Enhancing PAPR and Throughput for DFT-s-OFDM System Using FTN and IOTA Filtering

Area of Science:

• Wireless Communication
• Signal Processing

Background:

• High frequency wireless communication demands ultra high-speed transmissions.
• Waveform design faces challenges in balancing spectrum efficiency and hardware compatibility.
• Discrete Fourier Transform spreading-based Orthogonal Frequency Division Multiplexing (DFT-s-OFDM) offers flexibility and low Peak-to-Average Power Ratio (PAPR).

Purpose of the Study:

• To enhance spectral efficiency in DFT-s-OFDM by integrating Faster-Than-Nyquist (FTN) signaling.
• To investigate the impact of FTN integration on PAPR performance.
• To mitigate the inter-symbol interference (ISI) introduced by FTN signaling.

Main Methods:

• Integration of FTN signaling into DFT-s-OFDM.
• Deployment of an Isotropic Orthogonal Transform Algorithm (IOTA) filter to reduce ISI.
• Performance evaluation through simulations focusing on PAPR, Bit Error Rate (BER), and throughput.

Main Results:

• The proposed FTN-enhanced DFT-s-OFDM waveform shows improved spectral efficiency.
• PAPR performance is enhanced compared to standard DFT-s-OFDM.
• The IOTA filter effectively reduces ISI, leading to significant gains in PAPR (3.5 dB) and throughput (50%).

Conclusions:

• The FTN-enhanced DFT-s-OFDM waveform with an IOTA filter is a promising candidate for high frequency wireless communication.
• This approach simultaneously achieves good PAPR, BER, and throughput.
• The integration offers a substantial improvement in communication system performance.