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 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Chapter 3: Radio Propagation and Propagation Path-Loss Models"
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Example 3.1, Page 51"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import math\n",
      "\n",
      "#Variable declaration\n",
      "hb=100; #in feets(height of BS antenna)\n",
      "hm=5;  # in feets(height of mobile antenna)\n",
      "f=881.52;#in MHz\n",
      "lamda=1.116;  #in feet\n",
      "d=5000;  #in feet\n",
      "Gb=10**0.8;  #8dB(BS antenna gain)\n",
      "Gm=10**0;   # 0dB (Mobile antenna gain)\n",
      "\n",
      "#Calculations&Results\n",
      "free_atten=(4*math.pi*d/lamda)**2*(Gb*Gm)**-1;\n",
      "y=round(10*math.log10(free_atten));\n",
      "print 'Free space attenuation is %d dB \\n'%y\n",
      "reflect_atten= (d**4/(hb*hm)**2)*(Gb*Gm)**-1;\n",
      "x=round(10*math.log10(reflect_atten));\n",
      "print 'Reflecting surface attenuation is %d dB \\n '%x"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Free space attenuation is 87 dB \n",
        "\n",
        "Reflecting surface attenuation is 86 dB \n",
        " \n"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Example 3.2, Page 52"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import math\n",
      "\n",
      "#Variable declaration\n",
      "d=8000; #Distance between base station and mobile station\n",
      "f=1.5*10**9;#in Hz \n",
      "lamda=0.2;  #in metres\n",
      "Pt=10; #BS transmitted power in watts\n",
      "Lo=8;   #Total system losses in dB\n",
      "Nf=5;    #Mobile receiver noise figure in dB\n",
      "T=290;   #temperature in degree kelvin\n",
      "BW=1.25*10**6; #in Hz\n",
      "Gb=8;  #in dB\n",
      "Gm=0;   #in dB\n",
      "Hb=30;  #in metres\n",
      "Hm=3.;   #in metres\n",
      "B=1.38*10**-23; #Boltzmann's constant\n",
      "\n",
      "#Calculations&Results\n",
      "Free_Lp=20*math.log10(Hm*Hb/d**2);\n",
      "Pr=Free_Lp-Lo+Gm+Gb+Pt;  #in dBW\n",
      "Te=T*(3.162-1);\n",
      "Pn=B*(Te+T)*BW;\n",
      "print 'Received signal power is %d dBW \\n'%(10*math.log10(Pn))\n",
      "SNR=Pr-10*math.log10(Pn);\n",
      "print 'SNR ratio is %d dB \\n'%(round(SNR))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Received signal power is -138 dBW \n",
        "\n",
        "SNR ratio is 31 dB \n",
        "\n"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Example 3.3, Page 58"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import math\n",
      "\n",
      "#Variable declaration\n",
      "d=3*1000;#in metres\n",
      "Y=4;# path loss exponent\n",
      "Pt=4;  #Transmitted power in watts\n",
      "f=1800*10**6;#in Hz\n",
      "Shadow=10.5;  #in dB\n",
      "d0=100.;#in metres\n",
      "P0=-32;   #in dBm\n",
      "\n",
      "#Calculations&Results\n",
      "print \"Using equation 3.11 and including shadow effect we get\"\n",
      "Pr=P0+10*Y*math.log10(d0/d)+Shadow;\n",
      "print 'Received power is %.1f dBm \\n'%Pr\n",
      "path_loss=10*math.log10(Pt*1000)-Pr;\n",
      "print 'Allowable path loss is %.1f dB \\n'%path_loss"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using equation 3.11 and including shadow effect we get\n",
        "Received power is -80.6 dBm \n",
        "\n",
        "Allowable path loss is 116.6 dB \n",
        "\n"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Example 3.4, Page 58"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#Variable declaration\n",
      "shadow=10.; #in dB\n",
      "Lp=150;  #in dB\n",
      "\n",
      "#Calculations&Results\n",
      "print \"Using equation given in Problem i.e Lp=133.2+40*math.log(d) we get,\"\n",
      "d=10**((Lp-10-133.2)/40);\n",
      "print \"Separation between transmitter and receiver as %.2f km\"%d"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using equation given in Problem i.e Lp=133.2+40*math.log(d) we get,\n",
        "Separation between transmitter and receiver as 1.48 km\n"
       ]
      }
     ],
     "prompt_number": 10
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Example 3.5, Page 61"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import math\n",
      "\n",
      "#Variable declaration\n",
      "v=60*0.44704;  #.. mph to mps\n",
