Skip to main content

ASK, FSK, and PSK (with MATLAB + Online Simulator)


📘 ASK Theory 📘 FSK Theory 📘 PSK Theory 📊 Comparison 🧮 MATLAB Codes 🎮 Simulator

ASK or OFF ON Keying

ASK is a simple (less complex) Digital Modulation Scheme where we vary the modulation signal's amplitude or voltage by the message signal's amplitude or voltage. We select two levels (two different voltage levels) for transmitting modulated message signals.

Example: "+5 Volt" (upper level) and "0 Volt" (lower level). To transmit binary bit "1", the transmitter sends "+5 Volts", and for bit "0", it sends no power.

The receiver uses filters to detect whether a binary "1" or "0" was transmitted.

Output of ASK, FSK, and PSK modulation using MATLAB
Fig 1: Output of ASK, FSK, and PSK modulation using MATLAB for a data stream "1 1 0 0 1 0 1 0" (Get MATLAB Code)

FSK (Frequency Shift Keying)

In Frequency Shift Keying (FSK), the message signal is modulated using a high-frequency carrier. Binary "1" and "0" are represented by two different frequencies close to the carrier frequency.

For example, using frequencies f1 and f2 (where f1 > f2):

S₁(t) = A cos(2Ï€fc1t) for binary 1
S₂(t) = A cos(2Ï€fc2t) for binary 0

Here, fc1 is different from fc2.

PSK (Phase Shift Keying)

In Phase Shift Keying (PSK), the phase of the carrier signal is changed to represent data bits. Binary "1" is transmitted by shifting the signal’s phase by 180°, while binary "0" keeps the same phase.

s(t) = A cos(2πfct + π) for binary 1
s(t) = A cos(2Ï€fct) for binary 0

Bit Rate Comparison

PSK (Phase Shift Keying)

PSK can use various phase shifts to encode more bits per symbol (e.g., QPSK, 16-PSK). It is the most efficient for high bit rates.

FSK (Frequency Shift Keying)

FSK requires more bandwidth, making it less bit-efficient than PSK for high-speed applications.

ASK (Amplitude Shift Keying)

ASK is highly susceptible to noise and is typically less effective than PSK for high-speed transmission.

Conclusion: PSK can achieve the highest bit rates, especially using higher-order modulation techniques.

MATLAB Code: ASK, FSK, and PSK

This single script generates a random binary sequence and applies all three digital modulation techniques (Amplitude, Frequency, and Phase Shift Keying) for side-by-side comparison.

% DIGITAL MODULATION (ASK, FSK, PSK) 
% Source: SalimWireless.Com 

clc; clear all; close all;

% --- 1. Parameters Configuration ---
Fs = 1000;              % Sampling Frequency
Tb = 1;                 % Bit Duration (seconds)
N_bits = 8;             % Number of bits to transmit
fc = 10;                % Base Carrier Frequency (Hz)
fc2 = 30;               % Secondary Frequency for FSK (Hz)
Ts = 1/Fs;              % Sampling Period
t_bit = 0:Ts:Tb-Ts;     % Time vector for one bit
rng(42);                % For reproducible results

% Generate Random Binary Data
binary_data = randi([0, 1], 1, N_bits);

% --- 2. Signal Generation ---
message_sig = [];
ask_sig = [];
fsk_sig = [];
psk_sig = [];

for bit = binary_data
    % Message Signal (Square wave)
    m_segment = bit * ones(1, length(t_bit));
    message_sig = [message_sig m_segment];
    
    % ASK Logic: Bit 1 = Carrier ON, Bit 0 = Carrier OFF
    ask_seg = bit * sin(2*pi*fc*t_bit);
    ask_sig = [ask_sig ask_seg];
    
    % FSK Logic: Bit 1 = fc2 (High), Bit 0 = fc (Low)
    if bit == 1
        fsk_seg = sin(2*pi*fc2*t_bit);
    else
        fsk_seg = sin(2*pi*fc*t_bit);
    end
    fsk_sig = [fsk_sig fsk_seg];
    
    % PSK Logic: Bit 1 = 180 deg phase, Bit 0 = 0 deg phase
    if bit == 1
        psk_seg = sin(2*pi*fc*t_bit + pi);
    else
        psk_seg = sin(2*pi*fc*t_bit + 0);
    end
    psk_sig = [psk_sig psk_seg];
end

% Total Time Vector for Plotting
t_total = 0:Ts:(N_bits*Tb)-Ts;

% --- 3. Visualization ---
figure('Name', 'Digital Modulation Comparison', 'Color', 'w');

subplot(4,1,1);
plot(t_total, message_sig, 'LineWidth', 2, 'Color', 'k');
title(['Binary Message: ', num2str(binary_data)]); grid on; axis([0 N_bits*Tb -0.5 1.5]);

subplot(4,1,2);
plot(t_total, ask_sig, 'LineWidth', 1, 'Color', 'b');
title('ASK (Amplitude Shift Keying)'); grid on;

subplot(4,1,3);
plot(t_total, fsk_sig, 'LineWidth', 1, 'Color', 'r');
title('FSK (Frequency Shift Keying)'); grid on;

subplot(4,1,4);
plot(t_total, psk_sig, 'LineWidth', 1, 'Color', [0 0.5 0]);
title('PSK (Phase Shift Keying)'); grid on;
xlabel('Time (seconds)');

Interactive Modulation Simulator

Test your binary data (1,0,1,0) and adjust carrier frequencies in our web-based simulator tool.

Launch Full Simulator →

📚 Try Online Interactive Simulators

📚 Further Reading

📊 MATLAB & ONLINE SIMULATIONS (Web-Based)
🎓 GATE & UGC - NET SOLUTIONS
📡 WIRELESS & SIGNAL PROCESSING


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 ...
Read more

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...
Read more

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...
Read more

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

🧮 MATLAB Code for BPSK, M-ary PSK, and M-ary QAM Together 🧮 MATLAB Code for M-ary QAM 🧮 MATLAB Code for M-ary PSK 📚 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...
Read more

Theoretical BER vs SNR for BPSK

Theoretical Bit Error Rate (BER) vs Signal-to-Noise Ratio (SNR) for BPSK in AWGN Channel Let’s simplify the explanation for the theoretical Bit Error Rate (BER) versus Signal-to-Noise Ratio (SNR) for Binary Phase Shift Keying (BPSK) in an Additive White Gaussian Noise (AWGN) channel. Key Points Fig. 1: Constellation Diagrams of BASK, BFSK, and BPSK [↗] BPSK Modulation Transmits one of two signals: +√Eb or −√Eb , where Eb is the energy per bit. These signals represent binary 0 and 1 . AWGN Channel The channel adds Gaussian noise with zero mean and variance N₀/2 (where N₀ is the noise power spectral density). Receiver Decision The receiver decides if the received signal is closer to +√Eb (for bit 0) or −√Eb (for bit 1) . Bit Error Rat...
Read more

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...
Read more

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. ...
Read more