Rician Modeling and Prediction for Wireless Packet Data Systems

Wireless systems exploiting multi-user diversity require accurate channel state information. In this paper we examine channel prediction as a method to improve the performance of these systems. We model the outdoor channel by the Rician model, which combines diffuse spectra with a single specular co...

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Bibliographic Details
Published in:IEEE transactions on wireless communications 2008-11, Vol.7 (11), p.4692-4699
Main Authors: Ling, J., Tureli, U., Chizhik, D., Papadias, C.
Format: Article
Language:English
Subjects:
Accuracy
Applied sciences
broadband mobile communication systems
cellular technology
Channel state information
Channels
cross layer design and optimization
Data systems
Detection, estimation, filtering, equalization, prediction
Diffusion
Downlink
Exact sciences and technology
Filters
Information, signal and communications theory
k factors
Mathematical models
multiple access techniques
Noise levels
Optimization
Outdoor
Power system modeling
Prediction tools
Predictive models
resource allocation and interference management
Rician channels
Signal and communications theory
Signal, noise
Spectra
Studies
Systems, networks and services of telecommunications
Telecommunications
Telecommunications and information theory
Throughput
Transmission and modulation (techniques and equipments)
Wavelength measurement
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Summary:Wireless systems exploiting multi-user diversity require accurate channel state information. In this paper we examine channel prediction as a method to improve the performance of these systems. We model the outdoor channel by the Rician model, which combines diffuse spectra with a single specular component. Prediction accuracy is determined for the Rician model given various ratios (K factors) of specular to diffuse power. Simulation results show that accurate channel prediction further than one wavelength can be achieved at 30 dB SNR when the channel K factor is greater than ten. The predictor was evaluated on measured channels, and the Rician model was found to be appropriate as prediction intervals of the measured data are similar to those of synthetic data with same K factor. Using measurements some results regarding channel stationarity and optimal filter order are presented. We show for a proportionally fair scheduled downlink packet system that the predictor reduces fade margin at fixed packet outage leading to an improvement in throughput.
ISSN:1536-1276
1558-2248
DOI:10.1109/T-WC.2008.070825