On Discrete Ambiguity Functions of Random Communication Waveforms
Ying Zhang, Fan Liu, Yifeng Xiong, Weijie Yuan, Shuangyang Li, Le Zheng, Tony Xiao Han, Christos Masouros, Shi Jin

TL;DR
This paper characterizes the discrete ambiguity functions of random communication waveforms, providing analytical expressions for sidelobe levels and revealing structural constraints and waveform optimality regimes for delay-Doppler sensing in ISAC.
Contribution
It introduces a unified analytical framework for discrete periodic and fast-slow time AFs, and uncovers fundamental geometric and constellation-dependent properties of waveform ambiguity functions.
Findings
Normalized EISL is identical for all orthogonal waveforms.
Minimum sidelobe levels are constrained to specific delay-Doppler regions.
OFDM and OTFS are optimal for sub-Gaussian and super-Gaussian constellations respectively.
Abstract
This paper provides a fundamental characterization of the discrete ambiguity functions (AFs) of random communication waveforms under arbitrary orthonormal modulation with random constellation symbols, which serve as a key metric for evaluating the delay-Doppler sensing performance in future ISAC applications. A unified analytical framework is developed for two types of AFs, namely the discrete periodic AF (DP-AF) and the fast-slow time AF (FST-AF), where the latter may be seen as a small-Doppler approximation of the DP-AF. By analyzing the expectation of squared AFs, we derive exact closed-form expressions for both the expected sidelobe level (ESL) and the expected integrated sidelobe level (EISL) under the DP-AF and FST-AF formulations. For the DP-AF, we prove that the normalized EISL is identical for all orthogonal waveforms. To gain structural insights, we introduce a matrix…
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Taxonomy
TopicsRadar Systems and Signal Processing · PAPR reduction in OFDM · Sparse and Compressive Sensing Techniques
