Skip to main content

MATLAB Code for 8-PSK, 16-PSK, ...


 

MATLAB Code for BPSK, QPSK, 8-PSK, 16-PSK, 32-PSK


 

for BPSK, Constellation Size, M = 2
for QPSK, M = 4
for 8-PSK, M = 8, and so on 

 Output


Figure: 8-PSK Modulation




Figure: 8-PSK Demodulation after adding AWGN Noise

Using the above MATLAB code you'll able be to modulate and demodulate 2-PSK, 4-PSK, 8-PSK, 16-PSK, 32-PSK and so on. 

16-PSK

Fig: 16-PSK



In this above code 'M' is the number of the constellation points which denotes the total number of symbols or signals. You can vary the number of constellation points in the MATLAB code above. 
 

MATLAB Code for BER vs SNR for BPSK, QPSK, 8-PSK, 16-PSK, 32-PSK 

 
 

 

Real-World Applications of PSK Modulation

M-ary PSK modulation is widely used in modern telecommunications:

  • BPSK: Used in deep-space telemetry and low-cost passive RFID tags.
  • QPSK: The backbone of Satellite Television (DVB-S), cable modems, and 4G LTE control channels.
  • 8-PSK: Commonly used in the EDGE cellular network and aircraft communication systems.
  • Higher Order PSK: Used in high-speed optical fiber communications where SNR is strictly controlled.

Why are Constellation Diagrams Important?

To understand any digital modulation scheme, constellation diagrams are extremely important because they visually represent how signals vary in amplitude and phase. In the case of Phase Shift Keying (PSK), the signal amplitude remains constant while only the phase changes.

Communication engineers often analyze the distances between constellation points to evaluate the performance and efficiency of a modulation scheme. The minimum distance between constellation points directly affects the error performance of the system. For example, it is well known that PSK can provide approximately a 3 dB SNR advantage over FSK under certain conditions. This performance difference originates from the separation between constellation points and the corresponding Euclidean distance in the signal space.

Similarly, constellation point spacing plays a critical role in the performance of M-ary PSK modulation schemes. When the signal-to-noise ratio (SNR) is high, higher-order M-PSK schemes can be used to achieve greater spectral efficiency and higher data rates. However, as the modulation order increases, the angular separation between adjacent constellation points decreases, making the system more susceptible to noise and phase errors.

Therefore, in low-SNR environments, lower-order modulation schemes such as BPSK are generally preferred because their constellation points are more widely separated, resulting in better bit error rate (BER) performance and improved reliability. You can try the interactive online (web based) simulations below to understand how constellation diagram works.


Try Interactive Online Simulators


Comparison of M-PSK Modulation Schemes

Modulation M (Symbols) Bits per Symbol Noise Immunity
BPSK 2 1 Highest
QPSK 4 2 High
8-PSK 8 3 Medium
16-PSK 16 4 Low

Theoretical Bit Error Rate (BER) for m-ary PSK

For M-PSK in an AWGN channel, the symbol error probability P_s can be approximated for high SNR as:

Ps ≈ 2Q( √(2Es/N0) sin(Ï€/M) )

Where Es/N0 is the energy-to-noise density ratio and M is the modulation order.


Read More about BER vs SNR for m-ary PSK and QAM


Why Is QPSK an Important Modulation Scheme?

Quadrature Phase Shift Keying (QPSK) is an important digital modulation technique because it can transmit twice the data rate of Binary Phase Shift Keying (BPSK) while maintaining nearly the same bit error rate (BER) performance at low signal-to-noise ratio (SNR) levels when Gray coding is employed.

Compared with higher-order modulation schemes, QPSK offers a good balance between data rate, spectral efficiency, and reliability. Its spectral efficiency is comparable to that of 4-QAM and, under low-SNR conditions, it can outperform higher-order schemes such as 16-QAM in terms of robustness. In highly noisy communication channels, QPSK may even provide better overall spectral efficiency than 4-QAM or 16-QAM due to its lower error susceptibility.

As a result, QPSK is widely used in practical wireless communication systems and is often combined with QAM-based modulation techniques in adaptive modulation schemes, where the modulation order is dynamically adjusted according to channel conditions.

Read More: BER Performance Comparison of QPSK, BPSK, 4-QAM, 16-QAM, 64-QAM, and 256-QAM Using MATLAB and Simulation Tools (Click Here →)


Frequently Asked Questions

Q1: Why does the constellation plot look blurry at low SNR? A: At low SNR, the noise power is high, causing the received symbols to deviate significantly from their ideal positions.
Q2: Can I use this code for M=64? A: Yes, the pskmod function supports any power of 2 for M, but note that 64-PSK is rarely used in practice because QAM is more efficient for such high orders.


Further Reading

Contact Us

Name

Email *

Message *

Popular Posts

Online Simulator for ASK, FSK, and PSK

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 More Topics 1. ASK (Amplitude Shift Keying) Simulat...

