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FM-OFDM: A Constant-Envelope Sensing Waveform with Phase-Differencing Receiver Processing

Sep 2026 · 0 citations · 37 references
Engineering

TL;DR

This paper characterizes FM-OFDM as a sensing waveform based on its bandwidth, ambiguity function, sidelobe behavior, and Doppler estimation capability, and shows that its data dependent sidelobe floor is incoherent and decreases through across frame integration, whereas the corresponding CP-OFDM floor remains unchanged.

Abstract

Cyclic-prefix orthogonal frequency-division multiplexing (CP-OFDM) is widely adopted as a reference waveform for integrated sensing and communication (ISAC). However, its high peak-to-average power ratio (PAPR) requires power amplifier back-off, thereby reducing the available sensing link budget. Frequency-modulated OFDM (FM-OFDM) provides a constant-envelope signal with 0 dB PAPR and has demonstrated reliable communication performance in high-mobility scenarios, but its sensing characteristics remain largely unexplored. This paper characterizes FM-OFDM as a sensing waveform based on its bandwidth, ambiguity function, sidelobe behavior, and Doppler estimation capability. The analysis shows that its data dependent sidelobe floor is incoherent and decreases through across frame integration, whereas the corresponding CP-OFDM floor remains unchanged. Consequently, under equal occupied bandwidth and transmit power, frame-level integration reverses the single-symbol performance ordering and provides FM-OFDM with approximately 20 dB of additional dynamic range for weak-target detection. Moreover, the zero-delay cut of the FMOFDM ambiguity function is shown to be deterministic and independent of the transmitted data realization, in contrast to linearly modulated waveforms, while a closed-form expression is derived for the sidelobe floor away from the zero-delay cut. Since the nonlinear mapping between the data symbols and time-domain samples prevents the direct application of the conventional CP-OFDM range-Doppler processing chain, a weighted phase-increment Doppler estimator is developed. The proposed estimator enables closed-form prediction of the sensing floor and its crossover point with a minimum computational complexity.

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