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arXiv · 2508.09348

Inference-Driven Uplink for 6G: Architecture, Principles, and Challenges

Chunmei Xu·Yi Ma·Rahim Tafazolli·Peiying Zhu
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Abstract

Next-generation wireless networks (6G) face a critical uplink challenge arising from stringent device-side resource constraints and the growing demand for intelligent services. This article introduces InferCom, an inference-driven uplink architecture designed to enable robust communication under low signal-to-noise (SNR) conditions. It adopts a compute-asymmetric design with a lightweight transmitter and an inference-capable receiver empowered by generative artificial intelligence models. Grounded in the information bottleneck principle, InferCom redefines communications through task-agnostic compression, inference-driven reconstruction, error distribution channel code, and quality of experience-aware retransmission. A case study demonstrates that InferCom outperforms conventional 5G NR and Deep-JSCC in terms of transmitter-side computational complexity, uplink coverage and retransmission efficiency. Finally, we outline key challenges and research directions for inference driven uplink design in future intelligent 6G networks.

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Chunmei Xu, Yi Ma, Rahim Tafazolli, Peiying Zhu. 2025-08-12. Inference-Driven Uplink for 6G: Architecture, Principles, and Challenges. https://arxiv.org/abs/2508.09348

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