prediction of fading broadband wireless channels
DESCRIPTION
Prediction of Fading Broadband Wireless Channels. JOINT BEATS/Wireless IP seminar, Loen. Torbjörn Ekman UniK-University Graduate Center Oslo, Norway. Contents. Motivation Noise Reduction Linear Prediction of Channels Delay Spacing, Sub-sampling Results Power Prediction Results - PowerPoint PPT PresentationTRANSCRIPT
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Prediction of Fading Broadband Wireless Channels
Torbjörn Ekman
UniK-University Graduate Center
Oslo, Norway
JOINT BEATS/Wireless IP seminar, Loen
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Contents
• Motivation• Noise Reduction• Linear Prediction of Channels• Delay Spacing, Sub-sampling• Results• Power Prediction• Results• Recommendations
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With channels known in advance the problem with fast fading can be turned into an advantage
• Adaptive resource allocation
• Fast link adaptation
The multi-user diversity can be exploited
Why?
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Noise Reduction of Estimated Channels
The same noise floor is seen in the power delay profile.
The estimated Doppler spectrum is low pass and has a noise floor.
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IIR smoothers
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FIR or IIR Wiener-smoother?
• IIR smoothers1. based on a low pass ARMA-model2. can be numerically sensitive3. need few parameters• FIR smoothers1. based on a model for the covariance2. need many parameters• Both have similar performance.• Both use estimates of the variance of the
estimation error and the Doppler frequency.
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Linear Prediction of Mobile Radio Channels
• Model for the tap
• The FIR-predictor
• The MSE-optimal coefficients
• A step towards power prediction
• Can produce prediction of the frequency response
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Linear prediction with noise reduction
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Model Based Prediction
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Delay Spacing
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The MSE optimal delay spacing for the Jakes model depends on the variance of the estimation error.
The NMSE has many local minima.
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Sub-sampling and aliasing
• OSR 50
• Sub-sampling rate 13
• Jakes model
• SNR 10dB
• 16 predictor coefficients
• FIR Wiener smoother (128)
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Prediction performance on a Jakes model
• OSR 50 (100 samples per )
• FIR predictor, 8 coefficients
• FIR Wiener smoother (128)
• Dashed lines: no smoother
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The Measurements
• Channel sounder measurements in urban and suburban Stockholm
• Carrier frequency 1880MHz• Baseband sampling rate 6.4MHz• Channel update rate 9.1kHz • Vehicle speeds 30-90km/h• 1430 consecutive impulse responses at each
location• Data from 41 measurement locations
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Prediction performance on the taps
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Channel prediction performance
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Power Prediction
• The power of a tap
• A biased quadratic predictor
• An unbiased quadratic predictor
• Rayleigh fading taps: the optimal for the complex tap prediction is optimal also for the power prediction.
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Biased and unbiased NMSE
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Observed power or complex
regressors?
• AR2-process
• Approx. Jakes
• FIR predictor (2)
• Dash-dotted line for observed power in the regressors.
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Power prediction performance
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Median tap prediction performance
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Channel prediction
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Compare average predictor with unbiased predictor
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Predictor Design
• Estimate the channel with uttermost care.• Noise reduction using Wiener smoothers.• Estimate sub-sampled AR-models or use a
direct FIR-predictor.• Estimate as few parameters as possible.• Design Kalman predictor using a noise model
that compensates for estimation errors• Power prediction: Squared magnitude of tap
prediction with added bias compensation.