Peak-to-Average Power Ratio Reduction in OFDM Systems with SLM and PST Algorithms

This document presents the implementation of source code for reducing Peak-to-Average Power Ratio (PAPR) in Orthogonal Frequency Division Multiplexing (OFDM) systems. We provide an in-depth analysis of the implementation principles behind Selective Level Mapping (SLM) and Partial Transmit Sequence (PST) algorithms, including their core advantages in PAPR reduction. The implementation typically involves phase optimization techniques where SLM generates multiple candidate signals with different phase sequences and selects the one with minimum PAPR, while PST partitions subcarriers into disjoint blocks and applies phase rotation to each block. We further explore algorithmic enhancements for improved performance, such as incorporating gradient-based optimization or machine learning approaches for phase sequence selection. Practical examples demonstrate how these algorithms can be integrated into OFDM transmitters with code segments showing subcarrier partitioning, phase factor generation, and PAPR calculation using complementary cumulative distribution function (CCDF) metrics. Application scenarios include 5G systems, WiFi networks, and digital video broadcasting where PAPR reduction is critical for power amplifier efficiency. Through this technical exposition, readers will gain comprehensive understanding of PAPR challenges in OFDM systems and acquire practical implementation strategies for optimal system performance.