Skip to main content

Constellation Diagram of PSK in Detail (with Simulator)


 


 

 

 

 
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' (Tb = bit duration)

** For Transmission of binary ‘1’:
$E_b = \int_{0}^{T_b} (A_c \cos(2\Pi f_c t))^2 dt$
$= \int_{0}^{T_b} \frac{(A_c)^2}{2} dt + \int_{0}^{T_b} \frac{(A_c)^2 \cos(4\Pi f_c t)}{2} dt$
$= \int_{0}^{T_b} \frac{(A_c)^2}{2} dt + 0$ (The integral of $\cos(4\Pi f_c t)$ over a complete cycle is zero)
$= \frac{(A_c)^2}{2} \cdot T_b$
From this, $A_c = \sqrt{\frac{2E_b}{T_b}}$

** For Transmission of binary ‘0’:
$E_b = \int_{0}^{T_b} (-A_c \cos(2\Pi f_c t))^2 dt$
$= \int_{0}^{T_b} \frac{(A_c)^2}{2} dt + \int_{0}^{T_b} \frac{(A_c)^2 \cos(4\Pi f_c t)}{2} dt$
$= \int_{0}^{T_b} \frac{(A_c)^2}{2} dt + 0$ (The integral of $\cos(4\Pi f_c t)$ over a complete cycle is zero)
$= \frac{(A_c)^2}{2} \cdot T_b$
From this, $A_c = \sqrt{\frac{2E_b}{T_b}}$

** Constellation Diagram Representation:
For binary '1': $S_1(t) = A_c \cos(2\Pi f_c t) = \sqrt{\frac{2E_b}{T_b}} \cos(2\Pi f_c t) = \sqrt{E_b} \cdot \sqrt{\frac{2}{T_b}} \cos(2\Pi f_c t)$
For binary '0': $S_2(t) = -A_c \cos(2\Pi f_c t) = -\sqrt{\frac{2E_b}{T_b}} \cos(2\Pi f_c t) = -\sqrt{E_b} \cdot \sqrt{\frac{2}{T_b}} \cos(2\Pi f_c t)$

 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. 

Further Reading




Contact Us

Name

Email *

Message *

Popular Posts

Online Simulator for ASK, FSK, and PSK Signal Generation

Interactive Digital Signal Processing (DSP) Tutorial and Simulator for ASK, FSK, and BPSK modulation techniques. Try our new Digital Signal Processing Simulator!   •   Interactive ASK, FSK, and BPSK tools updated for 2025. Start Now Digital Modulation Visualizer: ASK, FSK, & BPSK Simulator Learn and visualize binary modulation techniques (ASK, FSK, BPSK) in real-time with adjustable carrier and sampling parameters. Perfect for DSP students and engineers. 📡 ASK Simulator 📶 FSK Simulator 🎚️ BPSK Simulator 📚 More Topics ASK Modulator FSK Modulator BPSK Modulator Demodulation More Topics 1. ASK (Ampli...

UGC NET Electronic Science Previous Year Question Papers with Solutions

Download Papers and Solutions Exam Pattern Preparation Tips FAQs More Home / Engineering & Other Exams / UGC NET 2026 PYQ 📊 Exam Highlights: Electronic Science (88) Feature Details Junior Research Fellowship (JRF) ₹37,000 + HRA per month Eligibility M.Sc/M.Tech in Electronics (55%) Validity of Certificate JRF (3 Years) | Lectureship (Lifetime) 📥 Download UGC NET Electronics PDFs Complete collection of previous year question papers, answer keys and explanations for Subject Code 88. Start Downloading 📂 View All Question Papers June 2025 - Question Paper Download PDF June 2025 - Sol...

