Positioning information not only benefits the localization systems but also improve the performance of geo-location based cognitive radio (CR) networks. Most researchers focus on other aspects of CR and databases but rarely discuss the fact of how the positioning information can influence the performance of CR systems in indoor environments. WLAN is the most common technology used for indoor positioning. Optimization of WLAN access points (APs) can enhance accuracy of the localization systems. In this paper, we present an optimization algorithm for WLAN localization system. The proposed scheme estimates the optimal density of the APs required to meet the coverage demands and optimize their deployment to enhance the localization accuracy. One of our main contributions is the APs hearability-based reference points (RPs) clustering technique. Its uniqueness lies in the fact that not all installed APs participate in the localization process for all RPs. Finally, we analyze the variables governing the optimization process and the trade-off between cost, computation, and accuracy. Extensive simulations are conducted to validate the effectiveness of our algorithm. Our approach reduces the mean positioning error by 25% and the maximum error by 44% compared to the previous algorithm’s performance.


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    Title :

    Improving Positioning Accuracy Using WLAN Optimization for Location Based Services and Cognitive Radio Networks


    Additional title:

    Lect.Notes Social.Inform.


    Contributors:
    Guo, Qing (editor) / Meng, Weixiao (editor) / Jia, Min (editor) / Wang, Xue (editor) / Khattak, Sohaib Bin Altaf (author) / Jia, Min (author) / Guo, Qing (author) / Gu, Xuemai (author)

    Conference:

    International Conference on Wireless and Satellite Systems ; 2021 July 31, 2021 - August 02, 2021



    Publication date :

    2022-01-21


    Size :

    15 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English






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