New Delay Doppler Communication Paradigm in 6G era: A Survey of Orthogonal Time Frequency Space (OTFS)
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Abstract (arXiv)
In the 6G era, space-air-Ground integrated networks (SAGIN) are anticipated to deliver global coverage, necessitating support for a diverse array of emerging applications in high-mobility, hostile environments. Under such conditions, conventional orthogonal frequency division multiplexing (OFDM) modulation, widely employed in cellular and Wi-Fi communication systems, experiences performance degradation due to significant Doppler shifts. To overcome this obstacle, a novel two-dimensional (2D) modulation approach, namely orthogonal time frequency space (OTFS), has emerged as a key enabler for future high-mobility use cases. Distinctively, OTFS modulates information within the delay-Doppler (DD) domain, as opposed to the time-frequency (TF) domain utilized by OFDM. This offers advantages such as Doppler and delay resilience, reduced signaling latency, a lower peak-to-average ratio (PAPR), and a reduced-complexity implementation. Recent studies further indicate that the direct interplay between information and the physical world in the DD domain positions OTFS as a promising waveform for achieving integrated sensing and communications (ISAC). In this article, we present an in-depth review of OTFS technology in the context of the 6G era, encompassing fundamentals, recent advancements, and future directions. Our objective is to provide a valuable resource for researchers engaged in the field of OTFS.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 23 Nov 2022.
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Citing papers per year: 2023: 1; 2024: 0; 2025: 3.
4 papers.
- 2025Large AI Model for Delay-Doppler Domain Channel Prediction in 6G OTFS-Based Vehicular Networkscited by 2
- 20232D-RC: Two-Dimensional Neural Network Approach for OTFS Symbol Detectioncited by 0
- 2025Edge-Enabled VIO with Long-Tracked Features for High-Accuracy Low-Altitude IoT Navigationcited by 0
- 2025HyM-UNet: Synergizing Local Texture and Global Context via Hybrid CNN-Mamba Architecture for Medical Image Segmentationcited by 0
- 2025HyM-UNet: Synergizing Local Texture and Global Context via Hybrid CNN-Mamba Architecture for Medical Image Segmentation22 Nov 2025
- 2025Edge-Enabled VIO with Long-Tracked Features for High-Accuracy Low-Altitude IoT Navigation10 May 2025
- 2025Large AI Model for Delay-Doppler Domain Channel Prediction in 6G OTFS-Based Vehicular Networks3 Mar 2025
- 20232D-RC: Two-Dimensional Neural Network Approach for OTFS Symbol Detection14 Nov 2023