Skip to main content

MATLAB code for MSK



 Copy the MATLAB Code from here

 

MATLAB Code 

clc;
clear;
close all;

% Define a bit sequence
bitSeq = [0, 1, 0, 0, 1, 1, 1, 0, 0, 1];

% Perform MSK modulation
[modSignal, timeVec] = modulateMSK(bitSeq, 10, 10, 10000);

% Plot the modulated signal
subplot(2,1,1);
samples = 1:numel(bitSeq);
stem(samples, bitSeq);
title('Original message signal');
xlabel('Time (s)');
ylabel('Amplitude');

% Plot the modulated signal
subplot(2,1,2);
samples = 1:10000;
plot(samples / 10000, modSignal(1:10000));
title('MSK modulated signal');
xlabel('Time (s)');
ylabel('Amplitude');

% Perform MSK demodulation
demodBits = demodMSK(modSignal, 10, 10, 10000);

% Function to perform MSK modulation
function [signal, timeVec] = modulateMSK(bits, carrierFreq, baudRate, sampleFreq)
% Converts a binary bit sequence into an MSK-modulated signal
% Inputs:
% bits - Binary input sequence
% carrierFreq - Carrier frequency
% baudRate - Symbol rate
% sampleFreq - Sampling frequency
% Outputs:
% signal - Modulated MSK signal
% timeVec - Corresponding time vector

% Convert bits to NRZ format (-1, 1)
diffEncBits = 2 * bits - 1;
diffEncBits = [-1, diffEncBits]; % Append initial value

% Define time parameters
numBits = length(bits);
symbDur = 1 / baudRate;
timeVec = 0:1/sampleFreq:numBits * symbDur - (1/sampleFreq);

% Compute phase shifts
phaseShift = zeros(1, numBits + 1);
for idx = 2:numBits+1
phaseShift(idx) = mod(phaseShift(idx-1) + ((pi * idx) / 2) * (diffEncBits(idx-1) - diffEncBits(idx)), 2 * pi);
end
phaseShift = phaseShift(2:end);
diffEncBits = diffEncBits(2:end);

% Generate MSK waveform
symbolIdx = floor(timeVec / symbDur) + 1;
signal = cos(2 * pi * (carrierFreq + diffEncBits(symbolIdx) / (4 * symbDur)) .* timeVec + phaseShift(symbolIdx));
end

% Function to perform MSK demodulation
function bitSeq = demodMSK(signal, carrierFreq, baudRate, sampleFreq)
% Recovers a binary bit sequence from an MSK-modulated signal
% Inputs:
% signal - MSK-modulated input signal
% carrierFreq - Carrier frequency
% baudRate - Symbol rate
% sampleFreq - Sampling frequency
% Outputs:
% bitSeq - Demodulated binary sequence

symbDur = 1 / baudRate;
samplesPerSymbol = round(symbDur * sampleFreq);
numSamples = length(signal);

% Generate reference MSK waveforms for bits 0 and 1
refWave1 = modulateMSK([1], carrierFreq, baudRate, sampleFreq);
refWave0 = modulateMSK([0], carrierFreq, baudRate, sampleFreq);

bitSeq = logical.empty;

% Demodulation using correlation
for startIdx = 1:samplesPerSymbol:numSamples
if startIdx + samplesPerSymbol > numSamples
break;
end
sampleSegment = signal(startIdx:startIdx+samplesPerSymbol-1);

% Compute cross-correlation with reference waveforms
corr1 = xcorr(sampleSegment, refWave1);
corr0 = xcorr(sampleSegment, refWave0);

% Compare correlation values to determine bit
if max(corr1) + abs(min(corr1)) > max(corr0) + abs(min(corr0))
bitSeq = [bitSeq, 1];
else
bitSeq = [bitSeq, 0];
end
end
end

Output


 




In Minimum Shift Keying (MSK), the two frequencies used for 0 and 1 depend on the carrier frequency \( f_c \) and the baud rate \( R_b \) (symbols per second).

Formula for MSK frequencies:

The two frequencies are given by:

\[ f_0 = f_c - \frac{1}{4T} \] \[ f_1 = f_c + \frac{1}{4T} \]

where \( T = \frac{1}{\text{baud rate}} \) is the symbol duration.

