Exp4_AM_QAM_FDM.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "c0j2HEwrwlfL"
   },
   "source": [
    "# AM QAM FDM\n",
    "\n",
    "## Objective\n",
    "\n",
    "This experiment aims:\n",
    "\n",
    "1. To study and practice the generation and demodulation of AM wave.\n",
    "\n",
    "2. To study and practice the generation and demodulation of QAM wave.\n",
    "\n",
    "3. To study and practice the FDM technique.\n",
    "\n",
    "\n",
    "## Introduction\n",
    "\n",
    "In this experiment, you will practice AM, QAM and FDM techniqus.\n",
    "Please refer to the textbook and lecture notes for theory part.\n",
    "\n",
    "## Procedure\n",
    "\n",
    "### Amplitude Modulation: Generation and Detection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "6WK7_LGFwlfc",
    "outputId": "07adafb5-5cd1-48ff-8dbb-9f3d9532cbad"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "clear all;\n",
    "\n",
    "fs   = 1e2;               % sampling frequency\n",
    "t    =  0 : 1/fs : 1;     % time vector\n",
    "f    = -fs/2 : 1 : fs/2;  % frequency vector\n",
    "fc   = 10;                % carrier frequency\n",
    "fm   = 2;                 % message frequency\n",
    "m    = cos(2*pi*fm*t);    % message signal\n",
    "c    = cos(2*pi*fc*t);    % carrier signal\n",
    "u    = 0.8;               % modulation index\n",
    "dsb  = u*m .* c;          % DSB-SC signal\n",
    "am   = dsb + c;           % AM signal\n",
    "AM   = sig_spec(am);\n",
    "\n",
    "% Demodulation using envelope detection\n",
    "% envelope detection can be implemented by squaring and lowpass filtering\n",
    "amsq   = am .* am;\n",
    "pkg load signal;\n",
    "[b, a] = butter(2,2*fm/(fs/2));\n",
    "mr1     = filter(b, a, amsq);\n",
    "\n",
    "% envelope detection also can be implemented using Hilbert transfom\n",
    "mr2     = abs(hilbert(am));\n",
    "\n",
    "\n",
    "figure();\n",
    "subplot(311); plot(t,am); grid on; title('AM and Message in Time Domain')\n",
    "hold on;\n",
    "subplot(311); plot(t,u*m+1); grid on;hold on;\n",
    "subplot(311); plot(t,-u*m-1); grid on;\n",
    "subplot(312); plot(f,AM); grid on; title('AM in Frequency Domain')\n",
    "subplot(313); plot(t,mr1); grid on; title('Received Signal')\n",
    "hold on;\n",
    "subplot(313); plot(t,mr2);\n",
    "hold on;\n",
    "subplot(313); plot(t,m); grid on;\n",
    "legend('mr1','mr2','m')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "LljSs-eZwlfh"
   },
   "source": [
    "---\n",
    "\n",
    "### Modulation Power Efficiency  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "twfVYRUKwlfi",
    "outputId": "ede89565-89fb-4006-cfd2-8b136928267c"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ps =  0.16640\n",
      "Pt =  0.69240\n",
      "eta =  0.24032\n"
     ]
    }
   ],
   "source": [
    "% Power efficiency of modulation\n",
    "% eta = Psidebands / (Pcarrier + Psidebands)\n",
    "Ps  = sum(dsb .* dsb) / fs\n",
    "Pt  = sum(am .* am) / fs\n",
    "eta = Ps / Pt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "8UKbogSqwlfk"
   },
   "source": [
    "Discussion\n",
    "\n",
    "* Use different values of modulation index and comment on its affect upon power efficiency and detection capability\n",
    "\n",
    "---\n",
    "\n",
    "### QAM: Generation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "eSCs8H9hwlfl",
    "outputId": "339e98f6-d202-4a9a-85aa-2d2de130d4e8"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fm1 = 2;                    % first message frequency\n",
    "fm2 = 3;                    % second message frequency\n",
    "c2  = cos(2*pi*fc*t-pi/2);  % second carrier signal\n",
    "m1  = cos(2*pi*fm1*t);      % first message signal\n",
    "m2  = cos(2*pi*fm2*t);      % second message signal\n",
    "qam = m1.*c + m2.*c2;       % QAM signal\n",
    "QAM = sig_spec(qam);\n",
    "\n",
    "figure();\n",
    "subplot(211); plot(t,qam); grid on; title('QAM and two Messages in Time Domain')\n",
    "hold on;\n",
    "subplot(211); plot(t,m1); grid on;hold on;\n",
    "subplot(211); plot(t,m2); grid on;\n",
    "legend('QAM','m1','m2')\n",
    "subplot(212); plot(f,QAM); grid on; title('QAM in Frequency Domain')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "RdF1FOCowlfm"
   },
   "source": [
    "---\n",
    "\n",
