{"ID":2883442,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2508.09348","arxiv_id":"2508.09348","title":"Inference-Driven Uplink for 6G: Architecture, Principles, and Challenges","abstract":"Next-generation wireless networks (6G) face a critical uplink challenge arising from stringent device-side resource constraints and the growing demand for intelligence services. This article introduces InferCom, an inference-driven communication architecture designed to enable robust 6G uplink transmission under low signal-to-noise (SNR) conditions. InferCom adopts a compute-asymmetric architecture, featuring a lightweight transmitter and an inference-capable receiver empowered by generative artificial intelligence (GenAI) models, together with a quality-of-experience (QoE)-aware retransmission mechanism. Grounded in the information bottleneck (IB) theory, InferCom redefines uplink communications through task-agnostic compression, inference-driven reconstruction, error-distribution channel coding, and QoE-aware feedback. The case study demonstrates that InferCom outperforms conventional 5G NR and Deep- JSCC in terms of transmitter-side computational complexity, required SNRs and retransmission efficiency. Finally, we outline key challenges and research directions toward making InferCom a practical enabler of human-centric, intelligent and sustainable wireless networks.","short_abstract":"Next-generation wireless networks (6G) face a critical uplink challenge arising from stringent device-side resource constraints and the growing demand for intelligence services. This article introduces InferCom, an inference-driven communication architecture designed to enable robust 6G uplink transmission under low si...","url_abs":"https://arxiv.org/abs/2508.09348","url_pdf":"https://arxiv.org/pdf/2508.09348v2","authors":"[\"Chunmei Xu\",\"Zhi Ding\",\"Yi Ma\",\"Rahim Tafazolli\",\"Peiying Zhu\"]","published":"2025-08-12T21:22:41Z","proceeding":"eess.SP","tasks":"[\"eess.SP\"]","methods":"[]","has_code":false}