IEEE 802.22 is a standardized WRAN (Wireless Regional Area Network) system that operates in TVWS (TV White Spaces) and aims to achieve an effective spectrum utilization. Since IEEE 802.22 offers excellent propagation characteristics in the UHF (Ultra High Frequency) band, it is expected to support a cost-effective wireless communication system in rural areas. To provide a long-distance wireless communication, it is important for the receiver design to compensate a multipath fading attributed to large differences in path lengths, while existing multipath fading channel profiles applicable to IEEE 802.22 has generalization and statistical limitations. To generally and stochastically reproduce the multipath propagation characteristics in an actual wide area environment, an algorithm to obtain a statistical channel model extracted from the field experiment data is required. In this study, we develop a novel channel modeling algorithm based on the conventional S-V (Saleh-Valenzuela) modeling algorithm that offers an approach to model and reproduce the multipath characteristics in an actual environment. The proposed channel modeling algorithm applies a dynamic GEV (Generalized Extreme Value) distribution fitting for the amplitude fluctuation of individual arrival cluster. We also evaluate the channel reproduction performance of the proposed algorithm by computer simulation using channel modeling factors calculated from the experiment result with a FE (Fading Emulator). As a result, by applying the proposed algorithm, the multipath fading characteristics measured in the experiment can be modeled, and its reproducibility is confirmed with regard to relative path power distribution, rms delay spread distribution, and BER characteristics.


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    Title :

    Channel Modeling Algorithm for TVWS-based IEEE 802.22 WRAN System in Rural Areas


    Contributors:


    Publication date :

    2020-11-01


    Size :

    1731294 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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