Skip to main content

Pulse Width Modulation (PWM)


Pulse-width modulation (PWM), or pulse-duration modulation (PDM), is a method of controlling the average power delivered by an electrical signal.

 






Fig: An example of PWM in an idealized inductor driven by a blue line voltage source modulated as a series of sawtooth pulses, resulting in a red line current in the inductor. 

 

Generating a PWM Signal

The simplest way to generate a PWM signal is the intersection method, which requires only a sawtooth or a triangle waveform (easily generated using a simple oscillator) and a comparator. When the value of the reference signal is more than the modulation waveform, the PWM signal (magenta) is in the high state; otherwise, it is in the low state. 


 

 

Duty cycle

A low duty cycle equates to low power because the power is off for most of the time; the word duty cycle reflects the ratio of "on" time to the regular interval or "period" of time. The duty cycle is measured in percent, with 100% representing full on. A digital signal has a duty cycle of 50% and looks like a "square" wave when it is on 50% of the time and off the other 50%. A digital signal has a duty cycle of greater than 50% when it spends more time in the on state than the off state. A digital signal has a duty cycle of 50% when it alternates between the on and off states more often than not.

 

 

 

 



Mathematical Formulation of pulse-width waveform

Pulse-width modulation uses a rectangular pulse wave whose pulse width is modulated resulting in the variation of the average value of the waveform. If we consider a pulse waveform f(t), with period T, low-value ymin, a high-value ymax, and a duty cycle D, the average value of the waveform is given by

 

Average Value of the Signal and PWM Generation

The average value of the signal is given by:

\[ \bar{y} = \frac{1}{T} \int_0^T f(t) \, dt \] As \(f(t)\) is a pulse wave, its value is \(y_\text{max}\) for \(0 < t < D \cdot T\) and \(y_\text{min}\) for \(D \cdot T < t < T\). The above expression then becomes:

\[ \bar{y} = \frac{1}{T} \int_0^{D \cdot T} y_\text{max} \, dt + \frac{1}{T} \int_{D \cdot T}^T y_\text{min} \, dt \] \[ = \frac{1}{T} \left(D \cdot T \cdot y_\text{max} + T(1 - D) \cdot y_\text{min}\right) \] \[ = D \cdot y_\text{max} + (1 - D) \cdot y_\text{min} \]

From this, the average value of the signal (\(\bar{y}\)) is directly dependent on the duty cycle \(D\). 

  

Further Reading



Contact Us

Name

Email *

Message *

Popular Posts

MATLAB Code for Constellation Diagram of QAM configurations such as 4, 8, 16, 32, 64, 128, and 256-QAM

📘 Overview of QAM 🧮 4-QAM MATLAB 🧮 16-QAM MATLAB 🚀 Online Simulator 📂 Other Topics on Constellation Diagrams... ▼ 🧮 MATLAB Code for 4-QAM 🧮 MATLAB Code for 16-QAM 🧮 MATLAB Code for m-ary QAM 🧮 Simulator for m-ary PSK 🧮 Simulator for m-ary QAM 🧮 Overview of Energy per Bit (Eb / N0) 🧮 Simulator for ASK, FSK, and PSK Overview of QAM One of the best-performing modulation techniques is QAM [↗] . Here, we modulate the symbols by varying the carrier signal's amplitude and phase in response to the variation in the message signal (or voltage variation). So, we may say that QAM is a combination of phase and amplitude modulation. Additionally, it performs better than ASK or PSK [↗] . In fact, any constellation for any type of modulatio...

UGC NET Electronic Science Previous Year Question Papers with Solutions

Download Papers and Solutions Exam Pattern Preparation Tips FAQs More Home / Engineering & Other Exams / UGC NET 2026 PYQ 📊 Exam Highlights: Electronic Science (88) Feature Details Junior Research Fellowship (JRF) ₹37,000 + HRA per month Eligibility M.Sc/M.Tech in Electronics (55%) Validity of Certificate JRF (3 Years) | Lectureship (Lifetime) 📥 Download UGC NET Electronics PDFs Complete collection of previous year question papers, answer keys and explanations for Subject Code 88. Start Downloading 📂 View All Question Papers June 2026 - Question Paper Download PDF June 202...

