DFT-spread-OFDM Based Chirp Transmission

TL;DR

This paper introduces a novel chirp transmission framework based on DFT-s-OFDM, enabling efficient synthesis of chirps for IoT, radar, and sensing applications by optimizing spectral shaping filters.

Contribution

It presents a new spectral shaping method for DFT-s-OFDM that converts it into chirp signals, with analytical design and noise reduction strategies, enhancing communication and sensing capabilities.

Findings

Low ripple frequency-domain filters reduce BER.

Analytical FDSS filter design for arbitrary chirps.

Noise enhancement mitigated through frequency repetitions.

Abstract

In this study, we propose a framework for chirp-based communications by exploiting discrete Fourier transform-spread orthogonal frequency division multiplexing (DFT-s-OFDM). We show that a well-designed frequency-domain spectral shaping (FDSS) filter for DFT-s-OFDM can convert its single-carrier nature to a linear combination of chirps circularly translated in the time domain. Also, by exploiting the properties of the Fourier series and Bessel function of the first kind, we analytically obtain the FDSS filter for an arbitrary chirp. We theoretically show that the chirps with low ripples in the frequency domain result in a lower bit-error ratio (BER) via less noise enhancement. We also address the noise enhancement by exploiting the repetitions in the frequency. The proposed framework offers a new way to efficiently synthesize chirps that can be used in Internet-of-Things (IoT), dual-function radar and communication (DFRC) or wireless sensing applications with existing DFT-s-OFDM transceivers.