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

• 📘 Overview & Theory
• 🧮 MATLAB Code for BPSK, QPSK, 8-PSK, 16-PSK, 32-PSK
• 🧮 Simulator for m-ary PSK
• 📚 Further Reading

 

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

clc; clear all; close all; rng(10) M = 8; % M = 2, 4, 8, 16, 32, etc. N_Bits = 2520; Phase = 0; data_info_bit = randi([0,1],N_Bits,1); data_temp = bi2de(reshape(data_info_bit,N_Bits/log2(M),log2(M))); modData = pskmod(data_temp,M,Phase); figure(1); scatterplot(modData); channelAWGN = 15; rxData2 = awgn(modData, channelAWGN); figure(2); scatterplot(rxData2); demodData = pskdemod(rxData2,M,Phase);  

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 

 

 

 

(Get MATLAB Code)

 

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.

Return to Modulation Techniques Main Page →

Try Interactive Online Simulators

1. Advanced M-ary PSK Simulator: Constellation, min dist, Efficiency, SER, EVM (RMS)
2. Interactive BER vs SNR Simulator for m-ary PSK & QAM

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:

P_s ≈ 2Q( √(2E_s/N₀) sin(π/M) )

Where E_s/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

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

1. Theoretical BER vs SNR for m-ary PSK and QAM
2. MATLAB Code for BER performance of QPSK with BPSK, 4-QAM, 16-QAM, 64-QAM, 256-QAM, etc
3. MATLAB code for BER vs SNR for M-QAM, M-PSK, QPSk, BPSK, ...