Qualcomm Incorporated
Greg Breit, Qualcomm Incorporated

3. Sample Coherence Time Analysis
November 2009
Sample Coherence Time Analysis
TGn coherence time defined as delay at which autocorrelation drops to 0.5
Standard definition from Rappaport, others
Same method used by Intel and NTT for TGac Channel Model
Left hand plot superimposes autocorrelations (pos. lags only) for all TX, RX, and tones
Autocorrelation is not scaled for overlap size, so coherence time>10s not measurable
Right hand plot is CDF of all coherence times (all corr=0.5 crossings)
Greg Breit, Qualcomm Incorporated

4. Asymptotes in Measured Coherence Time Distributions
November 2009
doc.: IEEE /1173r0
November 2009
Asymptotes in Measured Coherence Time Distributions
Intel: 1.6s Meas. Duration
NTT: 6.4s Meas. Duration
Qualcomm: 20s Meas. Duration
All measurements exhibit asymptotic coherence time at high values
Asymptote occurs at ~½ of the measurement duration
Median value falls on asymptote in all cases
Does this impact the reported coherence times?
Qualcomm measurements taken in large auditorium with pedestrian motion
Greg Breit, Qualcomm Incorporated
Greg Breit, Qualcomm Incorporated

5. Impact of Data Duration on Observable Coherence Time
November 2009
doc.: IEEE /1173r0
November 2009
Impact of Data Duration on Observable Coherence Time
Data Duration = 20s
Data Duration = 10s
Data Duration = 1.6s
Channel Autocorrelation
Median: 9.3s
Median: 4.8s
Coherence Time CDF
Median: ~800ms
10%ile: 5.0s
10%ile: 2.0s
10%ile: ~500ms
Coherence time was calculated from segments of complete 20s Qualcomm data record
Data were reanalyzed using 10s and 1.6s segments (latter is similar to Intel meas. duration)
Distributions of coherence time are biased by the data duration
Asymptote is an analysis artifact – both 50% and 10% (left tail) values are impacted
Limiting Qualcomm data to 1.6s duration (right hand plots) produces results very similar to Intel values
Greg Breit, Qualcomm Incorporated
Greg Breit, Qualcomm Incorporated

6. Computation of Correlation
November 2009
Computation of Correlation
“Biased” form decreases with increasing delay T
Fewer overlapping samples in summation in numerator
Will always approach zero as TL
Can alternatively use “Unbiased” form
Adjusts for number of overlapping samples in numerator summation
Greg Breit, Qualcomm Incorporated

7. Results using “Unbiased” Autocorrelation
November 2009
Results using “Unbiased” Autocorrelation
Each correlation point is adjusted for the size of the data overlap
Allows observation of coherence time out to total measurement duration
Extreme lags are unreliable due to small number of overlapping samples
No asymptote, but now have cases where 0.5 correlation is never reached
~90% of cases in this example
0.5 correlation is not a good metric to evaluate channels with stationary users
Fine for mobile channels, but too insensitive for the non-mobile case
Greg Breit, Qualcomm Incorporated

8. Relevance of Coherence Time Analysis
November 2009
doc.: IEEE /1173r0
November 2009
Relevance of Coherence Time Analysis
We care about channel coherence time because it impacts the required rate of CSI update for TxBF and DL MU-MIMO
Direct observation of channel coherence time in static conditions is difficult due to dependence on measurement duration
Calculation is flawed when data duration is limited
0.5 correlation is a very insensitive metric of channel aging
We need a more sensitive metric of channel aging
Time delay to correlation value ρ (ρ>0.5)
Time delay to XdBc MS channel error (e.g. -20dBc, -30dBc)
Time delay to X% beamformed capacity degradation
TxBF or MU-MIMO
Both NTT (09/0303r1) and Intel (09/0538r4) considered this originally
TGac Doppler model should use a value that reproduces the rate of channel aging observed in measurements
Greg Breit, Qualcomm Incorporated
Greg Breit, Qualcomm Incorporated

9. Revisiting the Intel Results (09/0538)
November 2009
doc.: IEEE /1173r0
November 2009
Revisiting the Intel Results (09/0538)
Original Intel analysis focused on TxBF capacity degradation as a function of time delay
Measurements show 49% capacity degradation at 100ms delay
Most extreme Doppler case (“DM”)
50% capacity loss never reached for more moderate cases (SM, PM, LM)
Intel applied same analysis to 11n Model D (~60ms coherence time)
~50% capacity degradation at 10ms delay
Suggests a measured coherence time at least 10x of 11n model
10x60ms = 600ms coherence time in the very worst case (DM)
Longer than 600ms for all other test cases
% degradation of TxBF gain relative to SDM
Motion Type
20ms delay
50ms delay
100ms delay
200ms delay
DM (arms waving at both links)
18.6
38.0
49.0
58.0
SM (arms waving at one link)
9.2
20.3
28.9
34.2
PM (pedestrian motion)
20.2
27.1
33.3
38.7
LM (light motion)
8.3
12.6
17.2
22.0
Greg Breit, Qualcomm Incorporated
Greg Breit, Qualcomm Incorporated

