Dual-Mapping Sparse Vector Transmission for Short Packet URLLC

TL;DR

This paper introduces a dual-mapping sparse vector coding scheme for short packet URLLC, enhancing decoding accuracy and spectral efficiency through combined block and single-element sparse mappings.

Contribution

It proposes a novel dual-mapping SVC scheme with a two-stage decoding process, improving performance over existing SVC methods in URLLC scenarios.

Findings

Outperforms existing SVC schemes in block error rate

Achieves higher spectral efficiency

Demonstrates robustness in simulation results

Abstract

Sparse vector coding (SVC) is a promising short-packet transmission method for ultra reliable low latency communication (URLLC) in next generation communication systems. In this paper, a dual-mapping SVC (DM-SVC) based short packet transmission scheme is proposed to further enhance the transmission performance of SVC. The core idea behind the proposed scheme lies in mapping the transmitted information bits onto sparse vectors via block and single-element sparse mappings. The block sparse mapping pattern is able to concentrate the transmit power in a small number of non-zero blocks thus improving the decoding accuracy, while the single-element sparse mapping pattern ensures that the code length does not increase dramatically with the number of transmitted information bits. At the receiver, a two-stage decoding algorithm is proposed to sequentially identify non-zero block indexes and single-element non-zero indexes. Extensive simulation results verify that proposed DM-SVC scheme outperforms the existing SVC schemes in terms of block error rate and spectral efficiency.