Skip to main content

MATLAB code for Constellation Diagram of QPSK



MATLAB Script

% QPSK Modulation and Demodulation

% Define input data
data = [1 1 0 1 0 1 0 0 1 0]; % Information

% Modulation
M = 4; % Number of symbols
k = log2(M); % Number of bits per symbol
bits_per_symbol = length(data) / k;
data_reshaped = reshape(data, k, bits_per_symbol)';
symbol = bi2de(data_reshaped, 'left-msb')';

% Generate QPSK modulation symbols
modulated_signal = pskmod(symbol, M, pi/4); % Phase offset pi/4 for QPSK

% AWGN Channel (Additive White Gaussian Noise)
EbNo = 10; % Energy per bit to noise power spectral density ratio (dB)
SNR = EbNo + 10*log10(k); % Signal to Noise Ratio (dB)
rx_signal = awgn(modulated_signal, SNR, 'measured');

% Demodulation
demodulated_signal = pskdemod(rx_signal, M, pi/4); % Phase offset pi/4 for QPSK

% Convert symbols to bits
demodulated_bits = de2bi(demodulated_signal, k, 'left-msb')';
received_data = reshape(demodulated_bits', 1, []);

% Plot original and received data
figure;
subplot(2,1,1);
stem(data, 'linewidth', 2);
title('Original Data');
xlabel('Bit');
ylabel('Amplitude');
axis([0 length(data) 0 1.5]);

subplot(2,1,2);
stem(received_data, 'linewidth', 2);
title('Received Data');
xlabel('Bit');
ylabel('Amplitude');
axis([0 length(received_data) 0 1.5]);

% Scatter plot
demodulated_symbols = demodulated_signal; % Replace with your demodulated symbols

% Map demodulated symbols to complex constellation points
constellation_points = [1+1i, -1+1i, -1-1i, 1-1i]; % QPSK constellation points
figure()
scatter(real(constellation_points(demodulated_symbols+1)), imag(constellation_points(demodulated_symbols+1)));
title('QPSK Constellation Diagram');
xlabel('In-phase Component');
ylabel('Quadrature Component');
axis([-2 2 -2 2]); % Adjust axis limits if needed
grid on;

    

Output

QPSK Modulation and Demodulation Result
Fig 1: QPSK Modulation and Demodulation
QPSK Constellation Diagram
Fig 2: Constellation Diagram of QPSK

Further Reading

  1. Quadrature Phase Shift Keying (QPSK) (Theory)
  2. MATLAB Code for QPSK Modulation and Demodulation
  3. Constellation Diagrams of ASK, FSK, and PSK
  4. MATLAB Code for Constellation Diagrams of ASK, FSK, and PSK

People are good at skipping over material they already know!

View Related Topics to







Contact Us

Name

Email *

Message *

Popular Posts

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 ...

MATLAB Code for ASK, FSK, and PSK

📘 Overview & Theory 🧮 MATLAB Code for ASK 🧮 MATLAB Code for FSK 🧮 MATLAB Code for PSK 🧮 Simulator for binary ASK, FSK, and PSK Modulations 📚 Further Reading ASK, FSK & PSK HomePage MATLAB Code MATLAB Code for ASK Modulation and Demodulation % The code is written by SalimWireless.Com % Clear previous data and plots clc; clear all; close all; % Parameters Tb = 1; % Bit duration (s) fc = 10; % Carrier frequency (Hz) N_bits = 10; % Number of bits Fs = 100 * fc; % Sampling frequency (ensure at least 2*fc, more for better representation) Ts = 1/Fs; % Sampling interval samples_per_bit = Fs * Tb; % Number of samples per bit duration % Generate random binary data rng(10); % Set random seed for reproducibility binary_data = randi([0, 1], 1, N_bits); % Generate random binary data (0 or 1) % Initialize arrays for continuous signals t_overall = 0:Ts:(N_bits...

Constellation Diagrams of ASK, PSK, and FSK

📘 Overview of Energy per Bit (Eb / N0) 🧮 Online Simulator for constellation diagrams of ASK, FSK, and PSK 🧮 Theory behind Constellation Diagrams of ASK, FSK, and PSK 🧮 MATLAB Codes for Constellation Diagrams of ASK, FSK, and PSK 📚 Further Reading 📂 Other Topics on Constellation Diagrams of ASK, PSK, and FSK ... 🧮 Simulator for constellation diagrams of m-ary PSK 🧮 Simulator for constellation diagrams of m-ary QAM 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...

