Skip to main content

Pulse Position Modulation (PPM)


Pulse Position Modulation (PPM) is a highly efficient signal modulation technique. Depending on the application, it is implemented using one of three primary methods: 1. Analog PPM (continuous shift), 2. Digital/M-ary PPM (discrete slots), and 3. Differential PPM (relative timing).

Digital Pulse Position Modulation (PPM) is a type of signal modulation in which M message bits are encoded by transmitting a single pulse within one of 2แดน possible time positions within a fixed time frame. This process is repeated every T seconds, resulting in a data rate of M/T bits per second.

Pulse Position Modulation Example (Analog Method)

PPM is a form of analog modulation where the position of each pulse is varied according to the amplitude of the sampled modulating signal, while the amplitude and width of the pulses remain constant. This means only the timing (position) of the pulse carries the information.

PPM is commonly used in optical and wireless communications, especially where multipath interference is minimal or needs to be reduced. Because the information is carried in timing, it's more robust in some noisy environments compared to other modulation schemes.

Although PPM can be used for analog signal modulation, it is also used in digital communications where each pulse position represents a symbol or bit pattern. However, it is not ideal for transmitting complex data files, as it is generally used for simple or low-data-rate signaling.

PPM waveform illustration
Fig: PPM Waveforms

Example: Pulse Position Modulation (PPM) of Sinusoidal Signal

We have a sinusoidal signal:

x(t) = A sin(2ฯ€ f t)

And we want to modulate this signal using Pulse Position Modulation (PPM).


Step-by-Step Example

1. Sinusoidal Signal

Let’s define a sinusoidal signal as:

x(t) = 5 sin(2ฯ€ ⋅ 1 ⋅ t)

This is a sine wave with:

  • Amplitude: A = 5
  • Frequency: f = 1 Hz

2. Pulse Position Modulation Concept

We’ll now encode information into the timing of pulses. To ensure robustness and avoid pulse overlapping, we use a small modulation index (k = 0.01).

If the amplitude is large, the pulse will be slightly delayed from its reference time. If it’s small, the pulse will stay closer to the reference time.

3. Calculating the Pulse Positions

We compute the values of x(t) and the corresponding pulse positions:

Time Sample 1: t = 0

x(0) = 5 sin(0) = 0

Pulse at reference time t = 0.

Time Sample 2: t = 0.1

x(0.1) = 5 sin(0.2ฯ€) ≈ 2.939
Shift = 0.01 × 2.939 = 0.0294
t = 0.1 + 0.0294 = 0.1294 seconds

Time Sample 3: t = 0.2

x(0.2) = 5 sin(0.4ฯ€) ≈ 4.7555
Shift = 0.01 × 4.7555 = 0.0475
t = 0.2 + 0.0475 = 0.2475 seconds

Time Sample 4: t = 0.3

x(0.3) = 5 sin(0.6ฯ€) ≈ 4.045
Shift = 0.01 × 4.045 = 0.0404
t = 0.3 + 0.0404 = 0.3404 seconds

Time Sample 5: t = 0.4

x(0.4) = 5 sin(0.8ฯ€) ≈ 2.939
Shift = 0.01 × 2.939 = 0.0294
t = 0.4 + 0.0294 = 0.4294 seconds

Time Sample 6: t = 0.5

x(0.5) = 5 sin(ฯ€) = 0
Pulse at reference time t = 0.5

4. Summary of Pulse Timing

Pulse positions based on sinusoidal amplitude (ensuring no overlap):

Sample Time (t) Amplitude x(t) Pulse Position (tpulse)
0.00.0000.0000
0.12.9390.1294
0.24.7550.2475
0.34.0450.3404
0.42.9390.4294
0.50.0000.5000

Demodulation of PPM Signal

Demodulation circuit for PPM

The noise-corrupted PPM waveform is received by the PPM demodulator circuit. A pulse generator produces fixed-duration pulses from the incoming signal and applies them to the reset (R) input of an SR flip-flop. Simultaneously, a synchronized reference pulse train (recovered via a Phase-Locked Loop) is applied to the set (S) input. The SR flip-flop generates a PWM waveform, which is then passed through a Low Pass Filter (LPF) to recover the original message.

Effect of Noise on Pulse Position Modulation

Since in a PPM system the transmitted information is contained in the relative positions of the modulated pulses, the presence of additive noise affects the performance by falsifying the perceived pulse timing. Immunity to noise can be improved by making the pulse rise rapidly, reducing the time window for noise interference.

