Grant-Free Transmission by LDPC Matrix Mapping and Integrated Cover-MPA Detector

Abstract

In this paper, a novel transceiver architecture is proposed to simultaneously achieve efficient random access and reliable data transmission in massive IoT networks. At the transmitter side, each user is assigned a unique protocol sequence which is used to identify the user and also indicate the user's channel access pattern. Hence, user identification is completed by the detection of channel access patterns. Particularly, the columns of a parity check matrix of low-density-parity-check (LDPC) code are employed as protocol sequences. The design guideline of this LDPC parity check matrix and the associated performance analysis are provided in this paper. At the receiver side, a two-stage iterative detection architecture is designed, which consists of a group testing component and a payload data decoding component. They collaborate in a way that the group testing component maps detected protocol sequences to a tanner graph, on which the second component could execute its message passing algorithm. In turn, zero symbols detected by the message passing algorithm of the second component indicate potential false alarms made by the first group testing component. Hence, the tanner graph could iteratively evolve. The provided simulation results demonstrate that our transceiver design realizes a practical one-step grant-free transmission and has a compelling performance.