In industrial Internet of Things (IIoT), short-packet communication requires higher reliability and lower latency, enabling Grant-free (GF) access in massive machine-type communication (mMTC) to gain a tremendous research interest. However, in practical applications, the accurate channel state information (CSI) required by coherent GF (C-GF) is challenging to acquire. Concurrently, the spectral efficiency and reliability of the non-coherent (NC-GF) scheme are areas necessitating enhancement. Inspired by sparse vector coding (SVC), this paper introduces an innovative SVC-GF scheme. This scheme redefines joint user activity detection (UAD) and data decoding as a bifurcated sparse recovery issue. A novel block refinement orthogonal matching pursuit and multipath matching pursuit (BROMP-MMP) algorithm is designed to resolve this intricate problem. Simulation results demonstrate that the proposed SVC-GF scheme outperforms traditional C-GF and NC-GF schemes in terms of probability of successful detection and average block error rate (BLER) performance, heralding a paradigm shift for massive GF access.

Enabling Internet-of-Things (IoT) in fifth generation (5G) networks is challenging due to the low access efficiency in the presence of massive random access (RA) requests. To tackle this, we investigate multi-criterion RA ranking and random access efficiency (RAE) maximization for massive IoT networks to deal with devices' heterogeneity and limited RA resources. A fuzzy logic-guided suitability ranking (FL-SR) scheme is proposed, where multiple criteria are considered such as RA delay, movement speed, and battery capacity to ensure that various service and application requirements are met. With normalized suitability and deployability from the FL-SR scheme, the backoff window size gets more flexible than previous work. A fuzzy logic guided random access efficiency optimization (FL-RAEO) algorithm is proposed to maximize the RAE. Thanks to the derived closed-form expressions for the optimal RAE, the FL-RAEO algorithm achieves optimal performance in average access delay, access throughput. and successful access rate.