Real-Time and Scalable Zak-OTFS Receiver Processing on GPUs
2026-04-02 • Networking and Internet Architecture
Networking and Internet Architecture
AI summaryⓘ
The authors study a type of wireless signal modulation called OTFS, which works better than traditional methods in fast-moving environments but usually needs a lot of computing power. They created a new way to process OTFS signals quickly using graphics cards (GPUs) by simplifying calculations and using the natural patterns in the signal data. Their method is fast enough to work in real-time and can handle large data sizes while maintaining strong performance. Tests show it works well on multiple computer systems and is promising for future fast wireless communication in vehicles or similar scenarios.
OTFS modulationdelay-Doppler domainGPU computingreal-time processingchannel sparsityiterative equalizer16QAM modulationVehicular-A channelZAK transform
Authors
Junyao Zheng, Chung-Hsuan Tung, Yuncheng Yao, Nishant Mehrotra, Sandesh Mattu, Zhenzhou Qi, Danyang Zhuo, Robert Calderbank, Tingjun Chen
Abstract
Orthogonal time frequency space (OTFS) modulation offers superior robustness to high-mobility channels compared to conventional orthogonal frequency-division multiplexing (OFDM) waveforms. However, its explicit delay-Doppler (DD) domain representation incurs substantial signal processing complexity, especially with increased DD domain grid sizes. To address this challenge, we present a scalable, real-time Zak-OTFS receiver architecture on GPUs through hardware--algorithm co-design that exploits DD-domain channel sparsity. Our design leverages compact matrix operations for key processing stages, a branchless iterative equalizer, and a structured sparse channel matrix of the DD domain channel matrix to significantly reduce computational and memory overhead. These optimizations enable low-latency processing that consistently meets the 99.9-th percentile real-time processing deadline. The proposed system achieves up to 906.52 Mbps throughput with a DD grid size of (16384,32) using 16QAM modulation over 245.76 MHz bandwidth. Extensive evaluations under a Vehicular-A channel model demonstrate strong scalability and robust performance across CPU (Intel Xeon) and multiple GPU platforms (NVIDIA Jetson Orin, RTX 6000 Ada, A100, and H200), highlighting the effectiveness of compute-aware Zak-OTFS receiver design for next-generation (NextG) high-mobility communication systems.