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India: Delhi, Kolkata, Mumbai, Chennai, Gurugram, Ahmedabad, Chandigarh, Gandhinagar, Hyderabad, Jamnagar, Bengaluru, Lucknow, and Pune

Qatar: Doha, Umm Şalāl Muḩammad, Ar Rayyān, Al Wakrah, Al Khawr, Ash Shaḩānīyah, Umm Sa‘īd, Dukhān, Madīnat ash Shamāl, Al Wukayr, Ar Ru’ays, Umm Bāb, Al Ghuwayrīyah, Fuwayri, Al Jumaylīyahţ


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Rayleigh vs Rician Fading (with MATLAB + Simulator)

  In Rayleigh fading , the channel coefficients tend to have a Rayleigh distribution, which is characterized by a random phase and magnitude with an exponential distribution. This means the magnitude of the channel coefficient follows an exponential distribution with a mean of 1. In Rician fading , there is a dominant line-of-sight component in addition to the scattered components. The channel coefficients in Rician fading can indeed tend towards 1, especially when the line-of-sight component is strong. When the line-of-sight component dominates, the Rician fading channel behaves more deterministically, and the channel coefficients may tend towards the value of the line-of-sight component, which could be close to 1.   MATLAB Script clc; clear all; close all; % Define parameters numSamples = 1000; % Number of samples K_factor = 5; % K-factor for Rician fading SNR_dB = 20; % Signal-to-noise ratio (in dB) % Generate complex Gaussian random variable for Rayleigh fading channel h_r...

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

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UGC NET Electronic Science Previous Year Question Papers

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

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UGC-NET Electronic Science Question Paper With Answer Key and Full Explanation [Dec 2023]

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Online Simulator for ASK, FSK, and PSK

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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; snr_db = -5:2:25; 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) ber_psk_results(i, :) = berawgn(snr_db, 'psk', psk_orders(i), 'nondiff'); end for i = 1:length(qam_orders) ber_qam_results(i, :) = berawgn(snr_db, 'qam', qam_orders(i)); end figure; semilogy(snr_db, ber_psk_results(1, :), 'o-', 'LineWidth', 1.5, 'DisplayName', 'BPSK'); hold on; for i = 2:length(psk_orders) semilogy(snr_db, ber_psk_results(i, :), 'o-', 'DisplayName', sprintf('%d-PSK', psk_orde...

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