In theory, noise would have no effect if pulses were perfectly rectangular (requiring infinite bandwidth). In practice, finite rise times mean some degradation is inevitable. Similar to continuous-wave modulation, PPM performance can be evaluated using the output signal-to-noise ratio (SNR). The figure of merit compares output SNR to channel SNR, showing that performance improves with bandwidth but suffers a threshold effect when SNR drops too low.


Try Interactive Online Simulation (web-based)

We have developed web-based interactive simulations to help you better understand Pulse Position Modulation and other complex concepts in wireless communication systems.

Try the Simulations:
PAM, PWM, & PPM Online Simulators


MATLAB Code for Analog Pulse Position Modulation

To get the MATLAB Code, click here 


Further Reading

  1. Pulse Amplitude Modulation (PAM)
  2. Pulse Width Modulation (PWM)
  3. Delta Modulation (DM)
  4. Pulse Code Modulation (PCM)
  5. Pulse Code Modulation in MATLAB
  6. PWM to PPM Conversion: Understanding Pulse Modulation Techniques


Contact Us

Name

Email *

Message *

Popular Posts

UGC NET Electronic Science Previous Year Question Papers with Solutions

Home / Engineering & Other Exams / UGC NET 2026 PYQ ⬇️ Download Papers and Solutions ๐Ÿ“‹ Exam Pattern ๐Ÿ’ก Preparation Tips ❓ FAQs ๐Ÿ“Š 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) ๐Ÿ“ฅ Download UGC NET Electronics PDFs Complete collection of previous year question papers, answer keys and explanations for Subject Code 88. Start Downloading ๐Ÿ“‚ View All Question Papers June 2025 - Question Paper Download PDF June 2025 - Solved Paper + Explanation ...

MUSIC Algorithm Explained (with MATLAB + Simulator)

Practical Implementation of the MUSIC Algorithm The focus is on how the algorithm works computationally , not just theory, and it explains the denominator (a H E n E n H a) mathematically and intuitively. 1. Introduction The MUSIC (Multiple Signal Classification) algorithm is a high-resolution method used in signal processing and array processing to estimate the Direction of Arrival (DOA) of signals received by a sensor array. Unlike classical beamforming methods, MUSIC uses eigenvector decomposition of the covariance matrix to separate the signal subspace and noise subspace , allowing it to achieve much higher angular resolution. In practical implementations, MUSIC works by: Simulating or collecting array signals Computing the covariance matrix Performing eigenvalue decomposition Separating signal and noise subspaces Scanning possible angles using a steering vector Constructing a pseudo-spectrum where peaks indicate signal directions 2. Signal Mo...

BER vs SNR for M-ary QAM, M-ary PSK, QPSK, BPSK, ...(MATLAB Code + Simulator)

Bit Error Rate (BER) & SNR Guide Analyze communication system performance with our interactive simulators and MATLAB tools. ๐Ÿ“˜ Theory ๐Ÿงฎ Simulators ๐Ÿ’ป MATLAB Code ๐Ÿ“š Resources BER Definition SNR Formula BER Calculator MATLAB Comparison ๐Ÿ“‚ Explore M-ary QAM, PSK, and QPSK Topics ▼ ๐Ÿงฎ Constellation Simulator: M-ary QAM ๐Ÿงฎ Constellation Simulator: M-ary PSK ๐Ÿงฎ BER calculation for ASK, FSK, and PSK ๐Ÿงฎ Approaches to BER vs SNR Calculation What is Bit Error Rate (BER)? The BER indicates how many corrupted bits are received compared to the total number of bits sent. It is the primary figur...

MATLAB Code for ASK, FSK, and PSK (with Online Simulator)

MATLAB Code for ASK, FSK, and PSK Comprehensive implementation of digital modulation and demodulation techniques with simulation results. ๐Ÿ“˜ Theory ๐Ÿ“ก ASK Code ๐Ÿ“ถ FSK Code ๐ŸŽš️ PSK Code ๐Ÿ•น️ Simulator ๐Ÿ“š Further Reading Amplitude Shift Frequency Shift Phase Shift Live Simulator ASK, FSK & PSK HomePage MATLAB Code MATLAB Code for ASK Modulation and Demodulation COPY % The code is written by SalimWireless.Com clc; clear all; close all; % Parameters Tb = 1; fc = 10; N_bits = 10; Fs = 100 * fc; Ts = 1/Fs; samples_per_bit = Fs * Tb; rng(10); binar...