Flat vs Frequency Selective Online Simulator

Flat vs Frequency Selective Online Simulator Channel Type Without Fading Flat Fading Multipaths Nakagami m SNR(dB) Run Simulation Input Signal Signal After Fading Constellation Diagram BER vs SNR Explore Advanced Flat vs Frequency-Selective Fading Simulator Want to see these equations in action? Visualize it. Launch Simulator Tool Flat Fading and Frequency-Selective Fading Effects of Multipath Components and the Nakagami-m Parameter 1. Flat Fading Flat fading occurs when the signal bandwidth is smaller than the channel's coherence bandwidth, meaning that all frequency components of the transmitted signal experience approximately the same fading. It is typically associated with narrowband signals, where the multipath delay spread is small relative to the symbol duration. ...

Orthogonal Time Frequency Space (OTFS) (with MATLAB)

In OTFS (Orthogonal Time Frequency Space) modulation — a scheme designed for high-Doppler and time-varying wireless channels — the terms ISFFT and SFFT are key mathematical transformations used to move between different representation domains. Figure: OTFS block diagram 1. ISFFT — Inverse Symplectic Finite Fourier Transform Purpose: Transforms data symbols from the delay-Doppler domain to the time-frequency domain . \[ X[n, m] = \frac{1}{\sqrt{NM}} \sum_{k=0}^{N-1} \sum_{l=0}^{M-1} x[k, l] \, e^{j2\pi \left( \frac{nk}{N} - \frac{ml}{M} \right)} \] Here, \( N \) is the number of Doppler bins (time slots), and \( M \) is the number of delay bins (subcarriers). The ISFFT maps each data symbol from the delay-Doppler grid (where the channel is sparse and easier to equalize) to the time-frequency grid (where standard multicarrier modulation like OFDM can be applied). 2. SFFT — Symplectic Finite Fourier Transform Purpose: Performs the reverse operation ...

Coherent vs. Non-Coherent Demodulation

  For demodulation In general: 1. Synchronous (coherent) demodulation Receiver generates a local carrier/oscillator . It combines/multiplies the received signal with that carrier. Then a filter extracts the message. Received signal ↓ × Local oscillator ↓ Low-pass filter ↓ Message So yes, carrier multiplication is a common implementation of synchronous demodulation . 2. Asynchronous (non-coherent) demodulation Receiver doesn't need a phase-synchronized local carrier . It uses properties of the received signal itself to recover the information. For ASK , an envelope detector is the classic example: ASK signal ↓ Diode + RC ↓ Envelope ↓ Comparator ↓ Data Modulation Synchronous demodulation Non-coherent/asynchronous demodulation ASK/OOK Local carrier + multiplier Envelope detector AM Product detector Envelope detector FSK Coherent correlator/mixer Frequency discriminator, filters, etc. PSK Local synchronized carrier + multiplier Differential/n...

Online Simulator for ASK, FSK, and PSK Signal Generation

Interactive Digital Signal Processing (DSP) Tutorial and Simulator for ASK, FSK, and BPSK modulation techniques. Try our new Digital Signal Processing Simulator!   •   Interactive ASK, FSK, and BPSK tools updated for 2025. Start Now Digital Modulation Visualizer: ASK, FSK, & BPSK Simulator Learn and visualize binary modulation techniques (ASK, FSK, BPSK) in real-time with adjustable carrier and sampling parameters. Perfect for DSP students and engineers. 📡 ASK Simulator 📶 FSK Simulator 🎚️ BPSK Simulator 📚 More Topics ASK Modulator FSK Modulator BPSK Modulator Demodulation More Topics 1. ASK (Ampli...

Random Variable vs. Random Process: Definitions, Examples, and Key Differences

Random Variable vs. Random Process: Definitions, Examples, and Key Differences Random Variable and Random Process In the fields of probability theory and statistics, understanding the distinction between a Random Variable and a Random Process (Stochastic Process) is fundamental. This guide breaks down these concepts with mathematical precision and practical examples. 1. Random Variable (RV) Definition: A Random Variable is a deterministic function that maps each possible outcome of a random experiment to a unique real number. Mathematical Representation A random variable X is defined as a mapping from the sample space S to the set of real numbers ℝ : X : S → ℝ S (Sample Space): The set of all possible outcomes of an experiment. s ∈ S: A specific outcome. X(s): The numerical value asso...