OpenAlex ·

A Deep Iterative Refinement Receiver for OTFS Symbol Detection in Doubly-Dispersive Channels

Efe Ispir and Ian P. Roberts

Published
Source
OpenAlex
DOI
10.48550/arxiv.2609.00465
Original
Read it at the publisher
Topics
Artificial IntelligenceSignal Processing

Abstract

Orthogonal time frequency space (OTFS) modulation has emerged as a promising candidate for high-mobility wireless communication systems due to the diversity it offers across both time and frequency. Reliable OTFS detection, however, remains challenging under doubly-dispersive channels, where delay and Doppler dispersion induce structured interference between transmitted symbols and complicate symbol recovery. To address these challenges, we propose a two-stage iterative OTFS detector that integrates a physics-informed learned initializer with an iterative refinement network, enabling progressively more accurate symbol estimates in doubly-dispersive channels. The initializer incorporates the known delay-Doppler input-output relationship to produce a robust first-stage estimate, while the refinement stage iteratively suppresses residual symbol interference in the delay-Doppler domain. Simulation results demonstrate that the proposed detector achieves consistent performance gains over conventional and existing learning-based detectors across a variety of channel conditions. These results highlight the effectiveness of incorporating known channel structure into the detection process and using iterative refinement for improved and robust OTFS detection.

The authors’ abstract, as arXiv lists it. arXiv’s listings, abstracts included, are free for anyone to reuse.

Read it on ReadSearch

Each opens after you create an account, and brings you back to this paper.

Already a reader? Sign in

All new papers in Artificial Intelligence

Get the few papers worth your time in Artificial Intelligence every morning.

ReadSearch reads the new papers in your field each day and brings you the few worth reading, each with its key finding in a sentence.

Papers belong to their authors and publishers; every page here links to the original. All research topics