{"title":"基于 ISAC 扩散薛定谔桥的电磁特性传感和通道重构","authors":"Yuhua Jiang, Feifei Gao, Shi Jin","doi":"arxiv-2409.11651","DOIUrl":null,"url":null,"abstract":"Integrated sensing and communications (ISAC) has emerged as a transformative\nparadigm for next-generation wireless systems. In this paper, we present a\nnovel ISAC scheme that leverages the diffusion Schrodinger bridge (DSB) to\nrealize the sensing of electromagnetic (EM) property of a target as well as the\nreconstruction of the wireless channel. The DSB framework connects EM property\nsensing and channel reconstruction by establishing a bidirectional process: the\nforward process transforms the distribution of EM property into the channel\ndistribution, while the reverse process reconstructs the EM property from the\nchannel. To handle the difference in dimensionality between the\nhigh-dimensional sensing channel and the lower-dimensional EM property, we\ngenerate latent representations using an autoencoder network. The autoencoder\ncompresses the sensing channel into a latent space that retains essential\nfeatures, which incorporates positional embeddings to process spatial context.\nThe simulation results demonstrate the effectiveness of the proposed DSB\nframework, which achieves superior reconstruction of the targets shape,\nrelative permittivity, and conductivity. Moreover, the proposed method can also\nrealize high-fidelity channel reconstruction given the EM property of the\ntarget. The dual capability of accurately sensing the EM property and\nreconstructing the channel across various positions within the sensing area\nunderscores the versatility and potential of the proposed approach for broad\napplication in future ISAC systems.","PeriodicalId":501034,"journal":{"name":"arXiv - EE - Signal Processing","volume":"116 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Electromagnetic Property Sensing and Channel Reconstruction Based on Diffusion Schrödinger Bridge in ISAC\",\"authors\":\"Yuhua Jiang, Feifei Gao, Shi Jin\",\"doi\":\"arxiv-2409.11651\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Integrated sensing and communications (ISAC) has emerged as a transformative\\nparadigm for next-generation wireless systems. In this paper, we present a\\nnovel ISAC scheme that leverages the diffusion Schrodinger bridge (DSB) to\\nrealize the sensing of electromagnetic (EM) property of a target as well as the\\nreconstruction of the wireless channel. The DSB framework connects EM property\\nsensing and channel reconstruction by establishing a bidirectional process: the\\nforward process transforms the distribution of EM property into the channel\\ndistribution, while the reverse process reconstructs the EM property from the\\nchannel. To handle the difference in dimensionality between the\\nhigh-dimensional sensing channel and the lower-dimensional EM property, we\\ngenerate latent representations using an autoencoder network. The autoencoder\\ncompresses the sensing channel into a latent space that retains essential\\nfeatures, which incorporates positional embeddings to process spatial context.\\nThe simulation results demonstrate the effectiveness of the proposed DSB\\nframework, which achieves superior reconstruction of the targets shape,\\nrelative permittivity, and conductivity. Moreover, the proposed method can also\\nrealize high-fidelity channel reconstruction given the EM property of the\\ntarget. The dual capability of accurately sensing the EM property and\\nreconstructing the channel across various positions within the sensing area\\nunderscores the versatility and potential of the proposed approach for broad\\napplication in future ISAC systems.\",\"PeriodicalId\":501034,\"journal\":{\"name\":\"arXiv - EE - Signal Processing\",\"volume\":\"116 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - EE - Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2409.11651\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - EE - Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.11651","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Electromagnetic Property Sensing and Channel Reconstruction Based on Diffusion Schrödinger Bridge in ISAC
Integrated sensing and communications (ISAC) has emerged as a transformative
paradigm for next-generation wireless systems. In this paper, we present a
novel ISAC scheme that leverages the diffusion Schrodinger bridge (DSB) to
realize the sensing of electromagnetic (EM) property of a target as well as the
reconstruction of the wireless channel. The DSB framework connects EM property
sensing and channel reconstruction by establishing a bidirectional process: the
forward process transforms the distribution of EM property into the channel
distribution, while the reverse process reconstructs the EM property from the
channel. To handle the difference in dimensionality between the
high-dimensional sensing channel and the lower-dimensional EM property, we
generate latent representations using an autoencoder network. The autoencoder
compresses the sensing channel into a latent space that retains essential
features, which incorporates positional embeddings to process spatial context.
The simulation results demonstrate the effectiveness of the proposed DSB
framework, which achieves superior reconstruction of the targets shape,
relative permittivity, and conductivity. Moreover, the proposed method can also
realize high-fidelity channel reconstruction given the EM property of the
target. The dual capability of accurately sensing the EM property and
reconstructing the channel across various positions within the sensing area
underscores the versatility and potential of the proposed approach for broad
application in future ISAC systems.