Given values:

  • Carrier frequency: \( f_c = 10 \) Hz
  • Baud rate: \( R_b = 10 \) symbols/sec
  • Symbol duration: \( T = \frac{1}{10} = 0.1 \) sec

Now, calculating the frequencies:

\[ f_0 = 10 - \frac{1}{4 \times 0.1} = 10 - \frac{1}{0.4} = 10 - 2.5 = 7.5 \text{ Hz} \] \[ f_1 = 10 + \frac{1}{4 \times 0.1} = 10 + 2.5 = 12.5 \text{ Hz} \]

 

Minimum Shift Keying (MSK) Simulator






Differences Between MSK and FSK

 In FSK, if bits change from 0 to 1, and f₀ ≠ f₁, the carrier switches frequency — but phase continuity is not maintained unless explicitly enforced. This causes a sudden jump in phase at the bit boundary. In MSK, the phase is not static or abruptly switching. It evolves linearly over time based on the bit value, ensuring continuity. For bit duration Tb, the frequency deviation is: 
Δf = ±(1 / 4Tb)
[Read More in Detail ...]
 

Q & A and Summary

1. What is the mathematical representation of the MSK signal and what does it represent?

Answer: The MSK signal is mathematically represented as: $$ s(t) = a_I(t) \cos\left(\frac{\pi t}{2T}\right) \cos(\omega_c t) - a_Q(t) \sin\left(\frac{\pi t}{2T}\right) \sin(\omega_c t) $$ In this formula, \( a_I(t) \) and \( a_Q(t) \) encode the even and odd information respectively, using square pulses of duration \( 2T \). The \( \omega_c \) is the carrier angular frequency, and the terms involving cosine and sine functions describe how the signal's phase and frequency vary over time. This continuous-phase signal is essential for reducing spectral sidebands and interference.

2. How does the constant-modulus property of MSK help reduce distortion in communication systems?

Answer: The constant-modulus property of MSK ensures that the amplitude of the signal remains unchanged regardless of the phase. This is important because non-linear distortion in communication systems typically occurs when the signal's amplitude fluctuates. By maintaining a constant amplitude, MSK reduces the chances of distortion due to non-linearities in amplifiers and other components, thus ensuring cleaner signal transmission and better performance in systems that use non-linear power amplifiers.

3. What is Minimum Shift Keying (MSK) and how does it differ from OQPSK?

Answer: Minimum Shift Keying (MSK) is a type of continuous-phase frequency-shift keying. Unlike OQPSK, MSK encodes data using half sinusoidal pulses rather than square pulses. This leads to a constant-modulus signal, reducing distortion and spectral spread. While OQPSK also uses quadrature components, MSK offers improved signal quality by ensuring smoother phase transitions.

4. Why is the continuous-phase property of MSK important?

Answer: The continuous-phase property of MSK is crucial because it minimizes spectral sidebands. In traditional phase-shift keying schemes, abrupt phase shifts can cause wide sidebands, which interfere with adjacent channels. MSK's smooth and continuous phase changes ensure a narrower spectral occupancy, allowing for better utilization of the available bandwidth and reducing interference.

5. How does the frequency separation in MSK affect the modulation process?

Answer: The frequency separation in MSK ensures that the phase shift over a bit period is exactly ±π/2. This specific frequency separation is what guarantees the smooth transitions between symbols, preventing abrupt phase changes. This also plays a critical role in maintaining the continuous-phase characteristic, which helps reduce spectral spreading and interference in the system.

6. Why is the phase modulation in MSK represented by \( \phi_k(t) = b(t) \frac{\pi t}{2T} + \phi_0 \)?

Answer: The phase modulation \( \phi_k(t) \) in MSK is represented as \( b(t) \frac{\pi t}{2T} + \phi_0 \) to ensure continuous, linear phase changes within each bit period. The term \( b(t) \) corresponds to the bit sequence, determining whether the phase shifts up or down. The factor \( \frac{\pi t}{2T} \) ensures that the phase modulation occurs smoothly over time, with no abrupt transitions, thus maintaining the continuous-phase property of MSK.

7. What makes MSK suitable for non-linear power amplifiers in communication systems?

Answer: MSK is suitable for non-linear power amplifiers because it has a constant-modulus signal. This means that the amplitude of the signal remains constant, regardless of the phase. Non-linear amplifiers work more efficiently when driven by signals with constant amplitude, as they avoid distortion that typically arises from varying amplitudes. This property of MSK allows for better power efficiency without compromising signal quality.


Try Online Interactive Simulators

  1. PSK vs MSK (Phase Difference) Simulation
  2. GMSK Simulation

Further Reading

  1.  Minimum Shift Keying (MSK)
  2. Gaussian Minimum Shift Keying (GMSK)
  3. MATLAB code for GMSK
  4. Difference Between MSK and GMSK
  5. Spectral Estimation of MSK vs GMSK Modulation

Spectral Efficiency and Aviation Utility of MSK

The Spectral Efficiency of MSK

Minimum Shift Keying (MSK) is a highly bandwidth-efficient form of Continuous Phase Modulation (CPM). Unlike standard BPSK or QPSK, which experience abrupt phase transitions at bit boundaries, MSK ensures the phase changes linearly over the duration of a bit.

