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doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt Submission Jan 2004 UCLA - STMicroelectronics, Inc.Slide 1 Proposal for Statistical Channel Error Model D. Maniezzo, G. Pau, F. Benedetto, F. Cerioli, M. Gerla, W. Zhu, M. Fitz. UCLA – University of California, Los Angeles Valerio Filauro STMicroelectronics, Inc. {maniezzo|gpau|beneoet|fcerioli|gerla}@cs.ucla.edu{maniezzo|gpau|beneoet|fcerioli|gerla}@cs.ucla.edu, zhuw@ucla.edu, fitz@ee.ucla.edu zhuw@ucla.edufitz@ee.ucla.edu valerio.filauro@st.com

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doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt Submission Jan 2004 UCLA - STMicroelectronics, Inc.Slide 2 Outline Introduction Statistical Channel Model from Testbed Measurements Tested Conficuration Instant PER vs SNR Channel Model Assumptions Results Conclusions and Future Work

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doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt Submission Jan 2004 UCLA - STMicroelectronics, Inc.Slide 3 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: –the geometry of the MIMO system, –the model of the channel, –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.

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doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt Submission Jan 2004 UCLA - STMicroelectronics, Inc.Slide 4 Testbed: 3x4 MIMO System

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doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt Submission Jan 2004 UCLA - STMicroelectronics, Inc.Slide 5 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 ) : –The receiver in fixed location; the transmitter is in different corridor locations for different experiments –Transmission power is -10 dBm for each transmit antenna. –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.

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doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt Submission Jan 2004 UCLA - STMicroelectronics, Inc.Slide 6 Testbed Configuration Physical layer parameters –Carrier Frequency: 220.5625MHz –Bandwidth: 4KHz –Symbol Rate: 3.2 kbps –Antenna Configuration: Up to 3x4 –No mobility

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doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt Submission Jan 2004 UCLA - STMicroelectronics, Inc.Slide 7 Testbed Configuration (cont’d) Frame Format The transmitter continuously transmits Long frames with the following structure: –Preamble (300 known symbols): used for frame and carrier synchronization. –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. –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). –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. …

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doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt Submission Jan 2004 UCLA - STMicroelectronics, Inc.Slide 8 values averaged over a 2 hours experiment

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doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt Submission Jan 2004 UCLA - STMicroelectronics, Inc.Slide 9 Channel Model Assumptions SISO (1x1) instead of MIMO (3x4); single carrier (instead of OFDM) Propagation model: –Exp. Path loss model –AWGN –Shadowing –No Fading (it is compensated in the real system by: multiple antenna diversity and multiple frequency subchannel spreading). –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

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doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt Submission Jan 2004 UCLA - STMicroelectronics, Inc.Slide 10 Channel Model Assumptions (cont’d) Doppler effects: –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: –In this simplified model we didn’t take into account the relatively slow change in attenuation caused by people moving in the environment. –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.

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doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt Submission Jan 2004 UCLA - STMicroelectronics, Inc.Slide 11 MAC/PHY Wireless Model in ns2 MAC netIF Radio Propagation Model Wireless Channel Received Power Free Space Shadowing Error Model

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doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt Submission Jan 2004 UCLA - STMicroelectronics, Inc.Slide 12 Experimental Scenarios We simulate the following scenarios proposed by TGn Usage Models workgroup: –Residential (#1) –Residential IBSS (#2) –Enterprise (#4) –Hot Spot (#6) Note: the same scenarios were simulated in [3] by ST-Microelectronics (without error model).

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doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt Submission Jan 2004 UCLA - STMicroelectronics, Inc.Slide 13 Simulation Set-up ns-2.26 MAC: STMicroelectronics extension “MAC b/QoS” [3] PHY: –Data Rate: 300Mbps –TX power: 17 dbm Channel: –300Mbps –Exp. Path loss model + AWGN + Shadowing + error model Simulation time 60 secs

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doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt Submission Jan 2004 UCLA - STMicroelectronics, Inc.Slide 14 Results - Scenario #1

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doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt Submission Jan 2004 UCLA - STMicroelectronics, Inc.Slide 15 Results - Scenario #2

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doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt Submission Jan 2004 UCLA - STMicroelectronics, Inc.Slide 16 Results - Scenario #4

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doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt Submission Jan 2004 UCLA - STMicroelectronics, Inc.Slide 17 Results - Scenario #6

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doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt Submission Jan 2004 UCLA - STMicroelectronics, Inc.Slide 18 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

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doc.: 11-04-0012-00-000n-proposal-statistical-channel-error-model.ppt Submission Jan 2004 UCLA - STMicroelectronics, Inc.Slide 19 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 http://www.ee.ucla.edu/~fitz/NBTestbed/NBtestbed.html [3] “802.11-TGn Usage Models Simulation Results”, Valerio Filauro, Liwen Chu – STMicroelectronics Inc. IEEE802.11-03-0841-00-000n.doc

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