PAPR Analysis for MIMO FTN Signaling with Gaussian Symbols

2025-07-20

AI Summary

This work investigates the peak-to-average power ratio (PAPR) characteristics of Gaussian symbols in multiple-input multiple-output faster-than-Nyquist (MIMO FTN) systems, focusing on how PAPR varies with the acceleration factor under two canonical power constraints: fixed transmit power and fixed received signal-to-noise ratio (SNR). Through rigorous theoretical modeling and optimal power allocation analysis, we establish that PAPR is fundamentally governed by the acceleration factor and the type of power constraint—while optimizing transmit-side power allocation yields no substantive reduction in PAPR for Gaussian signaling. This demonstrates an intrinsic PAPR degradation inherent to Gaussian symbols under FTN pulse overlapping. The result reveals a fundamental limitation of Gaussian signaling in FTN transmission and provides critical theoretical foundations and boundary insights for signal design, power management, and PAPR mitigation strategies in MIMO FTN systems.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Non-convex Optimization
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Security and Privacy: Large-scale security measurements
• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems

Abstract

Faster-than-Nyquist signaling serves as a promising solution for improving spectral efficiency in future generations of communications. However, its nature of fast acceleration brings highly overlapped pulses that lead to worse peak-to-average power ratio (PAPR) performance. In this paper, we investigate the PAPR behavior of MIMO FTN using Gaussian symbols under optimal power allocation for two power constraints: fixed transmit power and fixed received signal-to-noise-ratio (SNR). Our findings reveal that PAPR is mainly determined by the acceleration factor and the power constraint, but power allocation optimization does not change the PAPR behavior for Gaussian signaling.

Problem

• Analyzes PAPR in MIMO FTN with Gaussian symbols
• Examines impact of acceleration factor on PAPR
• Studies power constraints' effect on PAPR behavior

Innovation

• Analyzes PAPR in MIMO FTN with Gaussian symbols
• Investigates power allocation under two constraints
• Finds PAPR depends on acceleration and constraints