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

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

📘 Overview of BER and SNR 🧮 Online Simulator for BER calculation of m-ary QAM and m-ary PSK 🧮 MATLAB Code for BER calculation of M-ary QAM, M-ary PSK, QPSK, BPSK, ... 📚 Further Reading 📂 View Other Topics on M-ary QAM, M-ary PSK, QPSK ... 🧮 Online Simulator for Constellation Diagram of m-ary QAM 🧮 Online Simulator for Constellation Diagram of m-ary PSK 🧮 MATLAB Code for BER calculation of ASK, FSK, and PSK 🧮 MATLAB Code for BER calculation of Alamouti Scheme 🧮 Different approaches to calculate BER vs SNR What is Bit Error Rate (BER)? The abbreviation BER stands for Bit Error Rate, which indicates how many corrupted bits are received (after the demodulation process) compared to the total number of bits sent in a communication process. BER = (number of bits received in error) / (total number of tran...
Read more

BER performance of QPSK with BPSK, 4-QAM, 16-QAM, 64-QAM, 256-QAM, etc (MATLAB + Simulator)

📘 Overview 📚 QPSK vs BPSK and QAM: A Comparison of Modulation Schemes in Wireless Communication 📚 Real-World Example 🧮 MATLAB Code 📚 Further Reading   QPSK provides twice the data rate compared to BPSK. However, the bit error rate (BER) is approximately the same as BPSK at low SNR values when gray coding is used. On the other hand, QPSK exhibits similar spectral efficiency to 4-QAM and 16-QAM under low SNR conditions. In very noisy channels, QPSK can sometimes achieve better spectral efficiency than 4-QAM or 16-QAM. In practical wireless communication scenarios, QPSK is commonly used along with QAM techniques, especially where adaptive modulation is applied. Modulation Bits/Symbol Points in Constellation Usage Notes BPSK 1 2 Very robust, used in weak signals QPSK 2 4 Balanced speed & reliability 4-QAM ...
Read more

MATLAB code for BER vs SNR for M-QAM, M-PSK, QPSk, BPSK, ...(with Online Simulator)

🧮 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; num_symbols = 1e5; snr_db = -20:2:20; 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) psk_order = psk_orders(i); for j = 1:length(snr_db) data_symbols = randi([0, psk_order-1], 1, num_symbols); modulated_signal = pskmod(data_symbols, psk_order, pi/psk_order); received_signal = awgn(modulated_signal, snr_db(j), 'measured'); demodulated_symbols = pskdemod(received_signal, psk_order, pi/psk_order); ber_psk_results(i, j) = sum(data_symbols ~= demodulated_symbols) / num_symbols; end end for i...
Read more

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 ...
Read more

Theoretical BER vs SNR for binary ASK, FSK, and PSK with MATLAB Code + Simulator

📘 Overview & Theory 🧮 MATLAB Codes 📚 Further Reading Theoretical BER vs SNR for Amplitude Shift Keying (ASK) The theoretical Bit Error Rate (BER) for binary ASK depends on how binary bits are mapped to signal amplitudes. For typical cases: If bits are mapped to 1 and -1, the BER is: BER = Q(√(2 × SNR)) If bits are mapped to 0 and 1, the BER becomes: BER = Q(√(SNR / 2)) Where: Q(x) is the Q-function: Q(x) = 0.5 × erfc(x / √2) SNR : Signal-to-Noise Ratio N₀ : Noise Power Spectral Density Understanding the Q-Function and BER for ASK Bit '0' transmits noise only Bit '1' transmits signal (1 + noise) Receiver decision threshold is 0.5 BER is given by: P b = Q(0.5 / σ) , where σ = √(N₀ / 2) Using SNR = (0.5)² / N₀, we get: BER = Q(√(SNR / 2)) Theoretical BER vs ...
Read more

Doppler Delay

  Doppler Shift Formula When either the transmitter or the receiver is in motion, or when both are in motion, Doppler Shift is an essential parameter in wireless Communication. We notice variations in reception frequencies in vehicles, trains, or other similar environments. In plain language, the received signal frequency increases as the receiver moves toward the transmitter and drops as the receiver moves in the opposite direction of the transmitter. This phenomenon is called the Doppler shift or Doppler spread. Doppler Shift Formula: By equation,                fR = fT (+/-) fD                                      fR= receiving  frequency                                      fT= transmitted frequency              ...
Read more

How Windowing Affects Your Periodogram

The windowed periodogram is a widely used technique for estimating the Power Spectral Density (PSD) of a signal. It enhances the classical periodogram by mitigating spectral leakage through the application of a windowing function. This technique is essential in signal processing for accurate frequency-domain analysis.   Power Spectral Density (PSD) The PSD characterizes how the power of a signal is distributed across different frequency components. For a discrete-time signal, the PSD is defined as the Fourier Transform of the signal’s autocorrelation function: S x (f) = FT{R x (Ï„)} Here, R x (Ï„)}is the autocorrelation function. FT : Fourier Transform   Classical Periodogram The periodogram is a non-parametric PSD estimation method based on the Discrete Fourier Transform (DFT): P x (f) = \(\frac{1}{N}\) X(f) 2 Here: X(f): DFT of the signal x(n) N: Signal length However, the classical periodogram suffers from spectral leakage due to abrupt truncation of the ...
Read more

Theoretical vs. simulated BER vs. SNR for ASK, FSK, and PSK (MATLAB Code + Simulator)

📘 Overview 🧮 Simulator for calculating BER 🧮 MATLAB Codes for calculating theoretical BER 🧮 MATLAB Codes for calculating simulated BER 📚 Further Reading BER vs. SNR denotes how many bits in error are received for a given signal-to-noise ratio, typically measured in dB. Common noise types in wireless systems: 1. Additive White Gaussian Noise (AWGN) 2. Rayleigh Fading AWGN adds random noise; Rayleigh fading attenuates the signal variably. A good SNR helps reduce these effects. Simulator for calculating BER vs SNR for binary ASK, FSK, and PSK Calculate BER for Binary ASK Modulation Enter SNR (dB): Calculate BER Calculate BER for Binary FSK Modulation Enter SNR (dB): Calculate BER Calculate BER for Binary PSK Modulation Enter SNR (dB): Calculate BER BER vs. SNR Curves MATLAB Code for Theoretical BER % The code is written by SalimWireless.Com clc; clear; close all; % SNR va...
Read more