Direction of Arrival (DoA) Online Simulator (using MUSIC)

Interactive DOA Simulator X-axis XY angle (deg): 45 XZ angle (deg): 30 Noise: 0.05 Y-axis XY angle (deg): 60 YZ angle (deg): 45 Noise: 0.05 Z-axis XZ angle (deg): 60 YZ angle (deg): 30 Noise: 0.05 Estimated DOA (deg): 0 Simulation Workflow and Mathematical Background This simulator demonstrates Direction of Arrival (DOA) estimation using three-axis sensor signals (X, Y, Z), Maximal Ratio Combining (MRC) , and the MUSIC algorithm . It allows interactive control of signal angles and noise for teaching purposes. 1. Signal Generation A pure sinewave signal of frequency f is projected onto three axes using user-defined angles in different planes: X-axis: θ XY , θ XZ Y-axis: θ XY , θ YZ Z-axis: θ XZ , θ YZ Mathematically, for each time sample t : x(t) = s(t) * cos(θ_xy_x) * cos(θ_xz_x) + n_x(t) y(t) = s(t) * sin(θ_xy_y) * cos(θ_yz_y) + n_y(t) z(t) = s(t) * sin(θ_xz_z) * sin(θ_yz_z) + n_z(t) wh...

Constellation Diagrams of ASK, PSK, and FSK (with MATLAB Code + Simulator)

Constellation Diagrams: ASK, FSK, and PSK Comprehensive guide to signal space representation, including interactive simulators and MATLAB implementations. 📘 Overview 🧮 Simulator ⚖️ Theory 📈 Q-function 📚 Resources BASK Modulation Transmits one of two signals: 0 or $\sqrt{E_b}$, representing binary 0 and 1. Simple but sensitive to noise. BFSK Modulation Transmits one of two signals: $\sqrt{E_b}$ on the Y-axis or $\sqrt{E_b}$ on the X-axis. These are orthogonal signals. BPSK Modulation Transmits $+\sqrt{E_b}$ or $-\sqrt{E_b}$ (antipodal signaling). Most efficient binary scheme. ...

OFDM Symbols and Subcarriers Explained

This article explains how OFDM (Orthogonal Frequency Division Multiplexing) symbols and subcarriers work. It covers modulation, mapping symbols to subcarriers, subcarrier frequency spacing, IFFT synthesis, cyclic prefix, and transmission. Step 1: Modulation First, modulate the input bitstream. For example, with 16-QAM , each group of 4 bits maps to one QAM symbol. Suppose we generate a sequence of QAM symbols: s0, s1, s2, s3, s4, s5, …, s63 Step 2: Mapping Symbols to Subcarriers Assume N sub = 8 subcarriers. Each OFDM symbol in the frequency domain contains 8 QAM symbols (one per subcarrier): Mapping (example) OFDM symbol 1 → s0, s1, s2, s3, s4, s5, s6, s7 OFDM symbol 2 → s8, s9, s10, s11, s12, s13, s14, s15 … OFDM sym...

MATLAB Code for MUSIC

  MATLAB Code clc; clear; close all ; %% Step 1: Define Parameters M = 8; % Number of array sensors d = 0.5; % Sensor spacing (lambda/2) K = 2; % Number of signals N = 200; % Number of snapshots theta = [-20 30]; % True signal angles (degrees) SNR = 10; % Signal-to-noise ratio (dB) fprintf( 'Step 1: Parameters Initialized\n' ); %% Step 2: Generate Signal Sources t = 1:N; s1 = exp(1j*2*pi*0.05*t); s2 = exp(1j*2*pi*0.1*t); S = [s1; s2]; figure; plot(real(S(1,:))) title( 'Signal 1 (Real Part)' ) xlabel( 'Samples' ) ylabel( 'Amplitude' ) figure; plot(real(S(2,:))) title( 'Signal 2 (Real Part)' ) xlabel( 'Samples' ) ylabel( 'Amplitude' ) fprintf( 'Step 2: Source Signals Generated\n' ); %% Step 3: Construct Steering Matrix A = zeros(M,K); for k = 1:K A(:,k) = exp(-1j*2*pi*d*(0:M-1)'*sin(theta(k)*pi/180)); end fprintf( 'Step 3: Steering Matr...