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arXiv · 2610.25979

Learnable Pilot Design for OFDM-based Deep Joint Source-Channel Coding

Joohyun Shin·Jiwan Seo·Joonhyuk Kang
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Abstract

Recent advances in deep joint source-channel coding (DeepJSCC) have shown strong robustness to channel variations in wireless image transmission. However, its integration with orthogonal frequency-division multiplexing (OFDM) typically relies on fixed pilot patterns that are not optimized for receiver- side channel processing. This work introduces Pilot-Efficient DeepJSCC-OFDM (PE-JSCC), which learns pilot placement under a strictly fixed number of pilot symbols via a Gumbel- Top-k-based selector. The learned pilot placement improves end- to-end performance over the conventional Block-JSCC, Comb- JSCC, and Scatter-JSCC baselines. To support high mobility, the receiver incorporates a lightweight axial-attention-based inter- carrier interference (ICI) canceler and a CNN-based channel estimator. Simulation results show that PE-JSCC consistently outperforms fixed pilot patterns across diverse SNRs and remains robust over a wide mobility range.

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Joohyun Shin, Jiwan Seo, Joonhyuk Kang. 2026-10-19. Learnable Pilot Design for OFDM-based Deep Joint Source-Channel Coding. https://arxiv.org/abs/2610.25979

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