SC-FDMA Simulation Code Based on MATLAB Platform

SC-FDMA (Single Carrier Frequency Division Multiple Access) is a wireless communication technology widely adopted in 4G LTE uplink transmission, particularly valued for its low Peak-to-Average Power Ratio (PAPR) characteristics. Implementing SC-FDMA systems on the MATLAB simulation platform enables in-depth understanding of working principles and optimization of system performance.

The core concept of SC-FDMA involves transforming time-domain signals to the frequency domain through Discrete Fourier Transform (DFT), followed by subcarrier mapping and Inverse Fourier Transform (IDFT) to generate final transmission signals. MATLAB simulation typically includes these key implementation steps:

Signal Generation and Modulation: Generate random data bit streams first, then convert them to complex symbols using QPSK or QAM modulation. In MATLAB, this can be implemented using functions like randi() for data generation and pskmod()/qammod() for modulation.

DFT Pre-processing: Perform DFT transformation on modulated symbols to convert time-domain signals to frequency domain - this represents one of the main distinctions between SC-FDMA and conventional OFDM. MATLAB's fft() function efficiently handles this transformation with optimized computational performance.

Subcarrier Mapping: Utilize either localized or interleaved mapping approaches to assign DFT outputs to designated subcarriers. This can be implemented through index-based matrix operations in MATLAB, where mapping patterns are controlled by predefined mapping matrices.

IFFT Transformation: Convert mapped frequency-domain signals back to time-domain using IFFT to form SC-FDMA symbols. The ifft() function in MATLAB, combined with proper scaling factors, ensures accurate signal reconstruction.

Cyclic Prefix Addition: Insert cyclic prefixes to combat Inter-Symbol Interference (ISI) caused by multipath effects. MATLAB implementation typically uses array concatenation operations, where the last portion of the symbol is appended to the beginning.

Channel Modeling and Equalization: Simulate multipath channels and perform frequency-domain equalization (such as MMSE or ZF equalization) at the receiver end to recover original signals. The Communications Toolbox provides functions like comm.RayleighChannel for channel modeling and matrix inversion operations for equalizer implementation.

In MATLAB, built-in FFT/IFFT functions, matrix operations, and Communications Toolbox can efficiently implement the above workflow. Simulation results can be evaluated using metrics like Bit Error Rate (BER) and constellation diagrams, where functions like berawgn() and scatterplot() provide standardized performance analysis.

By adjusting parameters such as number of subcarriers, modulation schemes, or equalization algorithms, researchers can further explore SC-FDMA performance under different channel conditions, providing valuable references for practical system design.