    "### QAM: Receiver"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "1zQkS3BCwlfm",
    "outputId": "26bfc90b-6eca-41f9-c102-96f5f908ef1a"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "lo1  = cos(2*pi*fc*t);\n",
    "lo2  = cos(2*pi*fc*t-pi/2);\n",
    "r1   = lo1.*qam;\n",
    "r2   = lo2.*qam;\n",
    "R1   = sig_spec(r1);\n",
    "R2   = sig_spec(r2);\n",
    "\n",
    "pkg load signal;\n",
    "[b, a] = butter(2,fm2/(fs/2));\n",
    "mr1    = filter(b,a,r1);\n",
    "mr2    = filter(b,a,r2);\n",
    "Mr1    = sig_spec(mr1);\n",
    "Mr2    = sig_spec(mr2);\n",
    "\n",
    "figure();\n",
    "subplot(211); plot(t,mr1); grid on; title('First Demodulated Signal')\n",
    "hold on;\n",
    "subplot(211); plot(t,m1); grid on;\n",
    "legend('mr1','m1')\n",
    "subplot(212); plot(t,mr2); grid on; title('Second Demodulated Signal')\n",
    "hold on;\n",
    "subplot(212); plot(t,m2); grid on;\n",
    "legend('mr2','m2')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "C5zZ-9uujGWw"
   },
   "source": [
    "Discussion\n",
    "\n",
    "* Try to insert a phase error at the demodulation and comment on its affect upon detected signal.\n",
    "\n",
    "* What happen if the phase difference between demodulator and carrier was $\\pi/2$.\n",
    "\n",
    "---\n",
    "\n",
    "### FDM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "Pk0jYO5Owlfp",
    "outputId": "3f43754d-feea-4475-9f29-b9dc66a35dde"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "clear all;\n",
    "\n",
    "fs   = 4e2;               % sampling frequency\n",
    "t    =  0 : 1/fs : 1;     % time vector\n",
    "f    = -fs/2 : 1 : fs/2;  % frequency vector\n",
    "fc1  = 80;                % first carrier frequency\n",
    "fm1  = 5;                 % first message frequency\n",
    "fc2  = 120;               % second carrier frequency\n",
    "fm2  = 7;                 % second message frequency\n",
    "m1   = cos(2*pi*fm1*t);   % first message signal\n",
    "m2   = cos(2*pi*fm2*t);   % second message signal\n",
    "c1   = cos(2*pi*fc1*t);   % first carrier signal\n",
    "c2   = cos(2*pi*fc2*t);   % second carrier signal\n",
    "fdm  = m1.*c1 + m2.*c2;   % FDM of two DSB-SC signals\n",
    "FDM  = sig_spec(fdm);     % Spectrum of FDM of two DSB-SC signals \n",
    "\n",
    "pkg load signal;\n",
    "[b1, a1] = butter(2,[fc1-10 fc1+10]/(fs/2)); % first bandpass filter\n",
    "[b2, a2] = butter(2,[fc2-10 fc2+10]/(fs/2)); % second bandpass filter\n",
    "\n",
    "r1       = filter(b1, a1, fdm); % extracting the first signal\n",
    "r2       = filter(b2, a2, fdm); % extracting the second signal\n",
    "\n",
    "% Coherent detection of two DSB-SC signals\n",
    "dr1      = r1.*c1;\n",
    "dr2      = r2.*c2;\n",
    "\n",
    "[b, a] = butter(2,2*fm1/(fs/2));\n",
    "mr1       = filter(b, a, dr1);\n",
    "mr2       = filter(b, a, dr2);\n",
    "\n",
    "\n",
    "figure();\n",
    "subplot(221); plot(t,fdm); grid on; title('FDM in Time Domain')\n",
    "subplot(222); plot(f,FDM); grid on; title('FDM in Frequency Domain')\n",
    "subplot(223); plot(t,mr1); grid on; title('First Received Signal')\n",
    "hold on;\n",
    "subplot(223); plot(t,m1);\n",
    "legend('mr1','m1')\n",
    "subplot(224); plot(t,mr2); grid on; title('Second Received Signal')\n",
    "hold on;\n",
    "subplot(224); plot(t,m2); grid on;\n",
    "legend('mr2','m2')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "AFc2SEZKrXZR"
   },
   "source": [
    "Discussion\n",
    "\n",
    "* Try to make carriers as much as closer in frequency without interfering the modulating signals with each other.\n",
    "\n",
    "* Comment on the guard band requirement versus the filter order."
   ]
  }
 ],
 "metadata": {
  "colab": {
   "name": "Exp4_AM_QAM_FDM.ipynb",
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Octave",
   "language": "octave",
   "name": "octave"
  },
  "language_info": {
   "file_extension": ".m",
   "help_links": [
    {
     "text": "GNU Octave",
     "url": "https://www.gnu.org/software/octave/support.html"
    },
    {
     "text": "Octave Kernel",
     "url": "https://github.com/Calysto/octave_kernel"
    },
    {
     "text": "MetaKernel Magics",
     "url": "https://metakernel.readthedocs.io/en/latest/source/README.html"
    }
   ],
   "mimetype": "text/x-octave",
   "name": "octave",
   "version": "4.2.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}