{"ID":2847984,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.26844","arxiv_id":"2510.26844","title":"Multi-hop Parallel Image Semantic Communication for Distortion Accumulation Mitigation","abstract":"Existing semantic communication schemes primarily focus on single-hop scenarios, overlooking the challenges of multi-hop wireless image transmission. As semantic communication is inherently lossy, distortion accumulates over multiple hops, leading to significant performance degradation. To address this, we propose the multi-hop parallel image semantic communication (MHPSC) framework, which introduces a parallel residual compensation link at each hop against distortion accumulation. To minimize the associated transmission bandwidth overhead, a coarse-to-fine residual compression scheme is designed. A deep learning-based residual compressor first condenses the residuals, followed by the adaptive arithmetic coding (AAC) for further compression. A residual distribution estimation module predicts the prior distribution for the AAC to achieve fine compression performances. This approach ensures robust multi-hop image transmission with only a minor increase in transmission bandwidth. Experimental results confirm that MHPSC outperforms both existing semantic communication and traditional separated coding schemes.","short_abstract":"Existing semantic communication schemes primarily focus on single-hop scenarios, overlooking the challenges of multi-hop wireless image transmission. As semantic communication is inherently lossy, distortion accumulates over multiple hops, leading to significant performance degradation. To address this, we propose the...","url_abs":"https://arxiv.org/abs/2510.26844","url_pdf":"https://arxiv.org/pdf/2510.26844v2","authors":"[\"Bingyan Xie\",\"Jihong Park\",\"Yongpeng Wu\",\"Wenjun Zhang\",\"Tony Quek\"]","published":"2025-10-30T10:51:41Z","proceeding":"cs.IT","tasks":"[\"cs.IT\",\"cs.MM\",\"eess.IV\"]","methods":"[]","has_code":false}