submission doc.: ieee 11-13/1080r0 september 2013 joseph levy, interdigital communications...
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Submission
doc.: IEEE 11-13/1080r0September 2013
Joseph Levy, InterDigital Communications Inc..Slide 1
Markov Modeling of the Channel for HEW System Level Simulations
Date: 2013-09-17
Name Affiliations Address Phone email Joseph LEVY InterDigital 2 Huntington
Quadrangle, Melville, NY 11747
+1 631 622 4139
Frank LA SITA InterDigital
Pengfei XIA InterDigital
Fengjun XI InterDigital
Authors:
Submission
doc.: IEEE 11-13/1080r0September 2013
Joseph Levy, InterDigital Communications Inc..Slide 2
Abstract
This contribution proposes that a Markov Model be used in system level simulations to provide an accurate and efficient means of including fast fading of outdoor channels for HEW system level modelling. Similar methods have been used by 3GPP for LTE modelling and 802.16 for 802.16e modelling.
Submission
doc.: IEEE 11-13/1080r0
Motivation
To provide an accurate and efficient outdoor physical channel model for HEW system level simulations.
Markov modeling techniques can provide such a system level simulation model. ([2], [5], [10])
The Markov modeling technique can be used for any agreed channel model (e.g. WINNER2, ITU, or customized)
The modeling approach and channel model(s) used for system level simulations are important considerations which should be agreed to allow for meaningful comparison of performance results.
Slide 3 Joseph Levy, InterDigital Communications Inc..
September 2013
(10^5) (10^5)
Submission
doc.: IEEE 11-13/1080r0September 2013
Slide 4
This contribution provides:• A description of the proposed Finite State
Markov Chain (FSMC) system level modeling• Examples of calculated transition probability
matrix (TPM) for some channel models of interest.
Joseph Levy, InterDigital Communications Inc..
Discussion
(10^5)
Submission
doc.: IEEE 11-13/1080r0
Joseph Levy, InterDigital Communications Inc..
Description of the proposed Finite State Markov Chain (FSMC) system level
modeling
September 2013
Slide 5
Submission
doc.: IEEE 11-13/1080r0
Joseph Levy, InterDigital Communications Inc..
Finite State Markov Chain
Model the channel SNR as a finite-state Markov chain (FSMC)
Each state represents a given value (range) of the SNR
The following example has four different SNR states
Slide 6
September 2013
0 1 2 3 4 5 6 7 8 9 10
x 104
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Sample index
inst
anta
neou
s S
NR
Submission
doc.: IEEE 11-13/1080r0
Joseph Levy, InterDigital Communications Inc..
Use of FSMC in System Level Simulations
Slide 7
September 2013
Submission
doc.: IEEE 11-13/1080r0
Joseph Levy, InterDigital Communications Inc..
Transition Probability Matrix (TPM)
Transition probability matrixpi,j : prob that the jth state is next, given that the ith state is current
be the prob distribution function when current state is the ith state
The underlying physical channel is fully characterized by the corresponding TPM matrix.
Slide 8
September 2013
NNNN ,,1
3,22,21,2
2,11,1
00
.........0
0
00
Submission
doc.: IEEE 11-13/1080r0
Joseph Levy, InterDigital Communications Inc..
In modeling the physical channels, we need to convert multiple SNR values (one per subcarrier) into one single SNR value
Potential approaches
Throughput averaging (algo 1)
Straightforward, not MCS dependent
effective channel amplitude square
SNR averaging (algo 2)
Used by OPNET for LTE downlink/uplink
Exponential effective SNR mapping (EESM), received bit mutual information (RBIR), Mean mutual information per bit (MMIB) [10]
MCS dependent (not studied herein)
Multi-Carrier SNR Mapping
Slide 9
September 2013
22
22 ||1log||1log
1o
ii HH
N
2|| oH
Submission
doc.: IEEE 11-13/1080r0
Joseph Levy, InterDigital Communications Inc..
Examples of calculated transition probability matrix (TPM) for some channel
models of interest.
September 2013
Slide 10
Submission
doc.: IEEE 11-13/1080r0
Joseph Levy, InterDigital Communications Inc..
Proposed HEW Use Cases [9]
Slide 11
September 2013
1High density of APs and high density of STAs per AP
a stadiumb airport/train stationsc exhibition halld shopping mallse E-Education
f Multi-media Mesh backhaul
2 High density of STAs – Indoor
a dense wireless officeb public transportation
c lecture hall
d Manufacturing Floor Automation
3High density of APs (low/medium density of STAs per AP) – Indoor
a dense apartment building
b Community Wi-Fi
4High density of APs and high density of STAs per AP – Outdoor
a Super dense urban Street
b Pico-cell street deployment
c Macro-cell street deployment
5High throughput demanding applications
a surgery/health care (similar to 2e from 11ac)
b production in stadium (similar to 1d-1e from 11ac)
c smart car
Submission
doc.: IEEE 11-13/1080r0
Joseph Levy, InterDigital Communications Inc..
