Abstract

Grant-free (GF) access is one key technology for massive machine-type communication (mMTC) in Internet-of-things. Single-carrier (SC) modulation has higher power-efficiency than multicarrier modulation such as orthogonal frequency division multiplexing, due to lower peak-to-average power ratio, and thus is specifically suitable for low-power-supply machine-type devices. In this paper, we study both the coherent and non-coherent grant-free non-orthogonal multiple access (GF-NOMA) schemes where SC modulation is employed in frequency selective fading channels. For coherent SC-GF-NOMA, the linear input-output relation is first presented, and two user-activity detection (UAD) algorithms, block covariance-based maximum-likelihood detection (CB-MLD) and turbo approximated message passing (Turbo AMP), are proposed. In block CB-MLD, a block update strategy is introduced in the coordinate descent iteration to utilize the special block-sparsity signal property inherent in coherent SC-GF-NOMA. Moreover, Turbo AMP consists of two components, AMP and message passing (MP), and turbo iteration between them. Concretely, AMP is designed for UAD-CE with fixed active user probability, and MP is designed to update the active user probability by utilizing the block sparsity. Moreover, the performance of Turbo AMP is analyzed by state-evolution (SE) formalism. For non-coherent SC-GF-NOMA, the linear input-output relation is first derived from which the hierarchical block-sparsity signal property is observed, and then block CB-MLD-based UAD algorithm is presented to utilize this signal property. Finally, computer simulation results are given to demonstrate the effectiveness of the proposed algorithms in both coherent and non-coherent SC-GF-NOMA.

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