面向通感融合的结构化生成式无线图像传输框架与关键技术OA

As wireless communications evolve towards intelligence and integrated sensing and communication(ISAC),realizing efficient and robust image transmission under limited bandwidth and unreliable channel conditions has become a critical challenge in intelligent wireless networks.However,existing wireless image transmission schemes primarily focus on enhancing visual quality and often lack active sensing and structured understanding of the source image content,such as the spatial consistency and saliency of targets,making it difficult to preserve the spatial layout of targets,salient regions,and high-level semantic consistency under low code-rate transmission and channel disturbances.To address these issues,this paper proposes a structured generative wireless image transmission framework oriented towards ISAC.At the transmitter,a sensing module performs saliency detection to extract a saliency map that characterizes the spatial layout of the scenario,serving as a sparse sensing prior.Subsequently,constrained by this structural sensing prior,a multimodal large language model(MLLM)is utilized to convert the image into structure-aware descriptive text,achieving a structured joint representation of semantics and sensing features.During the transmission phase,considering the importance and redundant characteristics of different modalities,modality-separated joint source-channel coding is employed to achieve low code-rate and anti-noise reliable transmission,where the saliency prior preserves key spatial structures and the text semantics convey high-level content information.At the receiver,the reconstruction process is modeled as a structured condition-guided generative workflow,utilizing the received sensing prior as an explicit constraint to guide high-quality image synthesis.Simulation results demonstrate that the proposed structured generative transmission framework significantly outperforms existing methods in terms of both semantic fidelity and visual perceptual quality,fully validating the superiority of ISAC and structured guidance in resource-constrained wireless image communications.