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

Bit Error Rate (BER) & SNR Guide Analyze communication system performance with our interactive simulators and MATLAB tools. 📘 Theory 🧮 Simulators 💻 MATLAB Code 📚 Resources BER Definition SNR Formula BER Calculator MATLAB Comparison 📂 Explore M-ary QAM, PSK, and QPSK Topics ▼ 🧮 Constellation Simulator: M-ary QAM 🧮 Constellation Simulator: M-ary PSK 🧮 BER calculation for ASK, FSK, and PSK 🧮 Approaches to BER vs SNR What is Bit Error Rate (BER)? The BER indicates how many corrupted bits are received compared to the total number of bits sent. It is the primary figure of merit f...

Q-function in BER vs SNR Calculation

Q-function in BER vs. SNR Calculation | Interactive Guide Q-function in BER vs. SNR Calculation In digital communications and signal processing, the Q-function plays a significant role in predicting system reliability. It allows engineers to quantify the probability that Gaussian noise will exceed a specific threshold, causing a bit error. What is the Q-function? The Q-function is a mathematical function representing the tail probability of the standard normal (Gaussian) distribution. It is the complementary cumulative distribution function (CCDF) of a standard Gaussian distribution. Q(x) = (1 / √(2Ï€)) ∫â‚“∞ e^(-t² / 2) dt Q-Function Interactive Simulator Move the slider to see how the "Tail Probability" (the area in red) changes. This area represents the Probability of Error (BER) . Threshold Distance ( x ) — (Simulates Increasing SNR) ...

UGC NET Electronic Science Previous Year Question Papers with Solutions

Home / Engineering & Other Exams / UGC NET 2026 PYQ ⬇️ Download Papers and Solutions 📋 Exam Pattern 💡 Preparation Tips ❓ FAQs 📊 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 - Solved Paper + Explanation ...

MATLAB Code for ASK, FSK, and PSK (with Online Simulator)

MATLAB Code for ASK, FSK, and PSK Comprehensive implementation of digital modulation and demodulation techniques with simulation results. 📘 Theory 📡 ASK Code 📶 FSK Code 🎚️ PSK Code 🕹️ Simulator 📚 Further Reading Amplitude Shift Frequency Shift Phase Shift Live Simulator ASK, FSK & PSK HomePage MATLAB Code MATLAB Code for ASK Modulation and Demodulation COPY % The code is written by SalimWireless.Com clc; clear all; close all; % Parameters Tb = 1; fc = 10; N_bits = 10; Fs = 100 * fc; Ts = 1/Fs; samples_per_bit = Fs * Tb; rng(10); binar...

DFTs-OFDM vs OFDM: Why DFT-Spread OFDM Reduces PAPR Effectively (with MATLAB Code)

Understanding PAPR in DFT-spread OFDM vs. Standard OFDM In modern wireless communications like 4G LTE and 5G NR, managing the Peak-to-Average Power Ratio (PAPR) is critical for hardware efficiency. While OFDM is the gold standard for high-speed data, its high PAPR poses significant challenges for mobile devices. This is where DFTs-OFDM (also known as SC-FDMA) comes in. DFT-spread OFDM (DFTs-OFDM) has lower Peak-to-Average Power Ratio (PAPR) because it "spreads" the data in the frequency domain before applying IFFT, making the time-domain signal behave more like a single-carrier signal rather than a multi-carrier one like OFDM. Deeper Explanation: Aspect OFDM DFTs-OFDM Signal Type Multi-carrier Single-carrier-like Process IFFT of QAM directly QAM → DFT → IFFT PAPR Level High (due to many...

Comparisons among ASK, PSK, and FSK (with MATLAB + Simulator)

Modulation ASK, FSK & PSK Constellation MATLAB Simulink MATLAB Code Comparisons among ASK, PSK, and FSK 📘 Comparisons among ASK, FSK, and PSK 🧮 Online Simulator Bandwidth 🧮 MATLAB Code BER Analysis 📚 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 Comparisons among ASK, PSK, and FSK Comparison among ASK, FSK, and PSK Parameters ASK FSK PSK Variable Characteristics Amplitude ...

Which of the following statements are correct? A. If the intermediate frequency is too high, poor selectivity results even if sharp cutoff filters are used in the IF stage.

  61) Which of the following statements are correct?  A. If the intermediate frequency is too high, poor selectivity results even if sharp cutoff filters are used in the IF stage.  B. A high value of intermediate frequency increases tracking difficulties.  C. As the intermediate frequency is lowered, image frequency rejection becomes better.  D. A very low intermediate frequency can make the selectivity too sharp.  Choose the correct answer from the options given below:  1. A and B only [Option ID = 3073]  2. B and C only [Option ID = 3074]  3. C and D only [Option ID = 3075]  4. B and D only [Option ID = 3076 Answer: 4  Previous yr Question papers with Full Explanations → Electronics and Communiaction Study Materials → Try Interactive Online Simulator Run the Simulation The Superheterodyne Principle The...