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        <identifier>oai:meral.edu.mm:recid/3120</identifier>
        <datestamp>2021-12-13T05:47:08Z</datestamp>
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          <dc:title>An Effective Hybrid Time Synchronization Approach for Time Based Wireless Indoor Localization</dc:title>
          <dc:creator>Yuzana Hlaing</dc:creator>
          <dc:creator>Nyein Aye Maung Maung</dc:creator>
          <dc:creator>Win Zaw</dc:creator>
          <dc:description>&lt;p&gt;Position estimation for wireless indoor applications&lt;br&gt;
is a challenging problem due to lack of standard positioning&lt;br&gt;
system in indoor environments. The performance of indoor&lt;br&gt;
localization is restricted with many factors such as complex&lt;br&gt;
structure of the building, various materials inside the building&lt;br&gt;
and lack of availability and accessibility of GPS. Moreover,&lt;br&gt;
various localization techniques and applied wireless&lt;br&gt;
technologies can also affect the localization capability. Recently,&lt;br&gt;
time based wireless indoor localization is a popular trend.&lt;br&gt;
Having precise time synchronization is a vital concept for&lt;br&gt;
getting the accurate target localization. In this paper, an&lt;br&gt;
effective hybrid time synchronization approach is proposed for&lt;br&gt;
time based wireless indoor localization which can increase the&lt;br&gt;
time synchronization accuracy and hence to improve the&lt;br&gt;
localization performance. This new approach is based on&lt;br&gt;
Reference Broadcast Synchronization (RBS) and Pairwise&lt;br&gt;
Broadcast Synchronization (PBS) protocols, in which the&lt;br&gt;
number of timing messages is reduced compared with some&lt;br&gt;
existing synchronization protocols. As well, synchronization&lt;br&gt;
accuracy is improved as two way message exchange method is&lt;br&gt;
applied for time synchronization among all nodes. In addition,&lt;br&gt;
transmission delay is considered by using Gaussian random&lt;br&gt;
variables and probability density function to improve the&lt;br&gt;
accuracy performance. The proposed model is simulated with&lt;br&gt;
python programming language to show the robustness and&lt;br&gt;
accuracy of this system.&lt;/p&gt;</dc:description>
          <dc:date>2018-11-26</dc:date>
          <dc:identifier>http://hdl.handle.net/20.500.12678/0000003120</dc:identifier>
          <dc:identifier>https://meral.edu.mm/records/3120</dc:identifier>
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