Urban Micro Channels in HEW
• Urban Micro cellular environment fits well in HEW [8]• “The microcellular test environment focuses on small cells and high
user densities and traffic loads in city centers and dense urban areas. The key characteristics of this test environment are high traffic loads, outdoor and outdoor-to-indoor coverage. This scenario will therefore be interference-limited, using micro cells.” [7]
Slide 12
September 2013
WINNER 2 modelMetropolitan (C2)Typical Urban (B1, B4)Indoor to outdoor (A2)Rural macro (D1)
ITU modelUrban macro (UMa)Urban micro (UMi)Indoor (InH)High speed (RMa)
Submission
doc.: IEEE 11-13/1080r0
Joseph Levy, InterDigital Communications Inc..
TPM Generation Algorithm
Generate multiple (10^5) pairs of channel samples, each pair are separated by N OFDM symbols (N * 3.2 ms)
Each consists of multiple taps according to the channel model, e.g. WINNER 2 or ITU
Will serve as current state and next state in statistics collection
For each sample in the channel sample pair,
Convert it to freq domain using DFT
Convert multiple subcarrier SNRs into one effective SNR (either SNR averaging or throughput averaging)
Quantize the effective SNRs into P (16) equi-prob states
Find the probability of each state transitioning into other states accordingly
Slide 13
September 2013
Submission
doc.: IEEE 11-13/1080r0September 2013
Slide 14
Simulation Assumptions1) Channel Scenarios: WINNER 2 B1, ITU UMi
Directly comparable channel scenarios
2) Single transmit and single receive antenna
3) OFDM symbol separation between current and next state: 10 or 100
4) Large scale signal to noise ratio: 0 or 20dB
5) Mobile velocity: 3 or 30 km/hr
6) Two algorithms considered for determination of effective SNR:
1) Throughput averaging
2) SNR averaging
Joseph Levy, InterDigital Communications Inc..
Submission
doc.: IEEE 11-13/1080r0September 2013
Slide 15 Joseph Levy, InterDigital Communications Inc..
1 2 3 4 5 6 7 8 9 10111213141516
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ITU Channel
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WINNER 2 Channel
Diagonal max diff 0.10
Diagonal mean diff 0.05Off-diagonal max diff 0.09
Off-diagonal mean diff 0.01
ITU/WINNER 2 difference, 100 symbol, 20 dB snr, 30 km/hr, algo 1
The generated TPM are more or less similar for WINNER 2 B1 and
ITU UMi
ITU/WINNER 2 Comparison, 100 symbols. 20dB SNR, 30 km/h, Throughput Averaging
Submission
doc.: IEEE 11-13/1080r0September 2013
Slide 16 Joseph Levy, InterDigital Communications Inc..
The generated TPM are more or less similar for WINNER 2 B1 and
ITU UMi
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ITU Channel
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WINNER 2 Channel
Diagonal max diff 0.18
Diagonal mean diff 0.06
Off-diagonal max diff 0.07
Off-diagonal mean diff 0.01
ITU/WINNER 2 difference, 100 symbol, 20 dB snr, 30 km/hr, algo 2ITU/WINNER 2 Comparison, 100 symbols. 20dB SNR, 30 km/h, SNR Averaging
Submission
doc.: IEEE 11-13/1080r0September 2013
Slide 17 Joseph Levy, InterDigital Communications Inc..
Large scale SNR does not change the TPM noticeably (throughput averaging)
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20 dB
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0 dB
Diagonal max diff 0.05
Diagonal mean diff 0.02
Off-diagonal max diff 0.06
Off-diagonal mean diff 0.00
20dB vs 0 dB comparison, 100 symbol, 30 km/hr, WINNER 2 Channel B1, algo 1SNR Comparison, 20dB vs. 0dB, 100 symbols, 30 km/h, WINNER 2 B1 Throughput Averaging
Submission
doc.: IEEE 11-13/1080r0September 2013
Slide 18
Discussion on Multi-Carrier SNR MappingSNR averaging
Simple, independent of large scale SNR
SNR averaging occurs in the linear domain
Throughput averagingStrictly speaking depending on large scale SNR
This dependence is weak though (see comparison on previous page) and may be removed for simplicity
The mapping may thus be approximated by SNR averaging in the dB domain
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Joseph Levy, InterDigital Communications Inc..
Throughput averaging
SNR averaging in the dB domain
Submission
doc.: IEEE 11-13/1080r0September 2013
Slide 19
Simulation SummaryMarkov modeling of PHY multipath channels in HEW
TPM more or less similar for ITU UMi and WINNER 2 B1 channel
Faster velocity leads to more state changes in TPM
Larger separation leads to more state changes in TPM
Converting multiple subcarrier SNRs into a single value
SNR averaging in the linear domain
Throughput averaging
may be approximated by SNR averaging in the dB domain
More complex averaging may be usedThe general method may be applied to any other indoor or outdoor channels
for HEW system level simulations
ITU channels
WINNER 2 channels
and othersJoseph Levy, InterDigital Communications Inc..
