{"ID":2847454,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.27192","arxiv_id":"2510.27192","title":"From OFDM to AFDM: Enabling Adaptive Integrated Sensing and Communication in High-Mobility Scenarios","abstract":"Integrated sensing and communication (ISAC) is a key feature of next-generation wireless networks, enabling a wide range of emerging applications such as vehicle-to-everything (V2X) and unmanned aerial vehicles (UAVs), which operate in high-mobility scenarios. Notably, the wireless channels within these applications typically exhibit severe delay and Doppler spreads. The latter causes serious communication performance degradation in the Orthogonal Frequency-Division Multiplexing (OFDM) waveform that is widely adopted in current wireless networks. To address this challenge, the recently proposed Doppler-resilient affine frequency division multiplexing (AFDM) waveform, which uses flexible chirp signals as subcarriers, shows great potential for achieving adaptive ISAC in high-mobility scenarios. This article provides a comprehensive overview of AFDM-ISAC. We begin by presenting the fundamentals of AFDM-ISAC, highlighting its inherent frequency-modulated continuous-wave (FMCW)-like characteristics. Then, we explore its ISAC performance limits by analyzing its diversity order, ambiguity function (AF), and Cramer-Rao Bound (CRB). Finally, we present several effective sensing algorithms and opportunities for AFDM-ISAC, with the aim of sparking new ideas in this emerging field.","short_abstract":"Integrated sensing and communication (ISAC) is a key feature of next-generation wireless networks, enabling a wide range of emerging applications such as vehicle-to-everything (V2X) and unmanned aerial vehicles (UAVs), which operate in high-mobility scenarios. Notably, the wireless channels within these applications ty...","url_abs":"https://arxiv.org/abs/2510.27192","url_pdf":"https://arxiv.org/pdf/2510.27192v1","authors":"[\"Haoran Yin\",\"Yanqun Tang\",\"Jun Xiong\",\"Fan Liu\",\"Yuanhan Ni\",\"Qu Luo\",\"Roberto Bomfin\",\"Marwa Chafii\",\"Marios Kountouris\",\"Christos Masouros\"]","published":"2025-10-31T05:23:22Z","proceeding":"eess.SP","tasks":"[\"eess.SP\"]","methods":"[]","has_code":false}