Skip to main content

SALIM's LAB


Transmission & Reception Block Diagram

Digital Communication Simulator

Click to Start



This simulator provides an interactive visualization of a digital communication system, guiding the user through each major step involved in transmitting a digital message across a wireless channel. The simulator allows users to input a text message and observe how the message is encoded, transmitted, and decoded through the different blocks.


Topics coverd

Analog Modulation & Demodulation Amplitude Modulation (AM) and Demodulation Frequency Modulation (FM) and Demodulation Phase Modulation (PM) and Demodulation Pulse Modulation & Demodulation Pulse Amplitude Modulation (PAM) and Demodulation Pulse Width Modulation (PWM) and Demodulation Pulse Position Modulation (PPM) and Demodulation Delta Modulation (DM) and Demodulation Pulse Code Modulation (PCM) and Demodulation Digital Modulation & Demodulation Amplitude Shift Keying (ASK) and Demodulation Frequency Shift Keying (FSK) and Demodulation Phase Shift Keying (PSK) and Demodulation M-ary PSk M-ary QAM Constellation Diagrams
 

Explore Signal Processing Simulations



About SALIM's LAB

About Our Communication Process Simulator Introduction Welcome to our cutting-edge Communication Process Simulator! As a passionate creator, you've developed a powerful tool that enables users to explore and understand various communication techniques. Let's delve into the fascinating world of modulation, demodulation, source coding, channel coding, and decoding. Key Features 1. Modulation and Demodulation: - Our simulator allows users to experiment with different modulation schemes (such as amplitude modulation, frequency modulation, and phase modulation). - Understand how signals are modulated for efficient transmission and demodulated at the receiver end. 2. Source Coding: - Dive into the realm of data compression! Explore techniques like Huffman coding, arithmetic coding, and run-length encoding. - Witness how information is efficiently represented using fewer bits. 3. Channel Coding and Decoding: - Discover error-correcting codes like Reed-Solomon, convolutional codes, and turbo codes. - Simulate noisy channels and observe how these codes enhance data reliability. User Interface (UI) Our user-friendly interface ensures a seamless experience: - Interactive Controls: Adjust modulation parameters, select coding schemes, and visualize signal waveforms. - Visual Aids: Graphs, charts, and diagrams provide real-time feedback. How to Use 1. Access the Simulator: - Visit our website and navigate to the Communication Process Simulator section. - Click "Launch Simulator" to begin your exploration. 2. Choose a Module: - Select the specific communication process you want to simulate (e.g., modulation or source coding). - Set input parameters (e.g., signal frequency, data rate, coding rate). 3. Observe Results: - Visualize modulated signals, coded sequences, and noisy channel effects. - Analyze error rates and compare different coding strategies. Applications 1. Education and Learning: - Ideal for students, researchers, and enthusiasts studying communication systems. - Use it as a teaching aid in classrooms or workshops. 2. Prototyping and Testing: - Engineers can validate communication algorithms before implementing them in real-world systems. - Evaluate performance under varying conditions. Future Enhancements - Interactive Tutorials: Add guided walkthroughs for beginners. - Advanced Coding Techniques: Incorporate LDPC codes, polar codes, and adaptive modulation. - Collaboration Features: Enable users to share simulations and collaborate on projects. Conclusion Our Communication Process Simulator bridges theory and practice, empowering users to unravel the complexities of communication systems. Explore, learn, and innovate with us! 🚀

People are good at skipping over material they already know!

View Related Topics to







Contact Us

Name

Email *

Message *

Popular Posts

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

📘 Overview of Energy per Bit (Eb / N0) 🧮 Online Simulator for constellation diagrams of ASK, FSK, and PSK 🧮 Theory behind Constellation Diagrams of ASK, FSK, and PSK 🧮 MATLAB Codes for Constellation Diagrams of ASK, FSK, and PSK 📚 Further Reading 📂 Other Topics on Constellation Diagrams of ASK, PSK, and FSK ... 🧮 Simulator for constellation diagrams of m-ary PSK 🧮 Simulator for constellation diagrams of m-ary QAM BASK (Binary ASK) Modulation: Transmits one of two signals: 0 or -√Eb, where Eb​ is the energy per bit. These signals represent binary 0 and 1.    BFSK (Binary FSK) Modulation: Transmits one of two signals: +√Eb​ ( On the y-axis, the phase shift of 90 degrees with respect to the x-axis, which is also termed phase offset ) or √Eb (on x-axis), where Eb​ is the energy per bit. These signals represent binary 0 and 1.  BPSK (Binary PSK) Modulation: Transmits one of two signals...