      "fc=860*10**6;#in Hz\n",
      "td=2*10**-6; #RMS delay spread in sec\n",
      "c=3.*10**8;# speed of light in m/sec\n",
      "Rs=19200.; #Coded symbol rate in bps\n",
      "\n",
      "#Calculations&Results\n",
      "lamda=c/fc;\n",
      "fm=v/lamda; #Maximum doppler shift\n",
      "tc=1/(2*math.pi*fm);#Channel coherence time\n",
      "print 'Channel coherence time is %.4f sec \\n'%tc\n",
      "ts=1/Rs; #symbol interval\n",
      "print 'Symbol interval is %d microsec \\n'%(ts*10**6);\n",
      "print \"As the symbol interval is much smaller compared to the channel coherence time. So, Symbol distortion is minimal and fading is slow.\";\n",
      "print \"\";\n",
      "Bc=1/(2*math.pi*td);\n",
      "print 'Coherence Bandwidth is %.2f kHz \\n'%(Bc/1000)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Channel coherence time is 0.0021 sec \n",
        "\n",
        "Symbol interval is 52 microsec \n",
        "\n",
        "As the symbol interval is much smaller compared to the channel coherence time. So, Symbol distortion is minimal and fading is slow.\n",
        "\n",
        "Coherence Bandwidth is 79.58 kHz \n",
        "\n"
       ]
      }
     ],
     "prompt_number": 11
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Example 3.6, Page 65"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import math\n",
      "\n",
      "#Variable declaration\n",
      "p=1;# re\ufb02ection coef\ufb01cient of ground \n",
      "c=3.*10**8;# velocity of light in free space(m/sec)\n",
      "e=2.71828;#Euler's number\n",
      "fm=20;  #in Hz\n",
      "fc=900*10**6; #carrier frequency in Hz\n",
      "\n",
      "#Calculations&Results\n",
      "Nr=math.sqrt(2*math.pi)*fm*p*e**-(p**2);\n",
      "print 'NO of fades per second are %.2f  \\n'%Nr\n",
      "Afd=e**-(p**2)/(p*fm*math.sqrt(2*math.pi));\n",
      "print 'Average fade duration is %.4f sec \\n '%Afd\n",
      "v=fm*c/fc;\n",
      "print 'Maximum velocity of mobile is %.2f m/sec = %d Km/hour \\n'%(v,v*18/5);"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "NO of fades per second are 18.44  \n",
        "\n",
        "Average fade duration is 0.0073 sec \n",
        " \n",
        "Maximum velocity of mobile is 6.67 m/sec = 24 Km/hour \n",
        "\n"
       ]
      }
     ],
     "prompt_number": 13
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Example 3.7, Page 70"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import math\n",
      "import matplotlib\n",
      "import matplotlib.pyplot as plt\n",
      "import numpy as np\n",
      "%matplotlib inline\n",
      "\n",
      "#Variable declaration\n",
      "d=np.array([1, 2, 3, 4, 5]);  #in km\n",
      "hb=30; #Height of BS antenna in metres\n",
      "hm=2;# height of mobile antenna in matres\n",
      "fc=900;#carrier frequency in MHz\n",
      "W=15;  #street width(m)\n",
      "b=30;  # distance between building along radio path (m) \n",
      "phi=90; # incident angle relative to the street\n",
      "hr=30; #in m\n",
      "\n",
      "#Calculations\n",
      "dellhm=hr-hm;\n",
      "#L50=Lf+Lrts+Lms\n",
      "\n",
      "# By COST 231 model\n",
      "Lf=32.4+20*np.log10(d)+20*np.log10(fc);\n",
      "L0=4-0.114*(phi-55);\n",
      "Lrts=-16.9-10*math.log10(W)+10*math.log10(fc)+20*math.log10(dellhm)+L0;\n",
      "Lbsh=-18*math.log10(11);\n",
      "ka=54-0.8*hb;\n",
      "dellhb=hb-hr;\n",
      "kd=18-15*dellhb/dellhm;\n",
      "kf=4+0.7*(fc/925-1);\n",
      "Lms=Lbsh+ka+kd*np.log10(d)+kf*np.log10(fc)-9*np.log10(b);\n",
      "L50=np.array([0, 0, 0, 0, 0])\n",
      "L50=Lf+Lrts+Lms;\n",
      "\n",
      "#Okumura/Hata model\n",
      "ahm=(1.1*math.log10(fc)-0.7)*hm-(1.56*math.log10(fc)-0.8);\n",
      "L_50=69.55+26.16*np.log10(fc)+(44.9-6.55*np.log10(hb))*np.log10(d)-13.82*np.log10(hb)-ahm;\n",
      "L_50 = np.array(L_50)\n",
      "\n",
      "#Results\n",
      "fig,ax1 = plt.subplots()\n",
      "ax1.plot(d,L_50,'b-')\n",
      "ax1.set_xlabel('Distance from transmitter(in km)')\n",
      "ax1.set_ylabel('Path loss (in dB)')\n",
      "ax2 = ax1.twinx()\n",
      "ax2.plot(d,L50,'r')\n",
      "ax1.legend(['COST 231 model'],loc=0)\n",
      "ax2.legend(['HATA model'],loc=0)\n",
      "ax1.grid()\n",
      "plt.show()\n",
      "print \"L50 values by Cost 231 model\"\n",
