Sparsity-Inspired Sphere Decoding (SI-SD): A Novel Blind Detection Algorithm for Uplink Grant-Free Sparse Code Multiple Access

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.