FPGA-based Modulation Classification using Verilog Simulation

Author(s)	Afsal M M
Country	India
Abstract	Automatic modulation classification (AMC) plays a crucial role in modern communication systems, particularly in applications such as cognitive radio, spectrum monitoring, and software-defined radios (SDRs). Traditional AMC techniques rely heavily on software-based processing, which is computationally expensive and unsuitable for real- time embedded systems. In this work, we present a lightweight, Verilog HDL-based design for modulation classification targeting VLSI/FPGA platforms. The system is designed with modular blocks for feature extraction and classification and is evaluated using Vivado simulator. A zero-crossing rate (ZCR), amplitude-based and signal energy feature extraction approach is employed to differentiate between basic modulation schemes such as BPSK and QPSK. The classification is implemented as a simple threshold-based decision logic in Verilog HDL. Simulation results confirm that the proposed design successfully classifies signals with high accuracy under noise-free and moderate noise conditions. The work demonstrates the feasibility of integrating AMC algorithms into hardware-efficient FPGA- based systems, paving the way for future extensions to higher-order modulation schemes.
Keywords	Automatic Modulation Classification (AMC), Verilog HDL, VLSI, FPGA, BPSK, QPSK, Signal Processing, Vivado
Field	Computer > Electronics
Published In	Volume 7, Issue 3, May-June 2026
Published On	2026-05-02

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