STUDY AND SIMULATION OF FSK NARROWBAND DIGITAL MODULATION
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2026
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Abstract
This Master's end-of-study project provides a comprehensive theoretical, analytical, and practical study of Frequency Shift Keying (FSK) — a digital modulation technique that encodes binary data through discrete shifts in carrier frequency rather than amplitude or phase. The work spans modulation theory, in-depth FSK analysis, and hands-on simulation using MATLAB and Simulink.
Modulation Background
Chapter 1 surveys the landscape of modulation techniques, covering analog methods (AM, FM, PM) and the three principal digital schemes: Amplitude Shift Keying (ASK), Frequency Shift Keying (FSK), and Phase Shift Keying (PSK). FSK stands out for its constant-envelope waveform, making it inherently robust against amplitude noise, fading, and non-linear amplifier distortion — critical advantages over ASK-based systems that encode information in the more noise-susceptible amplitude domain.
FSK: Technical Analysis
Chapter 2 traces FSK from its origins in Reginald Fessenden’s two-tone Morse experiments (1910) through its modern variants. The chapter covers the complete FSK system architecture (binary source, carrier oscillators, modulator, transmission channel, demodulator, decision circuit), its mathematical formulation, and five key variants: Binary FSK (BFSK), Multiple FSK (MFSK), Continuous Phase FSK (CPFSK), Gaussian FSK (GFSK), and Minimum Shift Keying (MSK). Both coherent and non-coherent demodulation strategies are examined, with BER analysis showing coherent detection achieves Pb = ½ erfc(√(Eb/2N₀)) versus non-coherent Pb = ½ exp(−Eb/2N₀). FSK’s real-world applications include walkie-talkies, RFID systems, wireless sensor networks (IoT), satellite telemetry (TT&C), and telephone modems.
Simulation: MATLAB & Simulink
Chapter 3 implements FSK modulation and demodulation using two complementary approaches. The MATLAB script employs correlation-based coherent detection: the received signal is correlated against high- and low-frequency references for each bit interval, and the stronger correlation determines the decoded bit. The Simulink model builds a graphical block diagram using a Charge Pump Phase-Locked Loop (PLL) for non-coherent frequency tracking, mirroring real hardware receiver architectures. Both approaches were validated through scope
visualisations showing binary NRZ source, carrier frequencies, modulated signal, and recovered data.
Key Findings & Conclusions
The project confirms that FSK’s constant-envelope property provides decisive advantages in noise-prone environments. Coherent detection yields superior BER performance, while non-coherent PLL-based detection is preferred in practical hardware for its simplicity and phase-jitter resilience. MATLAB scripting excels for academic signal analysis and BER studies, whereas Simulink is better suited to system-level prototyping and embedded code generation. Future directions include FPGA/SDR implementation, BER analysis under fading channels (Rayleigh/Rician models), and integration of FSK with emerging LPWAN and NOMA network frameworks.