[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-85947-en":3,"doc-seo-85947-105":30,"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":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":13,"seo_description":14,"update_tm":28,"read_time":29},85947,7971461740909,"Levi","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","SCMA Inspired Sparse Vector Coding An Enhanced URLLC Transmission Scheme","Sparsity is jointly exploited in sparse code multiple access (SCMA) and sparse vector coding (SVC), motivating a study of their mutual enhancement for ultrareliable low-latency communications. A novel SCMA-inspired SVC scheme, SCMA-SVC, leverages SCMA’s sparse pattern and multidimensional constellation structure to enlarge the minimum Euclidean distance of SVC codebooks. Random phase rotations further enable full diversity order over Rayleigh fading channels. Under maximum-likelihood decoding, SCMA-SVC achieves strong error-rate performance over Gaussian and Rayleigh channels, and a low-complexity sparse-structured decoder preserves near-ML reliability with improved robustness over prior SVC variants.","SCMA Inspired Sparse Vector Coding: An Enhanced URLLC  \nTransmission Scheme  \nZhen-Ming Huang, Graduate Student Member, IEEE, Zilong Liu, Senior Member, IEEE, Leila Musavian, Senior Member, IEEE, and Chao-Yu Chen, Senior Member, IEEE  \narXiv :2607 . 10520v 1 [ cs .IT] 12 Jul 2026  \nAbstract—Sparsity is inherently exploited in sparse code multiple access (SCMA) and sparse vector coding (SVC), yet the interaction between these two has not been explored before. It is intriguing to ask if one can be used to improve the other, and vice versa. In this work, we present a novel SCMA inspired SVC scheme, called SCMA-SVC, for enhanced ultrareliable low-latency communications. Our key idea is to exploit the sparse pattern and multidimensional constellation nature of SCMA, with which one is able to further enlarge the minimum Euclidean distance (MED) of the corresponding SVC codebooks. Such an innovation allows us to harvest the multiuser coding gain and the constellation shaping gain which are pertinent to SCMA. Moreover, by applying random phase rotations to the sparse vectors, it is shown that the proposed SCMA-SVC achieves full diversity order over Rayleigh fading channels. Under maximum likelihood (ML) decoding, the proposed SCMASVC demonstrates remarkable error rate performances over both Gaussian and Rayleigh fading channels. Additionally, we develop a low-complexity decoder that exploits the structural sparsity of SCMA-SVC while maintaining near-ML performance. Simulation results demonstrate that the proposed SCMA-SVC achieves significantly improved reliability over the existing SVC variants.  \nIndex Terms—Sparse vector coding (SVC), sparse code multiple access (SCMA), short-packet transmission, ultra-reliable lowlatency communications (URLLC).  \nI. INTRODUCTION  \nA. Background  \nULTRA-reliable low-latency communication (URLLC) is  \none of the major use cases in future communication systems, targeting mission-critical applications, such as autonomous vehicles, telemetry, remote surgery, and factory automation [1]–[4] . In such applications, the transmitted data are often in short packets, carrying certain high-priority command/control signals, life-critical information, or emergency rescue messages. In the fifth-generation (5G) networks, stringent performance requirements should be met by those URLLC applications, including a target block error rate (BLER) of 10 −5 and an end-to-end latency constraint within 1 ms. Moving towards 6G, IMT-2030 further extends URLLC to hyper-reliable and low-latency communication, targeting  \nZhen-Ming Huang is with the Institute of Computer and Communication Engineering, National Cheng Kung University, Tainan 701, Taiwan, R.O.C.(e-mail: [n98101012@gs.ncku.edu.tw](n98101012@gs.ncku.edu.tw)).  \nZilong Liu and Leila Musavian are with the School of Computer Science and Electronic Engineering, University of Essex, CO4 3SQ Colchester, U.K.(e-mail: [zilong.liu@essex.ac.uk](zilong.liu@essex.ac.uk); [leila.musavian@essex.ac.uk](leila.musavian@essex.ac.uk)).  \nChao-Yu Chen is with the Department of Electrical Engineering and the Institute of Communications Engineering, National Cheng Kung University, Tainan 701, Taiwan, R.O.C. (e-mail: [super@mail.ncku.edu.tw](super@mail.ncku.edu.tw)).  \nBLER as low as to 10 −7 and latency of 0.1-1 ms [5] . Conventional coding schemes for ultra-high reliability are feasible for sufficiently long block codes only. New design approaches are needed in view of the short-packet transmission nature and the stringent requirements to reliability and latency in URLLC. To this end, in the sequel, we first introduce sparse vector coding (SVC) and sparse code multiple access (SCMA), and then present SCMA inspired SVC (SCMA-SVC) .  \nB. Related Works  \n1) SVC: In 2018, SVC was proposed as a novel coding technique for short-packet URLLC transmission [6] . In SVC, the basic idea is to map the information bits to certain nonzero elements of a sparse vector, with which one can generate the corresp","cbCaib7ItB6QqRm7","https://ap.wps.com/l/cbCaib7ItB6QqRm7","pdf",711451,3,1,13,"English","en",105,"# Introduction\n## Background\n## Related Works","[{\"question\":\"What is the main contribution of SCMA-SVC?\",\"answer\":\"SCMA-SVC introduces an SCMA-inspired SVC design that uses SCMA’s sparse pattern and multidimensional constellation nature to enlarge the minimum Euclidean distance of SVC codebooks, improving reliability for URLLC.\"},{\"question\":\"How does SCMA-SVC achieve full diversity order?\",\"answer\":\"By applying random phase rotations to the sparse vectors, the scheme is shown to achieve full diversity order over Rayleigh fading channels.\"},{\"question\":\"What decoding approaches are proposed and how do they compare?\",\"answer\":\"The document presents maximum-likelihood (ML) decoding and also develops a low-complexity decoder 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