Sparse Vector Coding for 5G Ultra-Reliable and Low Latency Communications

Abstract

Ultra reliable and low latency communication (URLLC) is a newly introduced service category in 5G to support delay-sensitive applications. In order to support this new service category, 3rd Generation Partnership Project (3GPP) sets an aggressive requirement that a packet should be delivered with 10^-5 block error rate within 1 ms transmission period. Since the current wireless standard designed to maximize the coding gain by transmitting capacity achieving long code-block is not relevant for this purpose, entirely new transmission strategy is required. In this paper, we propose a new approach to transmit short packet information, called sparse vector coding (SVC). Key idea behind the proposed method is to transmit the control channel information after the sparse vector transformation. By mapping the transmit information into the position of nonzero elements and then transmitting it after the random spreading, we obtain underdetermined sparse system for which the principle of compressed sensing can be applied. From the numerical evaluations on realistic channel setting and decoder performance analysis, we demonstrate that the proposed SVC technique is very effective in URLLC transmission and outperforms the 4G LTE and LTE-Advanced physical downlink control channel (PDCCH) scheme.