  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.
