Spring 2027

Communication Systems I

Communication Systems I covers amplitude, frequency, pulse, and pulse-code modulation, noise representation, signal-to-noise ratios, pulse shaping, timing recovery, carrier synchronization, equalization, sampling, quantization, and coding.

no offering record for this termCredits unavailable
Recorded instructors · Spring 2027 No instructors listed

Summary

1 / 7

Past student reviews · Paul Milenkovic

Students found the final project confusing, with one noting difficulty understanding the questions and experiments. Another described the project as confusing but manageable with office hours. Homework and exams were described as fine.

What you’ll be able to do

  • Characterize the energy and power of signals occurring in analog communication systems using the theory of inner products and properties of the Fourier series and the Fourier transform

  • Apply the theory of the narrowband representation of signals to the modulation and recovery of signals using the linear analog modulation techniques

  • Design phase and frequency modulation systems based on parameters of non-linear modulation

  • Apply random process theory to characterize the behavior of analog modulation systems in the presence of interference

  • Implement analog communication systems in discrete-time (software-defined radio)

  • Design and conduct experiments to confirm the performance of analog modulation systems in the presence of interfering noise

Source: UW Guide

Grade history

↗
average GPA
letter grades
A
AB
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All recorded terms · compare terms & instructors

Prerequisites

Course map

(E C E 203 or 330), graduate/professional standing, or member of Engineering Guest Students

    • take one
    • graduate/professional standing
    • member of Engineering Guest Students
    take one
ECE 436

This is a best-effort interpretation; check the catalog requirements above.

Prerequisite text tree
  • Any of
    • Any of
    • graduate/professional standing
    • member of Engineering Guest Students

Professors

Spring 2027

No instructors recorded for this selection.

Historical instructors & teaching patterns

PAUL MILENKOVIC is recorded teaching in Fall 2011, Fall 2012, Fall 2018, Fall 2019, Fall 2020, Fall 2021, Fall 2022, Fall 2023, Fall 2024, Fall 2025. Recorded history may be incomplete and does not establish a future schedule.

Recorded history may be incomplete and does not establish a future schedule.

Calendar & sections

Spring 2027

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SectionModeEnrolled / capacityWaitlist

Times are Central. Select a meeting for details; export includes recorded dates for the selected sections.

Meeting source records
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Student experience

the class

Past student reviews · Paul Milenkovic

The course involved projects using a Java DSP program developed by the instructor. Student opinions varied, with some finding the teaching inspiring and others criticizing the outdated software and lack of learning.

Recent recorded grades — Fall 2023: 3.59 GPA, 68.8% A/AB (n=16 letter grades); Fall 2024: 3.50 GPA, 81.2% A/AB (n=32 letter grades); Fall 2025: 3.65 GPA, 83.3% A/AB (n=30 letter grades).

difficulty & workload

Past student reviews · Paul Milenkovic

Students found the final project confusing, with one noting difficulty understanding the questions and experiments. Another described the project as confusing but manageable with office hours. Homework and exams were described as fine.

Past student reviews · Paul Milenkovic

The instructor was accessible by email and willing to answer questions. Lectures were recorded and notes posted, though some students found the lecture style dry or disorganized.

Topics

  • Amplitude, frequency, pulse, and pulse-code modulation
  • Narrow-band noise representation and signal-to-noise ratios
  • Pulse shaping, timing recovery, carrier synchronization, and equalization
  • Sampling, quantization, and coding
  • Signal energy, power, inner products, Fourier series, and Fourier transform
  • Discrete-time implementation and software-defined radio

Skills

  • Characterize signal energy and power using inner products and Fourier analysis
  • Apply narrowband signal representation for linear analog modulation and recovery
  • Design phase and frequency modulation systems
  • Apply random process theory to analyze modulation systems with interference
  • Implement analog communication systems in discrete-time software-defined radio
  • Design and conduct experiments to confirm modulation system performance under noise

Grades

Latest available · Fall 2025— not enough history to project Spring 2027.

average GPA
A / AB grades
letter grades
Instructor

Grade distribution · % of letter grades

A
AB
B
BC
C
D
F

Grades over time

Through Fall 2025

More grade details Grade mix, volume & source data

Where this course fits relative to

Latest available grades · Fall 2025 · all course levels

GPA

Higher than % of other courses in this group.

Course GPAs · red marks this course’s range

letter grades

More recorded grades than % of other courses in this group.

Typical course in this group: letter grades.

About this comparison

1316 courses over the same term, each with at least 30 recorded letter grades. Cross-listed courses count once. GPA is not a measure of difficulty or teaching quality. The typical course is the median by recorded grade count; tied values are not counted as lower. Grade counts describe course scale, not unique students or typical section size.

Descriptions compare GPA with this group’s average: at least 0.20 higher or lower; otherwise close to average. Section size uses median recorded enrollment: small up to 30, mid-sized 31–99, large 100+. Lectures and discussion/lab sections are described separately.

Sources & history

UW–Madison

Catalog & offerings

Descriptions, prerequisites, and recorded course offerings.

Catalog observation history

Observations at scan time; dates do not imply when a catalog change took effect.

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Selected offering source records

No offering records for the selected term.

Raw records 
[]
Rate My Professors

Student reviews

Original comments behind the course and instructor summaries.

Read original reviews
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Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

Explore recorded grades
Dataset & model

Recorded 2026-10-14

View the dataset on Hugging Face
Model outputs & technical records
Qwen/Qwen3.8-27B
LLM outputs across runs
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Full model traces

Recorded model configuration, reasoning, and tool conversations.

Download part 1
Model & dataset provenance 
{
  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "f1c88d39e1b755956819c440cb363c3672d7c9e0de949b98109ab329fc42ebf4",
  "requirements_status": "valid",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}