Skip to main content

Pulse Amplitude Modulation and Demodulation



 Pulse Amplitude Modulation (PAM)

Sampling allow us to represent real world continuous signal, such as audio or video, in a format suitable for digital processing and storage. This sampled discrete-time signal is inherently digital. A digital signal is a discrete-time signal that is further quantized in amplitude.

Pulse Amplitude modulation (PAM) is the modulation technique in which amplitude of carrier pulses is made to vary in accordance with the input message signal, similar to Amplitude Modulation (AM). But here we use pulse generator as carrier signal. So, Pulse–amplitude modulation (PAM) is a form of signal modulation where the message information is encoded in the amplitude of a series of signal pulses.


 Fig 1: Pulse Amplitude Modulation




The basic idea in PAM for communication over a Continuous Time (CT) channel is to transmit a sequence of Continuous Time pulses of some per-specified pulse shape, with the sequence of pulse amplitudes carrying the information. 


 Pulse Amplitude Demodulation

To demodulate a PAM signal, pass it through a reconstruction filter. As here, the amplitude of the pulse carrier is varied according to the amplitude of the message signal, we only need to pass this received pulse signal through a low-pass filter with a cut-off frequency the same as the message signal or slightly higher.


If you perform quantization at the transmitter side and assign some levels (amplitude levels), then demodulation is performed by detecting the amplitude level of the carrier at every single period. The number of possible pulse amplitudes in analog PAM is theoretically infinite. Digital PAM reduces the number of pulse amplitudes to some power of two. For example, in 4-level PAM there are (2^2 = 4) possible discrete pulse amplitudes; in 8-level PAM there are (2^3 = 8) possible discrete pulse amplitudes; and in 16-level PAM there are (2^4 = 16) possible discrete pulse amplitudes.
 

Instructions for Pulse Amplitude Modulation (PAM)

  • Note: Use the input fields to enter the message frequency and the square pulse carrier frequency.
  • Step 1: Click the "Generate Message" button to generate the input message signal.
  • Step 2: Click the "Generate Carrier" button to generate the carrier signal. Carrier must be > Message.
  • Step 3: Click the "Generate PAM Signal" button to generate the Modulated signal.

PAM Modulation Control Center

Perform Pulse Amplitude Modulation by interacting with the signal generators below.

Ready for Signal Recovery?

After generating your PAM signal, proceed to the Demodulation section to recover the original message using a reconstruction filter.

Go to Demodulation

Instructions for Pulse Amplitude Demodulation

  • The reconstruction filter recovers the original message from the sampled PAM signal.
  • A low-pass filter (LPF) is used with a cutoff frequency at or above the message frequency.
  • Click 'Demodulate' to view the recovered baseband signal.

Technical Definition: PAM Signal

MATLAB Mathematical Representation Copy Snippet
% Ideal Sampling with Pulse Train t = 0:0.001:1; fm = 2; fc = 10; m_t = cos(2*pi*fm*t); c_t = square(2*pi*fc*t); s_pam = m_t .* (c_t > 0); % Low Pass Reconstruction [b,a] = butter(4, fm/(fs/2)); demod = filter(b,a, s_pam);

Further Reading 



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 📋 Exam Pattern 💡 Preparation Tips ❓ FAQs 📊 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 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. 📘 Theory 🧮 Simulators 💻 MATLAB Code 📚 Resources BER Definition SNR Formula BER Calculator MATLAB Comparison 📂 Explore M-ary QAM, PSK, and QPSK Topics ▼ 🧮 Constellation Simulator: M-ary QAM 🧮 Constellation Simulator: M-ary PSK 🧮 BER calculation for ASK, FSK, and PSK 🧮 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. 📘 Theory 📡 ASK Code 📶 FSK Code 🎚️ PSK Code 🕹️ Simulator 📚 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. 📘 Overview 🧮 Simulator ⚖️ Theory 📈 Q-function 📚 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. ...

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...

Frequency Selective Fading vs Flat Fading in MATLAB

In the MATLAB code below, a comparison between  frequency-selective fading  and  flat fading  is shown. In frequency-selective fading, multipath propagation causes multiple delayed copies of the signal to arrive at the receiver. When the channel delay spread exceeds the symbol duration, these delayed components overlap, resulting in inter-symbol interference (ISI). In flat fading, ISI does not occur because the signal bandwidth is much smaller than the channel’s coherence bandwidth . Therefore, the channel response remains approximately constant across the signal bandwidth, and all symbols experience the same fading. MATLAB Code for frequency selective fading channel % OFDM over frequency selective Rayleigh fading channel clc; clearvars; close all ; % Simulation parameters nSym = 10^4; % Number of OFDM symbols EbN0dB = 0:2:20; % Eb/N0 range MOD_TYPE = 'MPSK' ; % 'MPSK' or 'MQAM' M = 4; % QPSK N = 64; % Total number ...

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...