Fixed-symbol aided random access scheme for machine-to-machine communications

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

3 Scopus Citations
View graph of relations

Author(s)

  • Zhaoji Zhang
  • Ying Li
  • Lei Liu
  • Wei Hou

Related Research Unit(s)

Detail(s)

Original languageEnglish
Article number8695167
Pages (from-to)52913-52928
Journal / PublicationIEEE Access
Volume7
Online published22 Apr 2019
Publication statusPublished - 2019

Abstract

The massiveness of devices in crowded Machine-to-Machine (M2M) communications brings new challenges to existing random-access (RA) schemes, such as heavy signaling overhead and severe access collisions. In order to reduce the signaling overhead, we propose a fixed-symbol aided RA scheme where active devices access the network in a grant-free method, i.e., data packets are directly transmitted in randomly chosen slots. To further address the access collision which impedes the activity detection, one fixed symbol is inserted into each transmitted data packet in the proposed scheme. An iterative message passing-based activity detection (MP-AD) algorithm is performed upon the received signal of this fixed symbol to detect the device activity in each slot. In addition, the deep neural network-aided MP-AD (DNN-MP-AD) algorithm is further designed to alleviate the correlation problem of the iterative message passing process. In the DNN-MP-AD algorithm, the iterative message passing process is transferred from a factor graph to a DNN. Weights are imposed on the messages in the DNN and further trained to improve the accuracy of the device activity detection. Finally, numerical simulations are provided for the throughput of the proposed RA scheme, the accuracy of the proposed MP-AD algorithm, and the improvement brought by the DNN-MP-AD algorithm.

Research Area(s)

  • deep neural network, M2M communications, message passing detection, random access

Citation Format(s)

Fixed-symbol aided random access scheme for machine-to-machine communications. / Zhang, Zhaoji; Li, Ying; Liu, Lei; Hou, Wei.

In: IEEE Access, Vol. 7, 8695167, 2019, p. 52913-52928.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review