[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-82042-en":3,"doc-seo-82042-105":29,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":13,"seo_description":14,"update_tm":27,"read_time":28},82042,7971461740909,"Levi","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","SIDMA: Semantic Interleave Division Multiple Access Communication System","Multiple Access (MA) technology enables the evolution of mobile communications, while Semantic Communication introduces semantic spatial resources by mining the deep meaning of information. In multi-user concurrent transmission, spatial correlation and semantic feature importance heterogeneity can trigger semantic collisions and semantic collapse. This paper proposes SIDMA (Semantic Interleaved Division Multiple Access) using a permutation operator for structural whitening and an Importance-aware Power Allocation (ImpPA) module for differentiated protection. Core features are scattered in the interleaving domain and power is adaptively optimized from real-time channels, improving reconstruction fidelity and scalability over multiple baselines.","SIDMA: Semantic Interleave Division Multiple Access  \nCommunication System  \nYunlu Wang, Chen Dong∗ , Sen Wang, Lei Teng, Yaping Sun, Xiaodong Xu, Senior Member, IEEE,  \nand Ping Zhang, Fellow, IEEE  \narXiv :2607 .08777v1 [ cs .IT] 27 May 2026  \nAbstract—Multiple Access (MA) technology has consistently served as the core driving force behind the evolution of mobile communications. As a promising paradigm for next-generation communications, Semantic Communication explores entirely new semantic spatial resources by mining the deep meaning of information. However, the inherent spatial correlation and importance heterogeneity of semantic features often cause semantic collisionsand semantic collapse in multi-user concurrent transmission scenarios. To address these challenges, this paper proposes a Semantic Interleaved Division Multiple Access (SIDMA) technique. By utilizing a permutation operator to perform structural whitening on semantic features and combining it with an Importance-aware Power Allocation (ImpPA) module for differentiated protection, SIDMA scatters core features across the interleaving domain and adaptively optimizes power levels based on real-time channel conditions. Simulation results demonstrate that, compared with traditional MA techniques and advanced semantic multiple access schemes including Orthogonal-Model Division Multiple Access (OMDMA), Deep Multiple Access (DeepMA), and Shared Embedding (SE), the proposed SIDMA exhibits superior reconstruction fidelity and scalability in multi-user concurrent transmissions, effectively enhancing the communication quality and robustness in resource-constrained environments.  \nIndex Terms—Semantic Communication, Interleaving Division Multiple Access, Adaptive Power Allocation  \nI. INTRODUCTION  \nSEMANTIC Communication represents a fundamental shift  \nin the communication paradigm, moving from traditional“bit transmission” to “semantic exchange” [1]–[3] . By extracting key semantic information and transmitting only essential features, semantic communication explores entirely new semantic spatial resources by mining the deep meaning of information. This approach demonstrates immense potential to surpass the Shannon limit, particularly in extremely low Signal-to-Noise Ratio (SNR) environments where precise  \nThis work is supported in part by the National Key Research and Development Program of China under Grant 2020YFB1806905, in part by the Beijing Natural Science Foundation under Grant L251035, and in part by Beijing University of Posts and Telecommunications-China Mobile Communications Group Co., Ltd. Joint Institute. (Corresponding authors: Chen Dong)  \nYunlu Wang, Chen Dong, Lei Teng, Xiaodong Xu and Ping Zhang are with the State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China. Yunlu Wang is also with the Department of Broadband Communication, Pengcheng Laboratory, Shenzhen 518000, China. (emails: yunlu [wang@bupt.edu.cn](wang@bupt.edu.cn), [dongchen@bupt.edu.cn](dongchen@bupt.edu.cn), ten[glei@bupt.edu.cn](glei@bupt.edu.cn), [xuxiaodong@bupt.edu.cn](xuxiaodong@bupt.edu.cn), [pzhang@bupt.edu.cn](pzhang@bupt.edu.cn))  \nSen Wang is with China Mobile Research Institute, Beijing, China. (email: [wangsenyjy@chinamobile.com](wangsenyjy@chinamobile.com))  \nYaping Sun is with the Department of Broadband Communication, Pengcheng Laboratory, Shenzhen 518000, China. Yaping Sun is also with the Shenzhen Future Network of Intelligence Institute (FNii-Shenzhen), Chinese University of Hong Kong (Shenzhen), Shenzhen 518172, China. (email: [sunyp@pcl.ac.cn](sunyp@pcl.ac.cn))  \nphysical bit recovery is impractical. By ensuring the reliable exchange of core meaning, this paradigm provides a pathway toward more intelligent, goal-oriented wireless networks that prioritize information essence over binary accuracy [1], [4] .  \nThroughout this evolution, MA technology has consistently served as the primary drivi","cbCaijw4zDPLMahO","https://ap.wps.com/l/cbCaijw4zDPLMahO","pdf",5783084,1,13,"English","en",105,"# Introduction\n## Multiple Access evolution (1G–5G)\n## Semantic multiple access overview\n## Paper contribution: SIDMA","[{\"question\":\"What problem does SIDMA address in semantic multiple access?\",\"answer\":\"It targets semantic collisions and semantic collapse caused by spatial correlation and importance heterogeneity of semantic features during concurrent multi-user transmissions.\"},{\"question\":\"How does SIDMA improve semantic transmission?\",\"answer\":\"It applies a permutation operator to structurally whiten semantic features and uses an importance-aware power allocation module to provide differentiated protection.\"},{\"question\":\"What do the simulation results show compared with other MA schemes?\",\"answer\":\"SIDMA achieves higher reconstruction fidelity and better scalability in multi-user concurrent transmissions than traditional MA and advanced semantic multiple access methods such as OMDMA, DeepMA, and 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problem does SIDMA address in semantic multiple access?","Question",{"text":75,"@type":76},"It targets semantic collisions and semantic collapse caused by spatial correlation and importance heterogeneity of semantic features during concurrent multi-user transmissions.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How does SIDMA improve semantic transmission?",{"text":80,"@type":76},"It applies a permutation operator to structurally whiten semantic features and uses an importance-aware power allocation module to provide differentiated protection.",{"name":82,"@type":73,"acceptedAnswer":83},"What do the simulation results show compared with other MA schemes?",{"text":84,"@type":76},"SIDMA achieves higher reconstruction fidelity and better scalability in multi-user concurrent transmissions than traditional MA and advanced semantic multiple access methods such as OMDMA, DeepMA, and 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