doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt submission jan 2004 ucla -...
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Jan 2004
UCLA - STMicroelectronics, Inc.Slide 1
doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt
Submission
Proposal for Statistical Channel Error Model
D. Maniezzo, G. Pau, F. Benedetto, F. Cerioli, M . Gerla,W. Zhu, M. Fitz.
UCLA â University of California, Los AngelesValerio Filauro
STMicroelectronics, Inc.
{maniezzo|gpau|beneoet|fcerioli|gerla}@cs.ucla.edu,[email protected], [email protected]
Jan 2004
UCLA - STMicroelectronics, Inc.Slide 2
doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt
Submission
Outline
⢠Introduction⢠Statistical Channel Model from Testbed
Measurements⢠Tested Conficuration⢠Instant PER vs SNR⢠Channel Model Assumptions⢠Results⢠Conclusions and Future Work
Jan 2004
UCLA - STMicroelectronics, Inc.Slide 3
doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt
Submission
Introduction⢠A realistic channel simulation model is mandatory to study a
PHY/MAC layer such as 802.11n that takes into account the channel conditions.
⢠The channel conditions affect the throughput, the delay and the jitter.
⢠Goal of the simulator: measure network throughput as a function of MIMO parameters such as: â the geometry of the MIMO system, â the model of the channel, â the distance of the stations, etc;
⢠A statistical error model gives us a faster simulator than if we integrated TGn Matlab channel model [1] with the selected network simulator.
Jan 2004
UCLA - STMicroelectronics, Inc.Slide 4
doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt
Submission
Testbed: 3x4 MIMO System
Jan 2004
UCLA - STMicroelectronics, Inc.Slide 5
doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt
Submission
Statistical Channel Model from Testbed Measurements
⢠From real MIMO measurements from the Narrowband Testbed [2], we derive Packet Error Statistic vs. SNR and use it in the network simulator.
⢠We select as a network simulator ns-2 but the approach applies to any simulator.
⢠Test-bed (in UCLA UnWiReD Lab ):â The receiver in fixed location; the transmitter is in different corridor
locations for different experimentsâ Transmission power is -10 dBm for each transmit antenna. â 24 different S/T coding schemes are tested
⢠Alamouti: 4PSK, 8PSK, 16QAM, 64QAM.⢠3-TX Orthogonal Block Code: 4PSK, 8PSK, 16QAM, 64QAM.⢠3-TX Super Orthogonal Block Code with 2 extra bits: 4PSK, 8PSK, 16QAM, 64QAM⢠3-TX Super Orthogonal Block Code with 3 extra bits: 4PSK, 8PSK, 16QAM, 64QAM. ⢠3-TX Super Orthogonal Block Code with 4 extra bits: 4PSK, 8PSK, 16QAM, 64QAM. ⢠3x4 BLAST: 4PSK, 8PSK, 16QAM, 64QAM.
⢠The measurements are repeated for different receiver positions to have PER vs. SNR.
Jan 2004
UCLA - STMicroelectronics, Inc.Slide 6
doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt
Submission
Testbed Configuration
⢠Physical layer parametersâ Carrier Frequency: 220.5625MHzâ Bandwidth: 4KHz â Symbol Rate: 3.2 kbps â Antenna Configuration: Up to 3x4â No mobility
Jan 2004
UCLA - STMicroelectronics, Inc.Slide 7
doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt
Submission
Testbed Configuration (contâd)⢠Frame Format
The transmitter continuously transmits Long frames with the following structure:â Preamble (300 known symbols): used for frame and carrier synchronization.â Control Frame (Alamouti coded frame): used for transmission of the state
(seed) of the random number generator, which is used to generate the random information bits to be coded.
â Data Block: consists of 24 Data Frames.Each Data Frame
⢠carries random information bits encoded using one of the 24 Space-Time Coding Schemes.
⢠consists of 300 symbols (228 of which are data and 72 are pilot symbols). â Silence Period between Long Frames (70 symbols): the transmitter is silent.
The receiver uses this period to estimate the received noise power in the operating frequency band.
âŚ
Jan 2004
UCLA - STMicroelectronics, Inc.Slide 8
doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt
Submission
values averaged over a 2 hours experiment
Packet Error Rate vs SNR
1.00E-04
1.00E-03
1.00E-02
1.00E-01
1.00E+00
0 5 10 15 20 25 30 35 40 45
SNR (dB)
PE
R
Alamouti, 16QAM, R=4
Alamouti, 64QAM, R=6
BLAST, QPSK, R=6
BLAST, 16QAM, R=12
BLAST, 64QAM, R=18
Jan 2004
UCLA - STMicroelectronics, Inc.Slide 9
doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt
Submission
Channel Model Assumptions⢠SISO (1x1) instead of MIMO (3x4); single carrier (instead of OFDM)⢠Propagation model:
â Exp. Path loss modelâ AWGNâ Shadowingâ No Fading (it is compensated in the real system by: multiple antenna diversity and multiple frequency
subchannel spreading).
â Error Model: from the measurements we set a look-up table that gives the PER vs. SNR.
