Skip to main content
Home Wireless Communication Modulation MATLAB Beamforming Project Ideas MIMO Computer Networks
Electronics Industry Wireless FORUM Work Hub Applications & Games Generate QR for Any Link Sitemap Generator (for Any Website) Play game Electrical & Electronics Calculator Contact Get Newsletter.
☰

SALIM's LAB


SALIM's LAB

Transmission & Reception



Analog Modulation & Demodulation

  1. Amplitude Modulation (AM) and Demodulation
  2. Frequency Modulation (FM) and Demodulation
  3. Phase Modulation (PM) and Demodulation

 


Pulse Modulation & Demodulation

  1. Pulse Amplitude Modulation (PAM) and Demodulation
  2. Pulse Width Modulation (PWM) and Demodulation
  3. Pulse Position Modulation (PPM) and Demodulation
  4. Delta Modulation (DM) and Demodulation
  5. Pulse Code Modulation (PCM) and Demodulation

 


Digital Modulation & Demodulation

  1. Amplitude Shift Keying (ASK) and Demodulation
  2. Frequency Shift Keying (FSK) and Demodulation
  3. Phase Shift Keying (PSK) and Demodulation

 



Other Experiments


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







Admin & Author: Salim

profile

  Website: www.salimwireless.com
  Interests: Signal Processing, Telecommunication, 5G Technology, Present & Future Wireless Technologies, Digital Signal Processing, Computer Networks, Millimeter Wave Band Channel, Web Development
  Seeking an opportunity in the Teaching or Electronics & Telecommunication domains.
  Possess M.Tech in Electronic Communication Systems.


Contact Us

Name

Email *

Message *

Popular Posts

Theoretical BER vs SNR for BPSK

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 Rate (BER) The probability of error (BER) for BPSK is given by a function called the Q-function. The Q-function Q(x) measures the tail probability of the normal distribution, i.e., the probability that a Gaussian random variable exceeds a certain value x.  Formula for BER: BER=Q(...
Read more

MATLAB code for BER vs SNR for M-QAM, M-PSK, QPSk, BPSK, ...

Modulation Constellation Diagrams BER vs. SNR MATLAB code for BER vs SNR for M-QAM, M-PSK, QPSk, BPSK, ...   MATLAB Script for  BER vs. SNR for M-QAM, M-PSK, QPSk, BPSK %Written by Salim Wireless %Visit www.salimwireless.com for study materials on wireless communication %or, if you want to learn how to code in MATLAB clc; clear; close all; % Parameters num_symbols = 1e5; % Number of symbols snr_db = -20:2:20; % Range of SNR values in dB % PSK orders to be tested psk_orders = [2, 4, 8, 16, 32]; % QAM orders to be tested qam_orders = [4, 16, 64, 256]; % Initialize BER arrays ber_psk_results = zeros(length(psk_orders), length(snr_db)); ber_qam_results = zeros(length(qam_orders), length(snr_db)); % BER calculation for each PSK order and SNR value for i = 1:length(psk_orders) psk_order = psk_orders(i); for j = 1:length(snr_db) % Generate random symbols data_symbols = randi([0, psk...
Read more

Channel Estimation utilizing Decision Feedback Equalizer (DFE)

  Channel estimation using DFE is a similar process to a non-linear equalization process. In DFE (decision feed equalizer), equalization error bits/symbols between the feedforward tabs and feedback taps are calculated continuously. And equalizer's tap weights tap weights are updated correspondingly.  In plain language, the error between the received bits and known training bits is calculated, and tap weights are updated accordingly. The equalizer estimates the channel impulse response (CIR) .  Once we find the channel impulse response or channel information, we can easily retrieve the original message signal from the noisy data. In the communication process, the whole system is modeled as a linear time-invariant (LTI) system. And  y = h*x + n where, y = received signal            x = transmitted signal           n = additive white Gaussian noise [Read more about the Linear time-invariant (LTI) system and convolu...
Read more

BER vs SNR for M-ary QAM, M-ary PSK, QPSK, BPSK, ...

