Skip to main content

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.




MATLAB Code for ASK Modulation and Demodulation

% 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); binary_data = randi([0, 1], 1, N_bits); t_overall = 0:Ts:(N_bits * Tb) - Ts; message_signal_overall = zeros(1, length(t_overall)); ask_signal_overall = zeros(1, length(t_overall)); carrier_template = sqrt(2/Tb) * sin(2*pi*fc*(0:Ts:Tb-Ts)); for i = 1:N_bits current_bit = binary_data(i); t_segment_indices = ((i-1)*samples_per_bit + 1) : (i*samples_per_bit); if current_bit == 1 message_segment = ones(1, samples_per_bit); else message_segment = zeros(1, samples_per_bit); end ask_segment = carrier_template .* message_segment; message_signal_overall(t_segment_indices) = message_segment; ask_signal_overall(t_segment_indices) = ask_segment; end
ASK Output

Fig 1: ASK Modulation and Demodulation

MATLAB Code for FSK Modulation and Demodulation

% The code is written by SalimWireless.Com clc; clear; close all; % Parameters Fs = 1000; fc1 = 20; fc2 = 50; Tb = 1; num_bits = 10; Ts = 1/Fs; samples_per_bit = Fs * Tb; rng(20); bits = randi([0, 1], 1, num_bits); t_bit = 0:Ts:Tb-Ts; modulated_signal = []; for bit = bits if bit == 0 modulated_signal = [modulated_signal sin(2*pi*fc1*t_bit)]; else modulated_signal = [modulated_signal sin(2*pi*fc2*t_bit)]; end end
FSK Output

Fig 2: FSK Modulation and Demodulation

MATLAB Code for PSK Modulation and Demodulation

% The code is written by SalimWireless.Com clc; clear all; close all; carrier_frequency = 10; bit_duration = 1; sampling_frequency = 1000; Ts = 1/sampling_frequency; samples_per_bit = sampling_frequency * bit_duration; rng(30); bit_stream = randi([0, 1], 1, 8); t_bit = 0:Ts:bit_duration-Ts; psk_signal = []; for bit = bit_stream if bit == 0 psk_signal = [psk_signal sin(2*pi*carrier_frequency*t_bit + 0)]; else psk_signal = [psk_signal sin(2*pi*carrier_frequency*t_bit + pi)]; end end
PSK Output

Fig 3: PSK Modulation and Demodulation

Understanding the MATLAB Implementation

Key Variables

  • Fs: Sampling frequency (must be > 2x carrier frequency).
  • Tb: Bit duration (defines how long each symbol lasts).
  • rng(10): Ensures your random bit generation is reproducible.

The Logic

The code uses a for loop to iterate through the bitstream. Depending on the bit value (0 or 1), it selects the appropriate carrier frequency or phase, effectively performing Hard-Decision Mapping.

Common MATLAB Errors & Fixes

1. "Undefined function or variable": Ensure you are running the script in the same folder where your variables are saved. Use clc; clear all; at the top.

2. Aliasing in Plots: If your waveforms look "jagged," increase the Fs (Sampling Frequency) to at least 10 times the carrier frequency.

3. Toolboxes: These codes run on base MATLAB, but for advanced BER analysis, you may need the Communication Toolbox.

Interactive Modulation Simulator

Launch the web-based tool to simulate digital modulation techniques.

Simulator Launch Simulator →

Modulation Parameter Changed Noise Immunity Complexity
ASK Amplitude Low (Highly susceptible) Simplest
FSK Frequency High (Robust) Moderate
PSK Phase Very High Highest (Requires Coherent Detection)

From Simulation to Hardware

While these MATLAB scripts simulate digital modulation in a vacuum, real-world deployment requires considering AWGN (Additive White Gaussian Noise). If you are moving to hardware like USRP (Universal Software Radio Peripheral) or RTL-SDR, you must implement Pulse Shaping (like Root-Raised Cosine) to limit bandwidth occupancy. Want to read more about raised cosine filter? Click here.

Frequently Asked Questions

Which is better: ASK, FSK, or PSK?

PSK is generally superior for high-speed data because it is the most bandwidth-efficient and noise-resistant, though it requires more complex receiver hardware.

How do I calculate BER in MATLAB?

You can use the biterr function in MATLAB to compare the transmitted bitstream with the demodulated bitstream to calculate the Bit Error Rate.


📚 Further Reading


Effect of Noise (AWGN) on ASK, FSK, and PSK

The modulated signal, x(t), is propagated through a physical communication medium—such as a wireless interface or fiber-optic cabling—where it is subject to various channel impairments. Consequently, the resulting received signal, y(t), constitutes a degraded representation of the original transmission.

