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Add example notebooks for RF blocks
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‎docs/source/examples/rf_amplifier_compression.ipynb‎

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# RF Amplifier Compression\n",
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"\n",
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"Simulation of an RF amplifier with gain compression demonstrating the third-order nonlinearity model. We sweep the input power and observe the 1 dB compression point and gain saturation behavior."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Amplifier Model\n",
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"\n",
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"The `RFAmplifier` block implements a third-order polynomial nonlinearity:\n",
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"\n",
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"$$y(t) = a_1 x(t) + a_3 x^3(t)$$\n",
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"\n",
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"where $a_1$ is the linear voltage gain and $a_3$ is derived from the input-referred third-order intercept point (IIP3). The output is hard-clipped at the gain compression peak to prevent unphysical sign reversal."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"import matplotlib.pyplot as plt\n",
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"\n",
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"# Apply PathSim docs matplotlib style\n",
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"plt.style.use('../pathsim_docs.mplstyle')\n",
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"\n",
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"from pathsim import Simulation, Connection\n",
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"from pathsim.blocks import Source, Scope, Spectrum\n",
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"from pathsim.solvers import RKCK54\n",
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"\n",
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"from pathsim_rf import RFAmplifier"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## System Setup\n",
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"\n",
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"We create an amplifier with 20 dB gain and an IIP3 of +10 dBm, and drive it with a single-tone sinusoidal source at 1 GHz. We sweep the input amplitude to trace out the compression curve."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Amplifier parameters\n",
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"gain_dB = 20.0 # Small-signal gain [dB]\n",
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"IIP3_dBm = 10.0 # Input-referred IP3 [dBm]\n",
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"Z0 = 50.0 # Reference impedance [Ohm]\n",
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"f0 = 100.0 # Signal frequency [Hz] (scaled for simulation)\n",
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"\n",
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"# Sweep input power levels\n",
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"pin_dbm = np.arange(-30, 15, 1.0)\n",
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"pout_dbm = np.zeros_like(pin_dbm)\n",
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"\n",
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"for i, p_in in enumerate(pin_dbm):\n",
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"\n",
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" # Input amplitude from power in dBm\n",
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" p_watts = 10.0 ** (p_in / 10.0) * 1e-3\n",
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" v_peak = np.sqrt(2.0 * Z0 * p_watts)\n",
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"\n",
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" # Build simulation\n",
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" src = Source(func=lambda t, vp=v_peak: vp * np.sin(2 * np.pi * f0 * t))\n",
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" amp = RFAmplifier(gain=gain_dB, IIP3=IIP3_dBm, Z0=Z0)\n",
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" sco = Scope()\n",
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"\n",
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" sim = Simulation(\n",
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" [src, amp, sco],\n",
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" [Connection(src, amp), Connection(amp, sco)],\n",
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" dt=1 / (40 * f0),\n",
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" Solver=RKCK54\n",
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" )\n",
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"\n",
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" # Run for several cycles to reach steady state\n",
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" sim.run(10 / f0)\n",
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"\n",
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" # Read output and measure peak amplitude (last 2 cycles)\n",
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" t, [y] = sco.read()\n",
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" n_last = int(len(t) * 0.5)\n",
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" v_out_peak = np.max(np.abs(y[n_last:]))\n",
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"\n",
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" # Convert to output power in dBm\n",
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" p_out = v_out_peak ** 2 / (2 * Z0)\n",
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" pout_dbm[i] = 10 * np.log10(p_out / 1e-3) if p_out > 0 else -100"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Compression Curve\n",
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"\n",
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"The plot shows output power vs. input power. The dashed line represents ideal linear gain. The deviation from linearity shows the gain compression characteristic."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"fig, ax = plt.subplots(dpi=120)\n",
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"\n",
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"# Ideal linear response\n",
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"ax.plot(pin_dbm, pin_dbm + gain_dB, '--', label='Ideal (linear)', alpha=0.7)\n",
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"\n",
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"# Simulated response\n",
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"ax.plot(pin_dbm, pout_dbm, linewidth=2, label='Simulated')\n",
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"\n",
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"# Mark P1dB point\n",
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"p1db_in = IIP3_dBm - 9.6\n",
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"ax.axvline(x=p1db_in, color='grey', linestyle=':', alpha=0.5, label=f'P1dB = {p1db_in:.1f} dBm')\n",
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"\n",
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"ax.set_xlabel('Input Power [dBm]')\n",
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"ax.set_ylabel('Output Power [dBm]')\n",
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"ax.set_title('RF Amplifier Compression Curve')\n",
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"ax.legend()\n",
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"ax.grid(True, alpha=0.3)\n",
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"plt.tight_layout()\n",
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"plt.show()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Time-Domain Waveforms\n",
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"\n",
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"Let's compare the output waveform in the linear and compressed regimes to visualize the clipping behavior."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"fig, axes = plt.subplots(1, 2, figsize=(10, 4), dpi=120)\n",
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"\n",
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"for ax, p_in, title in zip(axes, [-20, 5], ['Linear regime (-20 dBm)', 'Compressed regime (+5 dBm)']):\n",
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" p_watts = 10.0 ** (p_in / 10.0) * 1e-3\n",
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" v_peak = np.sqrt(2.0 * Z0 * p_watts)\n",
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"\n",
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" src = Source(func=lambda t, vp=v_peak: vp * np.sin(2 * np.pi * f0 * t))\n",
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" amp = RFAmplifier(gain=gain_dB, IIP3=IIP3_dBm, Z0=Z0)\n",
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" sco_in = Scope(labels=['input'])\n",
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" sco_out = Scope(labels=['output'])\n",
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"\n",
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" sim = Simulation(\n",
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" [src, amp, sco_in, sco_out],\n",
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" [Connection(src, amp, sco_in), Connection(amp, sco_out)],\n",
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" dt=1 / (40 * f0),\n",
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" Solver=RKCK54\n",
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" )\n",
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"\n",
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" sim.run(3 / f0)\n",
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"\n",
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" t_in, [y_in] = sco_in.read()\n",
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" t_out, [y_out] = sco_out.read()\n",
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"\n",
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" ax.plot(np.array(t_in) * f0, y_in * 1000, label='Input')\n",
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" ax.plot(np.array(t_out) * f0, y_out * 1000, label='Output')\n",
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" ax.set_xlabel('Cycles')\n",
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" ax.set_ylabel('Voltage [mV]')\n",
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" ax.set_title(title)\n",
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" ax.legend()\n",
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" ax.grid(True, alpha=0.3)\n",
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"\n",
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"plt.tight_layout()\n",
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"plt.show()"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"name": "python",
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"version": "3.12.0"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}

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