Sparse Vector Coding Aided Ultra-Reliable and Low-Latency Communications in Multi-User Massive MIMO Systems

Abstract

Ultra-reliable and low-latency communication (URLLC) has been recognized as a key service to support delay-sensitive applications for next generation wireless systems. A critical challenge is how to support multiple users with ultra reliability in the short packet transmission. In this paper, we propose a sparse vector coding (SVC)-aided URLLC multi-user transmission scheme by employing the massive multiple-input multiple-output (MIMO) technique. To reliably acquire the support information, we formulate the SVC decoding problem in multi-user massive MIMO systems as the problem to find out nonzero positions of a sparse vector. Then, the support recovery problem is transformed into a series of sub-problems by decoupling the support identification of each user, where the successive interference cancellation based matching pursuit (SIC-MP) algorithm is proposed to estimate the support sequentially. In addition, the user sorting scheme is proposed to alleviate the inter-user interference in the SVC decoding. The complexity of the proposed SIC-MP algorithm is only linear with the system parameters.