A Dynamic PAPR Reduction Method Using PTS-ESSA for MIMO Generalized FDM Wireless System
Kumar, Surendra Samriya, Jitendra Kumar Tiwari, Rajeev R. Kumar, Mohit Harnal, Shilpi Kumar, Neerai Sathish Guizani, Mohsen
Kumar, Surendra
Samriya, Jitendra Kumar
Tiwari, Rajeev R.
Kumar, Mohit
Harnal, Shilpi
Kumar, Neerai Sathish
Guizani, Mohsen
Supervisor
Department
Machine Learning
Embargo End Date
Type
Journal article
Date
2026
License
Language
English
Collections
Research Projects
Organizational Units
Journal Issue
Abstract
Generalized Frequency Division Multiplexing (GFDM) is considered a strong candidate to replace Orthogonal Frequency Division Multiplexing (OFDM) in 5G MIMO networks because of its enhanced spectral utilization and design flexibility. Despite these advantages, GFDM faces the drawback of producing a relatively high Peak-to-Average Power Ratio (PAPR), which limits the efficiency of power amplifiers. To address this issue, the Partial Transmit Sequence (PTS) method is often employed for PAPR reduction. Nevertheless, the effectiveness of PTS is hindered by the intensive computational effort required for searching multiple phase factors. To overcome this challenge, we propose a method that integrates the Enhanced Squirrel Search Algorithm (ESSA) with an adaptive parameter control mechanism and a Grey Wolf Optimizer (GWO), enabling a dynamic balance between exploration and exploitation during phase factor selection. This improvement reduces the computational overhead, accelerates the convergence, and enhances the robustness of the phase sequence optimization. Simulation results show that the Hybrid PTS-ESSA-GWO-RPSM model achieves superior PAPR reduction compared to conventional ESSA-based approaches, while also providing better BER and SNR performance under varying channel conditions. The proposed method therefore offers an efficient trade-off between complexity and PAPR reduction, making it suitable for practical deployment in MIMO-GFDM-based 5G systems. The proposed scheme is evaluated against related methods by analyzing key performance indicators, including Complementary Cumulative Distribution Function (CCDF), Bit Error Rate (BER), Peak-to-Average Power Ratio (PAPR), and Signal-to-Noise Ratio (SNR).
Citation
S. Kumar et al., "A Dynamic PAPR Reduction Method Using PTS-ESSA for MIMO Generalized FDM Wireless System," in IEEE Transactions on Network and Service Management, vol. 23, pp. 1162-1175, 2026, doi: 10.1109/TNSM.2025.3619945.
Source
IEEE Transactions on Network and Service Management
Conference
Keywords
CCDF, Computational complexity, ESSA, GFDM, MIMO, PAPR, PTS, RPSM
Subjects
Source
Publisher
IEEE