MATLAB Code for Rms Delay Spread

RMS delay spread is crucial when you need to know how much the signal is dispersed in time due to multipath propagation, the spread (variance) around the average. In high-data-rate systems like LTE, 5G, or Wi-Fi, even small time dispersions can cause ISI. RMS delay spread is directly related to the amount of ISI in such systems. RMS Delay Spread [↗] Delay Spread Calculator Enter delays (ns) separated by commas: Enter powers (dB) separated by commas: Calculate   The above calculator Converts Power to Linear Scale: It correctly converts the power values from decibels (dB) to a linear scale. Calculates Mean Delay: It accurately computes the mean excess delay, which is the first moment of the power delay profile. Calculates RMS Delay Spread: It correctly calculates the RMS delay spread, defined as the square root of the second central moment of the power delay profile.   MATLAB Code  clc...

Periodogram in MATLAB

Power Spectral Density Estimation Using the Periodogram Step 1: Signal Representation Let the signal be x[n] , where: n = 0, 1, ..., N-1 (discrete-time indices), N is the total number of samples. Step 2: Compute the Discrete-Time Fourier Transform (DTFT) The DTFT of x[n] is: X(f) = ∑ x[n] e -j2Ï€fn For practical computation, the Discrete Fourier Transform (DFT) is used: X[k] = ∑ x[n] e -j(2Ï€/N)kn , k = 0, 1, ..., N-1 k represents discrete frequency bins, f_k = k/N * f_s , where f_s is the sampling frequency. Step 3: Compute Power Spectral Density (PSD) The periodogram estimates the PSD as: S_x(f_k) = (1/N) |X[k]|² S_x(f_k) ...

Coherence Bandwidth and Coherence Time

🧮 Coherence Bandwidth 🧮 Coherence Time 🧮 MATLAB Code s 📚 Further Reading For Doppler Delay or Multi-path Delay Coherence time T coh ∝ 1 / v max (For slow fading, coherence time T coh is greater than the signaling interval.) Coherence bandwidth W coh ∝ 1 / Ï„ max (For frequency-flat fading, coherence bandwidth W coh is greater than the signaling bandwidth.) Where: T coh = coherence time W coh = coherence bandwidth v max = maximum Doppler frequency (or maximum Doppler shift) Ï„ max = maximum excess delay (maximum time delay spread) Notes: The notation v max −1 and Ï„ max −1 indicate inverse proportionality. Doppler spread refers to the range of frequency shifts caused by relative motion, determining T coh . Delay spread (or multipath delay spread) determines W coh . Frequency-flat fading occurs when W coh is greater than the signaling bandwidth. Coherence Bandwidth Coherence bandwidth is...

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

📘 Comparisons among ASK, FSK, and PSK 🧮 Online Simulator for calculating Bandwidth of ASK, FSK, and PSK 🧮 MATLAB Code for BER vs. SNR Analysis of ASK, FSK, and PSK 📚 Further Reading 📂 View Other Topics on Comparisons among ASK, PSK, and FSK ... 🧮 Comparisons of Noise Sensitivity, Bandwidth, Complexity, etc. 🧮 MATLAB Code for Constellation Diagrams of ASK, FSK, and PSK 🧮 Online Simulator for ASK, FSK, and PSK Generation 🧮 Online Simulator for ASK, FSK, and PSK Constellation 🧮 Some Questions and Answers 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 Parameters ASK FSK PSK Variable Characteristics Amplitude Frequency ...

Difference between AWGN and Rayleigh Fading

📘 Introduction, AWGN, and Rayleigh Fading 🧮 Simulator for the effect of AWGN and Rayleigh Fading on a BPSK Signal 🧮 MATLAB Codes 📚 Further Reading Wireless Signal Processing Gaussian and Rayleigh Distribution Difference between AWGN and Rayleigh Fading 1. Introduction Rayleigh fading coefficients and AWGN, or Additive White Gaussian Noise (AWGN) in Wireless Channels , are two distinct factors that affect a wireless communication channel. In mathematics, we can express it in that way. Fig: Rayleigh Fading due to multi-paths Let's explore wireless communication under two common noise scenarios: AWGN (Additive White Gaussian Noise) and Rayleigh fading. y = h*x + n ... (i) Symbol '*' represents convolution. The transmitted signal x is multiplied by the channel coeffic...