Title | ||
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Sparsity-Inspired Sphere Decoding(Si-Sd): A Novel Blind Detection Algorithm For Uplink Grant-Free Sparse Code Multiple Access |
Abstract | ||
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Sparse code multiple access (SCMA), as a promising non-orthogonal multiple access scheme for the 5G system, aims to achieve massive connections and grant-free transmission in the radio access scenario. In this paper, we propose a blind detection scheme for the uplink grant-free SCMA transmission based on a novel sparsity-inspired sphere decoding (SI-SD) algorithm. By introducing one additional all-zero code word, each user's status and data can be jointly detected, thus avoiding the redundant pilot overhead. Considering the sparsity features in the grant-free SCMA transmission, we establish its mathematical model where the degree of sparsity is characterized by a transmission probability parameter, which will be estimated during the SI-SD detection process. With such a priori probability, the proposed SI-SD algorithm will achieve the maximum a posteriori (MAP) detection. Furthermore, unlike the conventional sphere decoding, in the grant-free SCMA scenario, strong constraints are proven to exist among the nodes in the proposed SI-SD algorithm which can be utilized to early remove some improbable transmit hypotheses. In addition, a reduced sparsity-inspired MAP metric constitutes a tight sphere constraint which in turn implies less valid hypotheses within the search sphere. By using the above two strategies, the complexity of the SI-SD can be efficiently reduced. |
Year | DOI | Venue |
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2017 | 10.1109/ACCESS.2017.2752741 | IEEE ACCESS |
Keywords | Field | DocType |
5G, SCMA, grant-free, sparsity, sphere decoding | A priori probability,Computer science,Algorithm,Feature extraction,Modulation,Code word,Maximum a posteriori estimation,Decoding methods,Detector,Telecommunications link | Journal |
Volume | ISSN | Citations |
5 | 2169-3536 | 2 |
PageRank | References | Authors |
0.39 | 10 | 4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Guangjin Chen | 1 | 3 | 1.07 |
jincheng dai | 2 | 6 | 3.85 |
Kai Niu | 3 | 561 | 86.80 |
Chao Dong | 4 | 24 | 15.66 |