10. Revisiting the NTT Results (09/0303r1)
November 2009
doc.: IEEE /1173r0
November 2009
Revisiting the NTT Results (09/0303r1)
NTT observed approximately 11% capacity degradation after 100ms
Channel measurements performed with pedestrian motion
These results may be compared to existing 11n model or current 11ac model to estimate a coherence time value for the 11ac model
Data suggest a more stable channel than observed by Intel
Greg Breit, Qualcomm Incorporated
Greg Breit, Qualcomm Incorporated

11. Alternative Aging Metric – MS Error of Delayed CSI
November 2009
doc.: IEEE /1173r0
November 2009
Alternative Aging Metric – MS Error of Delayed CSI
CDFs of MS error between current and delayed channel (11ac Model D-NLOS)
Expressed in dBc (relative to channel power)
Statistics pooled over time samples and subcarriers
“D/T” in legend refers to ratio of CSI delay to channel coherence time
Sims were performed assuming 400ms coh time, but everything scales…
-30dBc error occurs when channel delay is 1.8% of model coherence time
-25dBc error occurs when channel delay is 2.5% of model coherence time
-20dBc error occurs when channel delay is 5% of model coherence time
This figure provides a basis by which to estimate coherence time from measurements in a D-NLOS-like environment
Requires stable phase in channel estimates over time
Greg Breit, Qualcomm Incorporated
Greg Breit, Qualcomm Incorporated

12. Alternative Aging Metric 2 – MS Error of Delayed CSI from Correlation
November 2009
doc.: IEEE /1173r0
November 2009
Alternative Aging Metric 2 – MS Error of Delayed CSI from Correlation
Straightforward to show that SNR ≡ |ρ|2/(1-|ρ|2), where ρ is the correlation coefficient between S and S+N
MSE of CSI can be estimated from (1- |ρ|2)/|ρ|2 (e.g., ρ= ↔ -20dBc MSE)
Correlation is more immune to phase drift than direct MSE calculation
Figure shows CDFs of MS error estimated from complex correlation coefficient
Medians are indistinguishable from direct calculation of MSE (previous slide)
Slightly wider distribution
Preferred method for analysis of measured data due to phase drift immunity
Greg Breit, Qualcomm Incorporated
Greg Breit, Qualcomm Incorporated

13. Sample Measurements Channel sounding system (5 GHz) Large lab
November 2009
Sample Measurements
Channel sounding system (5 GHz)
PHY based on 11n: 20 MHz, 64 subcarriers (48 used for sounding)
4x4 MIMO channel measured every 40ms
Large lab
Open but highly cluttered environment
Benches, racks, lab equipment, metal cabinets, ventilation shafts
Good representation of Model D
“Typical office, sea of cubes, large conference room”
STA placed NLOS to AP (range 10m)
Four test cases
1: Baseline – no deliberate motion in channel
5-10 people working seated in the lab, so some ambient motion
2-4: Deliberate pedestrian motion down middle of lab
Performed three times for each STA location
Different ped paths each time
Ped path never passes between AP and STA
Greg Breit, Qualcomm Incorporated

14. Measurement Results (analysis of 90%ile)
November 2009
Measurement Results (analysis of 90%ile)
Baseline
Ped Motion 1
delay (90%ile)
 80ms/1.8% = 4.4s coh time
delay (90%ile)
 80ms/5% = 1.6s coh time
Ped Motion 2
Ped Motion 3
delay (90%ile)
 80ms/5% = 1.6s coh time
delay (90%ile)
 40ms/5% = ~800ms coh time
Greg Breit, Qualcomm Incorporated

15. November 2009
Summary
Coherence time results to date (Intel, NTT, Qualcomm) appear flawed
Measurements are solid, but analysis is problematic
Insufficient measurement duration to observe ρ=0.5 accurately
Channel with stationary users may never reach ρ=0.5
Flawed values were the basis for current 11ac Doppler model
Should evaluate data using a more sensitive metric of channel aging
Degradation of TxBF or MU-MIMO capacity vs. delay
Original approach by both Intel and NTT
Growth of CSI MS error vs. delay
Easy to calculate
Expresses channel aging in similar terms as other CSI impairments
Requires stable measurement phase over time
Correlation vs. delay (higher value than 0.5)
Directly analogous to MSE analysis
More tolerant of phase drift than MSE
Channel model Doppler parameter should match measured data in terms of rate of channel aging evaluated by a reliable metric
Current 400ms coherence time assumption appears conservative
TGac channel model should adopt a value >600ms (800ms or 1.6s suggested)
Greg Breit, Qualcomm Incorporated

16. November 2009
References
Honma, N., et al., “Effect of SDMA in ac,” Doc. IEEE /303r1
Perahia, E., “Investigation into the n Doppler Model,” Doc. IEEE /0538r0
Perahia, E., “Channel Coherence Time.” Doc. IEEE /0784r0
Yamada, W. et al., “Coherence Time Measurement in NTT Lab.” Doc. IEEE /0828r0
Greg Breit, Qualcomm Incorporated