Key spectral characteristics include:

  • Rapid Spectral Roll-off: The power spectral density (PSD) of MSK drops off at a rate of 1/f4, compared to only 1/f2 for BPSK/QPSK. This significantly reduces "Side Lobe" levels, minimizing interference with adjacent frequency channels.
  • Main Lobe Width: While the MSK main lobe is 50% wider than that of QPSK (1.50/T vs 1.0/T), the lack of high-frequency "splatter" makes it more efficient in systems where tight channel spacing is required.
  • Constant Envelope: As demonstrated in the simulator, MSK maintains a constant amplitude (I² + Q² = 1). This is the "holy grail" for spectral efficiency in practical hardware, as the signal does not require linear amplification to preserve information.

Why MSK is Used in Aviation

In the aeronautical environment—including systems like ACARS (Aircraft Communications Addressing and Reporting System) and VHF Data Link (VDL)—MSK is a preferred standard for several critical reasons:

Power & Weight Efficiency

Aircraft are power-constrained. Because MSK has a constant envelope, it can be amplified using highly efficient Non-Linear (Class C) amplifiers. These amplifiers are lighter, generate less heat, and consume less battery power than the linear amplifiers required for phase-jump modulations.

Resistance to Fading

Aviation channels suffer from Doppler shifts and multi-path fading due to high speeds and ground reflections. MSK’s frequency-based nature makes it more robust against these signal fluctuations compared to amplitude-dependent schemes.

Strict Bandwidth Regulation

Aeronautical frequency bands are extremely crowded. MSK’s low side-lobes ensure that an aircraft’s transmission does not bleed into critical voice or navigation channels (like ILS or VOR) nearby in the spectrum.

MSK provides the perfect balance for aviation by offering a narrow spectral footprint (preventing interference) and a constant amplitude (allowing for smaller, cooler, and more efficient hardware).

Read More: BPSK vs MSK vs GMSK | Compare Spectra and Waveforms


BER vs. SNR Performance in MSK

1. Theoretical Equivalence

In an Additive White Gaussian Noise (AWGN) channel, the theoretical Bit Error Rate (BER) for Minimum Shift Keying (MSK) is identical to BPSK and QPSK, provided coherent detection is used. This is because MSK can be mathematically viewed as Offset QPSK (OQPSK) with half-sine pulse shaping.

Pb = Q(√(2Eb/N0))

2. Coherent vs. Non-Coherent Detection

  • Coherent Detection: Requires the receiver to be perfectly synchronized in phase and frequency. This achieves the optimum "waterfall" curve performance (e.g., 10-6 BER at approx 10.5 dB).
  • Non-Coherent Detection: If a simpler frequency discriminator is used, performance degrades significantly, behaving more like Non-coherent BFSK, which requires more power to achieve the same reliability.

3. The Hardware Advantage

While the BER math is the same as PSK, MSK is often superior in practical applications due to its Constant Envelope (0 dB PAPR).

Feature Practical Impact
Amplifier Efficiency MSK works with saturated (Class C) amplifiers, extending battery life.
Spectral Roll-off Faster roll-off (1/f4) reduces interference in adjacent channels.
Receiver Complexity More complex/finicky than BPSK, requiring precise phase tracking.

Note: MSK offers the high-tier power efficiency of BPSK but with a much cleaner spectral footprint and better compatibility with low-cost, high-efficiency power amplifiers, which is why it became the foundation for standards like GSM.

Read More: about BER vs SNR in MSK

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 / √(2π)) ∫ₓ∞ 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...

High Level and Low Level Modulation

📘 Overview 📚 Low Level Modulation 📚 High Level Modulation 📚 Simulator for High and Low Level Modulations 📚 MATLAB Code 📚 Further Reading High Level and Low Level Modulation You know for wireless communication is suitable for long distance communication. In wireless, for data transmission modulation become essential to avoid interference and to reduce antenna size significantly. Especially, in modulation process, we translate the low frequency baseband signal to higher frequency by modulating with high frequency carrier signal. For a typical communication system we generate the high frequency (carrier) signal by using local oscillator. Source signal or message signal is modulated with local oscillator. Then modulated signal is transmitted thru antenna.  Low Level Modulation In low-level modulation , the message signal is modulated with the carrier signal (from the local oscillator) at low power levels . After modulation, the signal is th...

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 ...