Parallel Adaptive Subspace Pursuit Algorithm for Multiuser Detection of Uplink Grant-Free NOMA

摘要

The signal recovery of the uplink grant-free nonorthogonal multiple access system is a challenging problem in random access of massive machine-type communications. In this paper, we propose a low-complexity parallel adaptive subspace pursuit (parallel ASP) algorithm. First, the signal recovery problem is converted into multiple single measurement vector compressive sensing (SMV-CS) problems. Then, the multiple SMV-CS problems are solved by ASP algorithm in parallel. Furthermore, an outer iteration is introduced where the information exchange strategy is designed to leverage the block-wise sparsity. Simulation results show that the proposed algorithm can reduce the computational complexity enormously with only small performance loss compared with conventional block sparsity ASP algorithm.