Skip to main content
Home Wireless Communication Modulation MATLAB Beamforming Project Ideas MIMO Computer Networks Lab 🚀

Sender, Source & Channel Coding, Channel, Receiver in wireless communication - step by step (2)


Modulation & Demodulation:

Wireless communication relies heavily on modulation and demodulation. By modulating with a high frequency carrier signal, we can convert the frequency of the original baseband signal to a very high frequency. Because, in many ways, a low frequency baseband signal is unsuitable for wireless communication. Modulation, on the other hand, increases channel capacity by delivering many data streams via a single channel at the same time. Because of this property of modulation, we employ it in wired communication as well. In a communication system, the modulation process is performed on the signal right before transmission from the antenna.


Signal Processing at receiver side for wireless communication:

To recover the signal, we perform the exact opposite on the receiver side. If we execute signal encoding on the transmitter side, we must also do signal decoding on the receiver side. If we modulate on the TX side, we must demodulate on the RX side, as indicated in the diagram above. At the end of process, receiver sends the feedback to the transmitter or sender so that sender can be informed whether the data packet is successfully received or not.


Acknowledgement / Feedback from Receiver Side in Wireless Communication:

It is essential to inform sender / transmitter that specific message / data packets have been received for reliable communication. For TCP transmission protocol sender sends a data packet to receiver. Then at receiver side it checks whether whole data packets have been transferred or not. If it received by receiver then it sends acknowledgement to transmitter. If not then whole packet is retransferred again.


Deep Dive:

If the source is analog in nature, we use the sampling and quantization approach to digitalize the signal. However, before transmission, we modulate the message signal with a high-frequency carrier signal. In fact, the signals that travel over a wireless channel are analog in nature. We typically don't need to apply modulation while using wired communication. We employ line coding techniques such as RZ, NRZ, duo binary, Manchester waveform, etc. to convert the digitalized signal into various waveforms. 

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

What is the Step Size in FFT?

  In FFT (Fast Fourier Transform), the step size refers to the spacing between consecutive points in the output data after performing the transform. It's often determined by the sampling rate of the signal. The step size is crucial for accurate frequency representation, and smaller step sizes provide finer frequency resolution in the resulting frequency domain representation.   Step Size of a Signal in the Time Domain Suppose you have a signal sampled at 1000 Hz (sampling rate) for a duration of 1 second. The step size, or the time difference between consecutive samples, is then given by the inverse of the sampling rate: Step size = 1/ Sampling rate = 1/ 1000   Hz = 0.001   seconds If you perform an FFT on this signal, the resulting frequency resolution in the frequency domain will be determined in part by this step size. Smaller step sizes provide a finer frequency resolution.   Step Size of a Signal in the Frequency / FFT Domain  Step Size in the Frequen

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, the signal power i

Comparisons among ASK, PSK, and FSK | And the definitions of each

Modulation ASK, FSK & PSK Constellation MATLAB Simulink MATLAB Code Comparisons among ASK, PSK, and FSK    Comparisons among ASK, PSK, and FSK Comparison among ASK,  FSK, and PSK Performance Comparison: 1. Noise Sensitivity:    - ASK is the most sensitive to noise due to its reliance on amplitude variations.    - PSK is less sensitive to noise compared to ASK.    - FSK is relatively more robust against noise, making it suitable for noisy environments. 2. Bandwidth Efficiency:    - PSK is the most bandwidth-efficient, requiring less bandwidth than FSK for the same data rate.    - FSK requires wider bandwidth compared to PSK.    - ASK's bandwidth efficiency lies between FSK and PSK. Bandwidth Calculator for ASK, FSK, and PSK The baud rate represents the number of symbols transmitted per second Select Modulation Type: ASK FSK PSK Baud Rate (Hz):

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 two signals or

Frequency Bands : EHF, SHF, UHF, VHF, HF, MF, LF, VLF and Their Uses

Frequency Bands EHF, SHF, UHF, VHF, HF, MF, LF... 1. Extremely High Frequency (EHF)30 - 300 GHz Uses 5G Networks 5G millimeter wave band , 6G and beyond (Experimental) RADAR, 2. Super High Frequency (SHF)3 - 30 GHz Uses Ultra-wideband (UWB , Airborne RADAR, Satellite Communication, Microwave Link Communication or SATCOM 3. Ultra High Frequency (UHF)300 - 3000 MHz Uses Satellite Communication, Television, surveillance, navigation aids Also, read important wireless communication terms 4. Very High Frequency (VHF)30 - 300 MHz Uses Television, FM broadcast, navigation aids, air traffic control, 5. High Frequency (HF)3 - 30 MHz Uses Telephone, Telegram and Facsimile, ship to coast, ship to aircraft communication, amateur radio, 6. Medium Frequency (MF)300 - 3000 KHz Uses coast guard communication, direction finding, AM broadcasting , maritime radio, 7. Low Frequency (LF)30 - 300 KHz Uses Radio beacons, Navigational Aids 8. Very Low Frequency (VLF)3 - 30 KHz

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_order-1]

MATLAB Code for Delta Modulation (DM) and Demodulation

  MATLAB Script  clc; clear all; close all; fs = 10000; fm = 100; t = 0:1/fs:1000/fs; % Time Duration = 1000/10000 = 0.1 second x = 5*sin(2*pi*100*t); % Define Message Signal with peak voltage 5V and frequency 100Hz plot(t, x); hold on y = [0]; % Output DM signal i.e. stream of 1 or 0 xr = 0; % Output of Integrator i.e. staircase approximation; initial value = 0 del = 0.4; % Stepsize for i = 1:length(x)-1 if xr(i) <= x(i) % If current sample greater than the previous values or output of the integrator, output of DM = 1 d = 1; xr(i+1) = xr(i) + del; % Staircase approximated value else d = 0; xr(i+1) = xr(i) - del; % If current sample less than the previous values or output of the integrator, output of DM = 0 end y = [y d]; end stairs(t, xr); % Show the staircase approximated signal title('Staircase Approximated Signal'); hold off MSE = sum((x - xr).^2) / length(x); % Mean Squared Error (MSE) disp(['Mean Squared Error (MSE): ', num2str(MSE)]); figure; % Delta M

5G Channel Estimation using Orthogonal Matching Pursuit (OMP)

5G Channel Estimation... For millimeter wave massive MIMO communication in 5G, we observe that the number of available multipath that avails communication is much smaller than the maximum connections possible between the transmitter(TX) and receiver(RX). Only a few MPCs reach at receiver with good received signal strength. For example, the number of strong MPCs that reaches the receiver is L and there is N transmitter antenna on the transmitter side and N number of antennas on the receiver side. So, from the channel matrix of the massive MIMO system, we can say the total number of available paths or connections between TX and RX is equal to, N X N or, N^(2) Now, L << N^(2) For simplicity, if the number of possible strong beams from the transmitter and receiver sides are NtBeams and NrBeams, then, L = NtBeams * NrBeams If we look up the massive MIMO channel matrix , then, H= Primarily, if the number of available MPCs to avail communication bet