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MATLAB Code for Rank and Condition Number of a Channel Matrix

To assess the signal strengths of various multipaths between TX and RX and enable communication, the rank and condition numbers of a channel matrix are highly helpful characteristics. Signal multipath propagation is a typical occurrence in wireless communication. Phases shift and the signal weakens during this process. We are discussing signal phases in this context. When numerous multipaths arrive at the receiver, the resulting signal may be additive or destructive because of phase alterations. A channel matrix is referred to as a sparse matrix if it only has a few stronger elements and the majority of the other elements are zero. Finding rank and condition number for sparse matrices is important for numerous reasons. That topic has already been covered in another article [ click here ]. We will just talk about the corresponding MATLAB codes here. MATLAB Code for Rank and Condition Number of a Channel Matrix %Author: Salim Wireless For study materials on wireless %com...
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Simulation of ASK, FSK, and PSK using MATLAB Simulink

ASK, FSK & PSK HomePage MATLAB Simulation Simulation of Amplitude Shift Keying (ASK) using MATLAB Simulink      In Simulink, we pick different components/elements from MATLAB Simulink Library. Then we connect the components and perform a particular operation.  Result A sine wave source, a pulse generator, a product block, a mux, and a scope are shown in the diagram above. The pulse generator generates the '1' and '0' bit sequences. Sine wave sources produce a specific amplitude and frequency. The scope displays the modulated signal as well as the original bit sequence created by the pulse generator. Mux is a tool for displaying both modulated and unmodulated signals at the same time. The result section shows that binary '1' is modulated by a certain sine wave amplitude of 1 Volt, and binary '0' is modulated by zero amplitude. Simulation of Frequency Shift Keying (FSK) using MATLAB Simulink   Result The diagram above shows t...
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MATLAB Code for QAM (Quadrature Amplitude Modulation)

  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 modulation, signal set (or, symbols) is structured in a way that prevents them from interacting further by being distinct by phase, amplitude, or frequency. MATLAB Script % This code is written by SalimWirelss.Com % This is an example of 4-QAM. Here constellation size is 4 % or total number of symbols/signals is 4 % We need 2 bits once to represent four constellation points % QAM modulation is the combination of Amplitude modulation plus % Phase Modulation. We map the decimal value of the input symbols, i.e., % 00, 01, 10, 11 to 1 + 1i, -1 + 1i, 1 - 1i, and -1 - 1i, respectively. clc;clear all;...
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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,...
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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...
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  (Search any topic) Search any topic on the whole website Modulation Signal Processing Beamforming MATLAB 5G Wireless GATE-ESE-NET Programming Telecommunication Channel Impulse Response Computer Networks MIMO - Multiple Input Multiple Output Filters Millimeter wave Python   Constellation Diagrams BER vs SNR Electronics Industry Fourier Series and Fourier Transform Frequency bands Wireless Communication Q & A ASK FSK PSK Channel Model IoTs UWB pskmod Antenna Applications and Games C Programming Channel Estimation Equalizers Gaussian Random Variable Projects Q & A QAM Transform Fading Microwave News about 5G PAM Python Matrix Operations SSC Exam Web Design WordPress Ionospheric Communication JavaScript MATLAB Simulink Mobile & Accessories OFDM Signal Processing for 5G Analog Circuits Cell Towers Computer Digital Circuits Fourier Series HomePage Information and Coding Theory Laplace Transform MySQL Node.js Search ShareLinkF / Generate QR Z Transform ...
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Star to Delta Conversion and Vice Versa | star delta conversion

The transformation of a star to a delta and a delta to a star circuit is a hot topic in electrical science and engineering. Examiners often ask about the conversion of star to delta and delta to star circuit diagram. When solving complex circuits, the conversion procedure can sometimes ease calculations and save time. Without further ado, we'll go over the characteristics of both a star and a delta circuit. As its title suggests, the star circuit looks like a star. Delta circuit, on the other hand, looks like a delta. Now we'll look at the mathematical method for converting delta to star and star to delta. Delta to Star R1 = RaRb / (Ra + Rb + Rc) R2 = RbRc / (Ra + Rb + Rc) R3 = RaRc / (Ra + Rb + Rc) Use star to delta online converter and vice versa Star to Delta Ra = (R1R2 + R2R3 + R3R1) / R2 Rb = (R1R2 + R2R3 + R3R1) / R3 Rc = (R1R2 + R2R3 + R3R1) / R1 Next Page>>
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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...
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