Fading : Slow & Fast and Large & Small Scale Fading (with MATLAB Code + Simulator)

📘 Overview 📘 LARGE SCALE FADING 📘 SMALL SCALE FADING 📘 SLOW FADING 📘 FAST FADING 🧮 MATLAB Codes 📚 Further Reading LARGE SCALE FADING The term 'Large scale fading' is used to describe variations in received signal power over a long distance, usually just considering shadowing.  Assume that a transmitter (say, a cell tower) and a receiver  (say, your smartphone) are in constant communication. Take into account the fact that you are in a moving vehicle. An obstacle, such as a tall building, comes between your cell tower and your vehicle's line of sight (LOS) path. Then you'll notice a decline in the power of your received signal on the spectrogram. Large-scale fading is the term for this type of phenomenon. SMALL SCALE FADING  Small scale fading is a term that describes rapid fluctuations in the received signal power on a small time scale. This includes multipath propagation effects as well as movement-induced Doppler fr...

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...

Online Simulator for ASK, FSK, and PSK

Try our new Digital Signal Processing Simulator!   Start Simulator for binary ASK Modulation Message Bits (e.g. 1,0,1,0) Carrier Frequency (Hz) Sampling Frequency (Hz) Run Simulation Simulator for binary FSK Modulation Input Bits (e.g. 1,0,1,0) Freq for '1' (Hz) Freq for '0' (Hz) Sampling Rate (Hz) Visualize FSK Signal Simulator for BPSK Modulation ...

Understanding the Q-function in BASK, BFSK, and BPSK

Understanding the Q-function in BASK, BFSK, and BPSK 1. Definition of the Q-function The Q-function is the tail probability of the standard normal distribution: Q(x) = (1 / √(2Ï€)) ∫ x ∞ e -t²/2 dt What is Q(1)? Q(1) ≈ 0.1587 This means there is about a 15.87% chance that a Gaussian random variable exceeds 1 standard deviation above the mean. What is Q(2)? Q(2) ≈ 0.0228 This means there is only a 2.28% chance that a Gaussian value exceeds 2 standard deviations above the mean. Difference Between Q(1) and Q(2) Even though the argument changes from 1 to 2 (a small increase), the probability drops drastically: Q(1) = 0.1587 → errors fairly likely Q(2) = 0.0228 → errors much rarer This shows how fast the tail of the Gaussian distribution decays. It’s also why BER drops drama...

Pulse Shaping using Raised Cosine Filter (with MATLAB + Simulator)

  MATLAB Code for Raised Cosine Filter Pulse Shaping clc; clear; close all ; %% ===================================================== %% PARAMETERS %% ===================================================== N = 64; % Number of OFDM subcarriers cpLen = 16; % Cyclic prefix length modOrder = 4; % QPSK oversample = 8; % Oversampling factor span = 10; % RRC filter span in symbols rolloff = 0.25; % RRC roll-off factor %% ===================================================== %% Generate Baseband OFDM Symbols %% ===================================================== data = randi([0 modOrder-1], N, 1); % Random bits txSymbols = pskmod(data, modOrder, pi/4); % QPSK modulation % IFFT to get OFDM symbol tx_ofdm = ifft(txSymbols, N); % Add cyclic prefix tx_cp = [tx_ofdm(end-cpLen+1:end); tx_ofdm]; %% ===================================================== %% Oversample the Baseband Signal %% ===============================================...

What is - 3dB Frequency Response? Applications ...

📘 Overview & Theory 📘 Application of -3dB Frequency Response 🧮 MATLAB Codes 🧮 Online Digital Filter Simulator 📚 Further Reading Filters What is -3dB Frequency Response?   Remember, for most passband filters, the magnitude response typically remains close to the peak value within the passband, varying by no more than 3 dB. This is a standard characteristic in filter design. The term '-3dB frequency response' indicates that power has decreased to 50% of its maximum or that signal voltage has reduced to 0.707 of its peak value. Specifically, The -3dB comes from either 10 Log (0.5) {in the case of power} or 20 Log (0.707) {in the case of amplitude} . Viewing the signal in the frequency domain is helpful. In electronic amplifiers, the -3 dB limit is commonly used to define the passband. It shows whether the signal remains approximately flat across the passband. For example, in pulse shapi...

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

📘 Overview & Theory 🧮 MATLAB Code for ASK 🧮 MATLAB Code for FSK 🧮 MATLAB Code for PSK 🧮 Simulator for binary ASK, FSK, and PSK Modulations 📚 Further Reading ASK, FSK & PSK HomePage MATLAB Code MATLAB Code for ASK Modulation and Demodulation % The code is written by SalimWireless.Com % Clear previous data and plots clc; clear all; close all; % Parameters Tb = 1; % Bit duration (s) fc = 10; % Carrier frequency (Hz) N_bits = 10; % Number of bits Fs = 100 * fc; % Sampling frequency (ensure at least 2*fc, more for better representation) Ts = 1/Fs; % Sampling interval samples_per_bit = Fs * Tb; % Number of samples per bit duration % Generate random binary data rng(10); % Set random seed for reproducibility binary_data = randi([0, 1], 1, N_bits); % Generate random binary data (0 or 1) % Initialize arrays for continuous signals t_overall = 0:Ts:(N_bits...