Modulation Constellation Diagrams BER vs. SNR BER vs SNR for M-QAM, M-PSK, QPSk, BPSK, ... 1. 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. It is defined as,  In mathematics, BER = (number of bits received in error / total number of transmitted bits)  On the other hand, SNR refers to the signal-to-noise power ratio. For ease of calculation, we commonly convert it to dB or decibels.   2. What is Signal the signal-to-noise ratio (SNR)? SNR = signal power/noise power (SNR is a ratio of signal power to noise power) SNR (in dB) = 10*log(signal power / noise power) [base 10] For instance, the SNR for a given communication system is 3dB. So, SNR (in ratio) = 10^{SNR (in dB) / 10} = 2 Therefore, in this instance,...
Read more

MATLAB Codes for Various types of beamforming | Beam Steering, Digital...

Beamforming Techniques MATLAB Codes for Beamforming... The mathematical [↗] and theoretical aspects of beamforming [↗] have already been covered. We'll talk about coding in MATLAB in this tutorial so that you may generate results for different beamforming approaches. Let's go right to the content of the article. In analog beamforming, certain codebooks are employed on the TX and RX sides to select the best beam pairs. Because of their beamforming gains, communication created through the strongest beams from both the TX and RX side enhances spectrum efficiency. Additionally, beamforming gain directly impacts SNR improvement. Wireless communication system capacity = bandwidth*log2(1+SNR) bits/s. Thus, the capacity or overall throughput of the system increases. MATLAB Script %Written by Salim Wireless %Visit www.salimwireless.com for study materials on wireless communication %or, if you want to learn how to code in MATLAB clear all;...
Read more

Constellation Diagrams of ASK, PSK, and FSK

Modulation ASK, FSK & PSK Constellation 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: +√Eb​ or -√Eb (they differ by 180 degree phase shift), where Eb​ is the energy per bit. These signals represent binary 0 and 1.  This article will primarily discuss constellation diagrams, as well as what constellation diagrams tell us and the significance of constellation diagrams. Constellation diagrams can often demonstrate how the amplitude and phase of signals or symbols differ. These two characteristics lessen the interference between t...
Read more

Hybrid Beamforming | Page 1

Beamforming Techniques Hybrid Beamforming... Page 1 | Page 2 | Hybrid Beamforming: Hybrid beam formation was developed to address some of the limitations of digital pre-coding approaches. Every antenna element is connected to an RF chain in digital pre-coding (beam forming) method. We also know that each RF chain is in charge of providing a separate data stream between the transmitter and the receiver. We know that a larger number of independent data streams leads to higher data rates. It has a spatial multiplexing feature for MIMO. As a result, we may assume that switching from MIMO to massive MIMO will benefit us more in terms of spatial multiplexing in massive MIMO, where each antenna is coupled to a single RF chain. We'll proceed with a definition of hybrid beam forming. Overview of hybrid beam forming with example: Unlike digital beam forming, more than one antenna element is connected to a single RF chain in hybr...
Read more

Constellation Diagram of PSK in Detail

        Fig 1: Constellation Diagram of PSK    In the above figure, the binary bit '1' is represented by S1(t) and the binary bit '0' by S2(t), respectively. So, energy of S1(t) = (√(Eb))2 = Eb So, energy of S2(t) = (-√(Eb))2 = Eb Distance between the signaling points, d12 = 2(√(Eb))   Energy per bit for binary '1' and binary '0'           High-order PSK (e.g., 8 PSK, 16 PSK) can transmit more bits per symbol but is more sensitive to noise. Low-order PSK (e.g., BPSK, QPSK) is less susceptible to noise. PSK modulation can be visualized using a constellation diagram, where each point represents a symbol. In the presence of noise, points may be away from the original positions, making them harder to distinguish.  
Read more