Exercises

ex-sp-ch16-01

Easy

Create a box plot of BER values for 3 modulation schemes (BPSK, QPSK, 16-QAM) using Seaborn. Generate 100 samples per modulation with appropriate noise levels.

Show Hint

Use sns.boxplot(data=df, x="modulation", y="ber").

Solution

Implementation

import numpy as np, pandas as pd, seaborn as sns
import matplotlib.pyplot as plt

rng = np.random.default_rng(42)
records = []
for mod, base in [('BPSK', -4), ('QPSK', -3), ('16-QAM', -2)]:
    bers = 10**(base + 0.3 * rng.standard_normal(100))
    for b in bers:
        records.append({'modulation': mod, 'ber': b})
df = pd.DataFrame(records)

fig, ax = plt.subplots(figsize=(6, 4))
sns.boxplot(data=df, x='modulation', y='ber', ax=ax)
ax.set_yscale('log')
ax.set_title('BER by Modulation')

ex-sp-ch16-02

Easy

Create a correlation heatmap of a 5-column simulation result DataFrame using sns.heatmap with annotations.

ex-sp-ch16-03

Easy

Create an interactive scatter plot with Plotly Express showing throughput vs. SNR, colored by modulation type.

ex-sp-ch16-04

Easy

Animate a traveling sine wave using FuncAnimation and save as GIF.

ex-sp-ch16-05

Easy

Create a polar plot of a dipole antenna pattern $G(\theta) = \cos^2(\theta)$ in dB scale.

ex-sp-ch16-06

Medium

Create a violin plot comparing throughput distributions across 3 scheduling algorithms and 2 channel conditions, using hue for the channel type.

ex-sp-ch16-07

Medium

Build a Plotly dashboard with two linked plots: a scatter plot of users and a histogram of their BER values. Selecting points in the scatter should filter the histogram.

ex-sp-ch16-08

Medium

Animate gradient descent on the function $f(x, y) = x^2 + 10y^2$ showing contours and the optimizer path. Compare standard GD with momentum.

ex-sp-ch16-09

Medium

Generate an eye diagram for 4-PAM signaling with a root-raised cosine pulse at rolloff $\beta = 0.35$ and SNR = 20 dB.

ex-sp-ch16-10

Medium

Create a waterfall spectrum plot showing 30 seconds of spectrum monitoring data with frequency-hopping interference.

ex-sp-ch16-11

Hard

Implement a Smith chart from scratch using Matplotlib circles for constant-resistance and constant-reactance lines. Plot the impedance trajectory of a matching network.

ex-sp-ch16-12

Hard

Create an animated constellation diagram showing the effect of carrier frequency offset: the constellation rotates, then a PLL corrects it. Show both raw and corrected constellations.

ex-sp-ch16-13

Hard

Build a faceted plot (Seaborn FacetGrid) showing BER curves across 4 channel models and 3 coding rates, with shared y-axis (log scale).

ex-sp-ch16-14

Challenge

Build a complete signal analysis dashboard in Plotly Dash that takes a recorded IQ file and shows: spectrogram, constellation, eye diagram, and BER estimate with interactive parameter tuning.

ex-sp-ch16-15

Challenge

Create an animated waterfall spectrum showing a 5G NR frame structure with different numerologies (15 kHz, 30 kHz, 60 kHz subcarrier spacing) occupying different bandwidth parts.

Chapter Summary References & Further Reading