Constellation Diagrams of ASK, PSK, and FSK (with MATLAB Code + Simulator)

Constellation Diagrams: ASK, FSK, and PSK Comprehensive guide to signal space representation, including interactive simulators and MATLAB implementations. ๐Ÿ“˜ Overview ๐Ÿงฎ Simulator ⚖️ Theory ๐Ÿ“ˆ Q-function ๐Ÿ“š Resources BASK Modulation Transmits one of two signals: 0 or $\sqrt{E_b}$, representing binary 0 and 1. Simple but sensitive to noise. BFSK Modulation Transmits one of two signals: $\sqrt{E_b}$ on the Y-axis or $\sqrt{E_b}$ on the X-axis. These are orthogonal signals. BPSK Modulation Transmits $+\sqrt{E_b}$ or $-\sqrt{E_b}$ (antipodal signaling). Most efficient binary scheme. ...

PSD Calculation with FFT: MATLAB Tutorial for Signal Analysis

  Implementation Steps 1. FFT Computes the Frequency Content of a Signal FFT converts a time-domain signal to the frequency domain. If: The signal is sampled at rate $f_s$ You compute an $N_{\text{FFT}}$-point FFT Then each FFT bin corresponds to a frequency resolution of: $$\Delta f = \frac{f_s}{N_{\text{FFT}}}$$ So the FFT gives you accurate frequency content, assuming the signal is stationary and adequately sampled (Nyquist criterion met).  2. Magnitude Squared Gives Power (Not Amplitude) $$P[k] = |X[k]|^2$$ This gives power at each frequency bin, not just amplitude. It represents how much energy is present at each frequency. It's a key step for PSD.  3. Normalization Makes the PSD Physically Meaningful The equation: $$\text{PSD}[k] = \frac{|X[k]|^2}{N_{\text{FFT}} \cdot f_s \cdot U}$$ is derived from first principles and ensures that the u...

OFDM Symbols and Subcarriers Explained

This article explains how OFDM (Orthogonal Frequency Division Multiplexing) symbols and subcarriers work. It covers modulation, mapping symbols to subcarriers, subcarrier frequency spacing, IFFT synthesis, cyclic prefix, and transmission. Step 1: Modulation First, modulate the input bitstream. For example, with 16-QAM , each group of 4 bits maps to one QAM symbol. Suppose we generate a sequence of QAM symbols: s0, s1, s2, s3, s4, s5, …, s63 Step 2: Mapping Symbols to Subcarriers Assume N sub = 8 subcarriers. Each OFDM symbol in the frequency domain contains 8 QAM symbols (one per subcarrier): Mapping (example) OFDM symbol 1 → s0, s1, s2, s3, s4, s5, s6, s7 OFDM symbol 2 → s8, s9, s10, s11, s12, s13, s14, s15 … OFDM sym...

MATLAB code for BER vs SNR for M-QAM, M-PSK, QPSK, BPSK (with Simulation)

๐Ÿงฎ MATLAB Code for BPSK, M-ary PSK, and M-ary QAM Together ๐Ÿงฎ MATLAB Code for M-ary QAM ๐Ÿงฎ MATLAB Code for M-ary PSK ๐Ÿ“š Further Reading MATLAB Script for BER vs. SNR for M-QAM, M-PSK, QPSK, BPSK % Written by Salim Wireless clc; clear; close all; snr_db = -5:2:25; psk_orders = [2, 4, 8, 16, 32]; qam_orders = [4, 16, 64, 256]; ber_psk_results = zeros(length(psk_orders), length(snr_db)); ber_qam_results = zeros(length(qam_orders), length(snr_db)); for i = 1:length(psk_orders) ber_psk_results(i, :) = berawgn(snr_db, 'psk', psk_orders(i), 'nondiff'); end for i = 1:length(qam_orders) ber_qam_results(i, :) = berawgn(snr_db, 'qam', qam_orders(i)); end figure; semilogy(snr_db, ber_psk_results(1, :), 'o-', 'LineWidth', 1.5, 'DisplayName', 'BPSK'); hold on; for i = 2:length(psk_orders) semilogy(snr_db, ber_psk_results(i, :), 'o-', 'DisplayName', sprintf('%d-PSK', psk_or...