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    vc2011 Klo

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    da0luna
    The document describes optimizing a multislope propagation channel model for near a transmitter site using particle swarm optimization. The model uses two coupling points at 40m and 1km to define the simulation space, with a breakpoint in between whose position is optimized by PSO to minimize mean squared error between the model and measured data. Simulations were done with one and two optimized breakpoints, with the two breakpoint model showing slightly better accuracy based on the results tables.

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    vc2011 Klo

    Uploaded by

    da0luna
    22 views1 page
    The document describes optimizing a multislope propagation channel model for near a transmitter site using particle swarm optimization. The model uses two coupling points at 40m and 1km to define the simulation space, with a breakpoint in between whose position is optimized by PSO to minimize mean squared error between the model and measured data. Simulations were done with one and two optimized breakpoints, with the two breakpoint model showing slightly better accuracy based on the results tables.

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    The document describes optimizing a multislope propagation channel model for near a transmitter site using particle swarm optimization. The model uses two coupling points at 40m and 1km to define the simulation space, with a breakpoint in between whose position is optimized by PSO to minimize mean squared error between the model and measured data. Simulations were done with one and two optimized breakpoints, with the two breakpoint model showing slightly better accuracy based on the results tables.

    Copyright:

    Attribution Non-Commercial (BY-NC)
    Download as PDF, TXT or read online from Scribd
    Download as pdf or txt
    22 views1 page

    vc2011 Klo

    Uploaded by

    da0luna
    The document describes optimizing a multislope propagation channel model for near a transmitter site using particle swarm optimization. The model uses two coupling points at 40m and 1km to define the simulation space, with a breakpoint in between whose position is optimized by PSO to minimize mean squared error between the model and measured data. Simulations were done with one and two optimized breakpoints, with the two breakpoint model showing slightly better accuracy based on the results tables.

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    of 1

    Near Site Outdoor Channel Measurement and Optimization Processing

    Lukas Klozar
    Department of Radio Electronics, Brno University of Technology, Purkyova 118, 612 00 Brno, Czech Republic E-mail: xkloza00@stud.feec.vutbr.cz

    Abstract This poster deals with a multislope propagation channel model optimization for a near site of a transmitter in mobile communication networks. The PSO processing, of pathloss model parameters, with a criterial function based on the MSE deviation error estimation, is described.
    Keywords Propagation channel, model, multislope, path loss, PSO.
    1 30

    M u lti s lo p e L o g D is ta n c e p ro p a g a tio n m o d e l

    The multislope modeling approach is applied to simulate the higher level attenuation in near site of a transmitter. Two Coupling points, at distance 40m and 1 km define the boundaries of the simulation space. Between them the PSO processing model the parameters of a channel to the best fit with measurred data. The MSE decision technique in criteria function of PSO is applied.

    P a t h lo s s [d B ]

    Simulation Introduction

    1 20 1 10 1 00 90 80 70 60 10
    2

    10

    D is t a n c e [m ]

    Propagation Channel Modeling


    The path loss levels of Coupling points are predicted according to the Freespace propagation (40 m ~ 63dB) and Okumura-Hata prediction (1 km ~ 127 dB). Each agent of the PSO represents the breakpoint in the work space. Position of this breakpoint changes the slope n of the model. Path losses of this model PLP are compared with measured data PLM, to find one with a minimal deviation value of the MSE.
    PL=10nlog10 d
    MSE =
    P a t h lo s s [d B ]

    Fig. 1 Multislope modeling principle with one optimised breakpoint and two coupling points.
    M u lti s lo p e L o g D is ta n c e p ro p a g a tio n m o d e l
    1 30 1 20 1 10 1 00 90 80 70

    PLM PLP 2
    N1

    60 10

    10

    D is t a n c e [m ]

    Two approaches are simulated, one with single optomized breakpoint ( seeL Fig. 1 ), and another with two breakpoints =32.4420log f 20log d ( see Fig. 2).
    fs 10 10

    Fig. 2 Multislope modeling principle with two optimised breakpoints and two coupling points.
    MSE [dB] Breakpoint distance of transmitter [m] 1.BP 41 135 41 122 2.BP 673 990 997 818 Breakpoint path loss level [dB] 1.BP 90 103 100 101 2.BP 108 110 108 111

    Conclusion
    The results of the modeling simulations are shown in table Tab.1 and Tab. 2. The deviation error is caused by fading effects. These affects signal propagation and causes a path loss level variation.

    MSE deviation error [dB] 15.5 15.4 15.4 15.3 15.3

    Breakpoint distance of transmitter [m] 192 137 947 115 106

    Breakpoint path loss level [dB] 99 95 120 91 90

    x 13.0 12.7 12.2 13.1

    Tab. 1 Model MSE deviations for one optimised breakpoint.

    Tab. 2 Model MSE deviations for two optimised breakpoint.

    Acknowledgements
    Thanks to prof. Dr. Ing. Z. Kolka. This paper was supported by the European Community's Seventh Framework program (FP7/2007-2013) under grant agreement no. 230126.

    IEEE Workshop Vsack Cb, 08/2011

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