Submission
doc.: IEEE 11-13/1080r0September 2013
Slide 20
Potential Items of Agreement
1. Use of Markov modeling of PHY multipath channels• Channel model(s) to be used (e.g. ITU UMi and WINNER 2 B1)
• Velocities to be considered
• SNR to be considered
• Number of Symbols to be averaged
2. Method of converting multiple subcarrier SNR• Throughput averaging
• More complex averaging
3. TPM for each agreed configuration• Generate multiple (e.g. 10^5) pairs, number of symbols separating pairs,
N
• Number of equi-probable states, P (e.g. 16)
Joseph Levy, InterDigital Communications Inc..
Submission
doc.: IEEE 11-13/1080r0September 2013
Slide 21
References[1] IEEE 802.11-13/0722r1, “HEW SG Evaluation Methodology”, Intel.
[2] IEEE 802.11-04/0184r0, “802.11n TGn proposal for PHY abstraction in MAC simulators,” ST Microelectronics.
[3] R. Yaniv et. Al., “CINR measurements using the EESM method”, IEEE C802.16e-05/141r3.
[4] L. Hentilä, P. Kyösti, M. Käske, M. Narandzic , and M. Alatossava. (2007, December.) MATLAB implementation of the WINNER Phase II Channel Model ver1.1 [Online]. Available: https://www.ist-winner.org/phase_2_model.html
[5] OPNET Technologies Inc., “LTE PHY Multipath Fading Models – Design Document”.
[6] Software implementation of IMT.EVAL channel model, doc num: IST-4-027756
[7] Report ITU-R M.2135-1 (12/2009) Guidelines for evaluation of radio interface technologies for IMT Advanced
[8] IEEE 802.11-13/0996r1, . “Outdoor Channel Model Candidates for HEW”, K. Josiam, R. Taori, and F. Tong,
[9] IEEE 802.11-13/0657, “Usage models for IEEE 802.11 High Efficiency WLAN study group (HEW SG) – Liaison with WFA”, Laurent Cariou
[10] IEEE 802.16m-08/004r5, “IEEE 802 16m Evaluation Methodology Document (EMD)”
Joseph Levy, InterDigital Communications Inc..
Submission
doc.: IEEE 11-13/1080r0
Joseph Levy, InterDigital Communications Inc..
Additional TPM plots
September 2013
Slide 22
Submission
doc.: IEEE 11-13/1080r0September 2013
Slide 23 Joseph Levy, InterDigital Communications Inc..
Faster velocity leads to more state transitions
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3 km/hr
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30 km/hr
Diagonal max diff 0.60
Diagonal mean diff 0.47
Off-diagonal max diff 0.23
Off-diagonal mean diff 0.03
Velocity comparison 30km/hr vs 3km/hr, 100 symbol, 20 dB snr, WINNER 2 Channel B1, algo 1Velocity Comparison, 30 km/h vs. 3 km/h, 100 symbols, 20dB, WINNER 2 B1 Throughput Averaging
Submission
doc.: IEEE 11-13/1080r0September 2013
Slide 24 Joseph Levy, InterDigital Communications Inc..
Larger separation leads to more state transitions
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10 symbol
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100 symbol
Diagonal max diff 0.59
Diagonal mean diff 0.47
Off-diagonal max diff 0.23
Off-diagonal mean diff 0.03
Symbol duration comparison 10 vs 100 symbols, 20 dB snr, 30 km/hr, WINNER 2 Channel B1, algo 1Packet Duration Comparison, 10 vs. 100 symbols, 20dB, 30 km/h, WINNER 2 B1 Throughput Averaging
Submission
doc.: IEEE 11-13/1080r0September 2013
Slide 25 Joseph Levy, InterDigital Communications Inc..
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Algo 1: Throughput Averaging
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Algo 2: SNR Averaging
Diagonal max diff 0.25
Diagonal mean diff 0.17Off-diagonal max diff 0.09
Off-diagonal mean diff 0.01
Algo difference, 100 symbol, 20 dB snr, 30 km/hr, WINNER 2 Channel B1Algorithm Comparison,100 symbols, 20dB, 30 km/h, WINNER 2 B1
Submission
doc.: IEEE 11-13/1080r0September 2013
Slide 26 Joseph Levy, InterDigital Communications Inc..
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Algo 1: Throughput Averaging
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Algo 2: SNR Averaging
Diagonal max diff 0.18
Diagonal mean diff 0.09
Off-diagonal max diff 0.08
Off-diagonal mean diff 0.01
Algo difference, 100 symbol, 20 dB snr, 30 km/hr, ITU Channel UMiAlgorithm Comparison,100 symbols, 20dB, 30 km/h, ITU Channel UMi