This relationship is mathematically characterized by the general received signal model in the presence of fading and noise:

y(t) = h(t) · x(t) + n(t)

Where:

  • x(t) denotes the transmitted modulated signal;
  • h(t) represents the multiplicative fading characteristics of the channel;
  • n(t) signifies the Additive White Gaussian Noise (AWGN) superimposed on the signal.

Read More: Effect of AWGN on ASK→   Effect of AWGN on FSK→   Effect of AWGN on PSK→   GET MATLAB Code 


Effect of Rayleigh Fading on ASK, FSK, and PSK

This technical analysis details the lifecycle of a signal within a digital communication system, focusing on the transition from the message signal to final recovery. To facilitate long-distance transmission, information is modulated onto high-frequency carriers. However, as the signal traverses a physical medium, it encounters significant degradation modeled by the following time-domain relationship:

y(t) = [h(t)] ∗ s(t) + w(t)

In this model, h(t) represents the Channel Impulse Response—specifically Rayleigh Fading—while w(t) signifies Additive White Gaussian Noise (AWGN). The text distinguishes between these two impairments: AWGN is a constant thermal noise that reduces the signal-to-noise ratio (SNR) across all frequencies, whereas Rayleigh Fading is a stochastic process caused by multipath propagation. In urban or indoor environments, signal reflections create "deep fades," resulting in rapid fluctuations of signal strength.

The performance impact is most visible in the Bit Error Rate (BER). While BER in an AWGN channel decreases exponentially with higher power, fading channels exhibit a much slower, linear decay. For instance, at 0 dB SNR using BPSK modulation, the BER effectively doubles from 0.078 (AWGN) to 0.16 (Rayleigh).

To combat these effects, systems employ Equalization to reverse channel distortion and Diversity Techniques (spatial, temporal, or frequency) to ensure redundancy.

Read More: Impact of Rayleigh Fading on BPSK



Contact Us

Name

Email *

Message *

Popular Posts

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...

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...

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...

(Filters) Free MATLAB alternative for signal analysis

Advanced Signal Filters Upload CSV (1st Col) or Audio (WAV, MP3, etc.) Generate Messy Signal (20Hz + 50Hz + 150Hz) No Operation FFT (Spectrum) Amplitude Modulation (AM) Double Sideband Supressed Carrier (DSBSC) Pulse Amplitude Modulation (PAM) Flat Top PAM Filters - LPF, HPF, BPF, Notch Principal Component Analysis (PCA) Cross Spectrum Filter Type: Signal Cleaner ...

ADC Conversion Time Comparison: Flash, SAR, Ramp & Dual-Slope ADC

ADC Conversion Time Comparison: Flash, SAR, Ramp & Dual-Slope ADC ADC Conversion Time: Flash, Digital Ramp, SAR and Dual-Slope ADC Analog-to-digital converters (ADCs) convert continuous analog signals into digital values. Different ADC architectures require different amounts of time to complete this conversion. This guide explains the working principles, conversion-time formulas, and differences between Flash, Digital Ramp, Successive Approximation, and Dual-Slope ADCs. Table of Contents Flash ADC conversion time Digital Ramp ADC conversion time Successive Approximation ADC conversion time Dual-Slope ADC conversion time ADC conv...

CMOS Logic Gates: Inverter, NAND, and NOR

CMOS Logic Gates: Inverter, NAND, and NOR Complementary metal–oxide–semiconductor (CMOS) technology forms the backbone of modern digital IC design. Patented by Frank Wanlass in 1963 ( US patent 3,356,858 ), CMOS enables low-power, high-speed, and noise-immune logic circuits. CMOS gates, including inverters, NAND, and NOR, are widely used in both large-scale and small-scale integrated circuits due to their efficiency and versatility. CMOS Inverter A CMOS inverter consists of a complementary pair of PMOS and NMOS transistors. The PMOS transistor connects to the supply voltage V DD , while the NMOS connects to ground. The input voltage V IN controls both gates, and the output voltage V OUT is taken from the connected drains. CMOS inverters are highly energy-efficient and produce minimal heat due to their comple...

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...

Interactive Sallen-Key filter Simulation (2nd order LPF)

  Sallen-Key Filter Explained: Why It’s the Most Popular Second-Order Low-Pass Filter Sallen-Key Filter Explained: Why It’s the Most Popular Second-Order Low-Pass Filter (With Math) If you're learning analog electronics, active filters, or preparing for engineering interviews and exams, you've probably come across the Sallen-Key filter . But what exactly is it, and why do engineers prefer it over simply cascading RC low-pass filters? Live Interactive Simulator Adjust the component values to see the real-time frequency response (Bode Plot). R1 (kΩ): 10 R2 (kΩ): 10 C1 (nF): 10 C2 (nF): 10 ...