      "print '%.2f  %.2f  %.2f  %.2f  %.2f \\n '%(L50[0],L50[1],L50[2],L50[3],L50[4]);\n",
      "print \"L50 values bu Okumura/Hata model\"\n",
      "print '%.2f  %.2f  %.2f  %.2f  %.2f \\n '%(L_50[0],L_50[1],L_50[2],L_50[3],L_50[4]);\n",
      "print \"The results from the plot of two models shows that the calculated path loss with the COST 231 model is higher than the value obtained by the Okumura/Hata model.\"\n",
      "\n",
      "#Answers vary due to built-in functions of Python used"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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+V9XpmthY+PRTqF8fXn1VCm6lZlSc6jx6VIIylSpB8+YS7V+8WKzU228HxKjo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\nKIqiKIqiKIqiZEz+H0C1ZRMhMDC/AAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0xb55925ac>"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "L50 values by Cost 231 model\n",
        "129.03  140.47  147.16  151.91  155.59 \n",
        " \n",
        "L50 values bu Okumura/Hata model\n",
        "125.13  135.73  141.93  146.34  149.75 \n",
        " \n",
        "The results from the plot of two models shows that the calculated path loss with the COST 231 model is higher than the value obtained by the Okumura/Hata model.\n"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Example 3.8, Page 76"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import math\n",
      "\n",
      "#Variable declaration\n",
      "SNRmin=12;#in dB\n",
      "n=3; #No of floors\n",
      "Backgroundnoise=-115; #dBm\n",
      "pt=100  #in dBm\n",
      "\n",
      "#Calculations\n",
      "pt_db=10*math.log10(pt);\n",
      "Sr=Backgroundnoise+SNRmin; #receiver sensitivity\n",
      "Lpmax=pt_db-Sr;\n",
      "#Refering table 3.4\n",
      "Lp_d0=38;  #ref path loss at the first meter(dB)\n",
      "Lf=15+4*(n-1); #signal attenuation through n floors\n",
      "y=3; #path loss exponent\n",
      "X=10; #Shadowing effect(dB)\n",
      "d=10**((Lpmax-Lp_d0-Lf-X)/30); #max allowable path loss\n",
      "\n",
      "#Result\n",
      "print 'Coverage radius of an access point = %d m \\n'%(round(d))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Coverage radius of an access point = 54 m \n",
        "\n"
       ]
      }
     ],
     "prompt_number": 22
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Example 3.9, Page 77"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import math\n",
      "\n",
      "#Variable declaration\n",
      "SSmean=-100; #signal strength(dBm)\n",
      "Sr=-110; #receiver sensitivity(dBm)\n",
      "sd=10;  #standard deviation(dB)\n",
      "\n",
      "#Calculations\n",
      "P_Smin=(0.5-0.5*math.erf((Sr-SSmean)/(math.sqrt(2)*sd)));\n",
      "\n",
      "#Result\n",
      "print 'probability of exceeding signal beyond the receiver sensitivity is %.2f \\n'%(P_Smin)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "probability of exceeding signal beyond the receiver sensitivity is 0.84 \n",
        "\n"
       ]
      }
     ],
     "prompt_number": 24
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Example 3.10, Page 81"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import math\n",
      "\n",
      "#Variable declaration\n",
      "Lp=140; # path losses in dB \n",
      "k=1.38*10**-23; # Boltzmann\u2019s constant (W/Kelvin-Hz)\n",
      "k_db=10*math.log10(k);\n",
      "f=900;#in MHz\n",
      "Gt=8; #transmitting antenna gain(dB)\n",
      "Gr=0; #receiver antenna gain(dB)\n",
      "Ag=24;#gain of receiver ampli\ufb01er in dB \n",
      "Fmargin=8;#Fade margin(dB)\n",
      "Nf=6;#Noise figure(dB)\n",
      "L0=20; #\u0002 other losses in dB\n",
      "Lf=12; # antenna feed line loss in dB \n",
      "T=24.6;#Temperature expressed in dB\n",
      "R=39.8; #\u0002 data rate in dB \n",
      "M=8;  #overall link margin(dB)\n",
      "Eb_No=10;#dB\n",
      "\n",
      "#Calculations\n",
      "#From equation  (3.54)\n",
      "pt_db=M-Gt-Gr-Ag+ Nf + T+ k_db+ Lp+ Lf+ L0 + Fmargin+ R+ Eb_No;\n",
      "\n",
      "Pt=10**(pt_db/10);  #dB into normal number\n",
      "\n",
      "#Result\n",
      "print 'Total transmitted power is %d Watts \\n'%Pt"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Total transmitted power is 6 Watts \n",
        "\n"
       ]
      }
     ],
     "prompt_number": 25
    }
   ],
   "metadata": {}
  }
 ]
}