Loading [a11y]/accessibility-menu.js
When Statistical Signal Transmission Meets Nonorthogonal Multiple Access: A Potential Solution for Industrial Internet of Things | IEEE Journals & Magazine | IEEE Xplore

When Statistical Signal Transmission Meets Nonorthogonal Multiple Access: A Potential Solution for Industrial Internet of Things


Abstract:

With the global promotion of fifth-generation (5G) communications, researches for sixth generation (6G) communications are being globally launched from various perspectiv...Show More

Abstract:

With the global promotion of fifth-generation (5G) communications, researches for sixth generation (6G) communications are being globally launched from various perspectives. Industrial Internet of Things (IIoT), which is the most representative application that reflects the ubiquitous connectivity characteristics of 6G, has attracted much attention. To explore for a feasible perspective in promoting ubiquitous connectivity and improving IIoT abilities, in this article, we seek solutions to incorporate two promising techniques, i.e., nonorthogonal multiple access (NOMA) and statistical signal transmission (SST). To accomplish such a motivation, we conceive the feasible transceiver architecture for the union of NOMA-SST technique, and elaborate workflow and detection procedures for both uplink and downlink modes. A dedicated resilient window strategy is designed thereafter, which largely strengthen weaker NOMA users’ SST performance without depressing stronger users. The proposed technique is finally testified through both simulation experiments and practical applications. Numerical results verify that NOMA-SST technique has satisfactory detection performance in common IIoT environments. It is also manifested that the proposed technique can refine various aspects, including recall rate and sensing accuracy of monitoring services, successful handling rate of emergency situations, etc., for practical IIoT applications. Such advantages are promising for practice.
Published in: IEEE Internet of Things Journal ( Volume: 11, Issue: 20, 15 October 2024)
Page(s): 33459 - 33476
Date of Publication: 19 July 2024

ISSN Information:

Funding Agency:


References

References is not available for this document.