⢠Scaling from 4Khz band and 200Mhz carrier to 5Mhz and 2.4Ghz: As a first approximation, for a given encoding scheme, the error rates are dependent only on SNR.
⢠As a first approximation, bit errors are assumed to be randomly and uniformly distributed in a frame; packet error rate is computed based on packet length. Future work will investigate error burstiness
⢠Note: One caveat is that at higher speeds, and using OFDM, better, more robust codes could be used. Anyway, current 4Khz results will provide a conservative estimation
Jan 2004
UCLA - STMicroelectronics, Inc.Slide 10
doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt
Submission
Channel Model Assumptions (contâd)
Doppler effects:â Doppler effects are present as people move in the environment
changing the multipath characteristics and thus causing a drift in carrier frequency (with possible extra errors). This effect is negligible in an indoor slow mobility scenario.
Multipath fade changes and obstruction of direct ray:â In this simplified model we didnât take into account the relatively
slow change in attenuation caused by people moving in the environment.
â In the future, careful monitoring of this attenuation in the experiment could be used to set up a proper 2 state Markov Chain to capture these effects.
Jan 2004
UCLA - STMicroelectronics, Inc.Slide 11
doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt
Submission
MAC/PHY Wireless Model in ns2
MACMAC
netIFnetIFRadioRadio
Propagation Propagation ModelModel
Wireless ChannelWireless Channel
Received PowerReceived Power
Free SpaceShadowing
ErrorModel
Jan 2004
UCLA - STMicroelectronics, Inc.Slide 12
doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt
Submission
Experimental Scenarios
⢠We simulate the following scenarios proposed by TGn Usage Models workgroup:â Residential (#1)
â Residential IBSS (#2)
â Enterprise (#4)
â Hot Spot (#6)
⢠Note: the same scenarios were simulated in [3] by ST-Microelectronics (without error model).
Jan 2004
UCLA - STMicroelectronics, Inc.Slide 13
doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt
Submission
Simulation Set-up
⢠ns-2.26 ⢠MAC: STMicroelectronics extension âMAC
b/QoSâ [3]⢠PHY:
â Data Rate: 300Mbpsâ TX power: 17 dbm
⢠Channel:â 300Mbpsâ Exp. Path loss model + AWGN + Shadowing + error
model⢠Simulation time 60 secs
Jan 2004
UCLA - STMicroelectronics, Inc.Slide 14
doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt
Submission
Results - Scenario #1
0.00E+00
2.00E+06
4.00E+06
6.00E+06
8.00E+06
1.00E+07
1.20E+07
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
ID #
TH
RO
UG
HP
UT (bp
s)
ORIGINAL ERROR MODEL
Jan 2004
UCLA - STMicroelectronics, Inc.Slide 15
doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt
Submission
Results - Scenario #2
0.00E+00
1.00E+06
2.00E+06
3.00E+06
4.00E+06
5.00E+06
6.00E+06
7.00E+06
8.00E+06
0 1 2 3 4 5 6 7 8 9 10 11 12
ID #
TH
RO
UG
HP
UT (bp
s)ORIGINAL ERROR MODEL
Jan 2004
UCLA - STMicroelectronics, Inc.Slide 16
doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt
Submission
Results - Scenario #4
0.00E+00
5.00E+05
1.00E+06
1.50E+06
2.00E+06
2.50E+06
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43
ID #
TH
RO
UG
HP
UT (bp
s)
ORIGINAL ERROR MODEL
Jan 2004
UCLA - STMicroelectronics, Inc.Slide 17
doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt
Submission
Results - Scenario #6
0.00E+00
2.00E+05
4.00E+05
6.00E+05
8.00E+05
1.00E+06
1.20E+06
1.40E+06
1.60E+06
1.80E+06
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60 62 64 66 68 70
ID #
TH
RO
UG
HP
UT (bp
s)
ORIGINAL ERROR MODEL
Jan 2004
UCLA - STMicroelectronics, Inc.Slide 18
doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt
Submission
Future Work⢠More realistic measurements will be available shortly from a new
2.4Ghz testbed.⢠More experiments will be conducted to evaluate error burstiness and
obtain a more accurate dependence of packet error probability on packet size.
⢠A two states Markov chain error model will be developed to take into account the time correlation of the errors (e.g. attenuation caused by people moving in the environment).
⢠The knowledge of time correlation between errors will be exploitedfor optimal parameter setting (eg, fragment aggregation size).
⢠Model parameterization will be used to limit the size of the look-up table (ie PER vs. SNR) as the system becomes more complex
Jan 2004
UCLA - STMicroelectronics, Inc.Slide 19
doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt
Submission
References
[1] 11-03-0940-01-000n.doc TGn Channel Model, November 2003.
[2] Narrowband Testbed webpage:http://www.ee.ucla.edu/~fitz/NBTestbed/NBtestbed.html
[3] â802.11-TGn Usage Models Simulation Resultsâ, Valerio Filauro, Liwen Chu â STMicroelectronics Inc.IEEE802.11-03-0841-00-000n.doc