Publication:
Ternary noise modulation

Placeholder

School / College / Institute

Program

KU Authors

Co-Authors

Yapici, E.
Tek, Y. I.

Editor & Affiliation

Compiler & Affiliation

Translator

Other Contributor

Date

Language

eng

Embargo Status

N/A

Journal Title

Journal ISSN

Volume Title

Alternative Title

Abstract

By exploiting noise as an information-bearing re source, noise-driven communication offers a promising frame work for low-complexity wireless system design. In this letter, the scheme of ternary noise modulation (T-NoiseMod) is proposed for noise-based wireless communication scenarios, where infor mation is encoded into the statistical characteristics of artificial noise. Unlike conventional binary NoiseMod, which employs two variance levels, the proposed scheme introduces a third transmission state: intentional silence. By pairing two consecutive noise blocks, the signaling scheme is expanded to eight valid state combinations, enabling the transmission of three information bits per signaling interval. In our proposed scheme, the two stage receiver is developed, consisting of mean-based silent-state detection followed by variance-based low/high classification. An approximate analytical expression for the bit error probability (BEP) is derived for Rayleigh fading. Our computer simulation results match closely with our approximate theoretical results and show the effects of key system parameters. Furthermore, comparisons with binary NoiseMod, Q-NoiseMod, and OODN demonstrate the inherent trade-off between reliability and rate.

Source

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Physical sciences, Engineering, Electrical and electronic engineering, Computer science, Artificial intelligence

Citation

Has Part

Source

IEEE Wireless Communications Letters

Book Series Title

Edition

DOI

10.1109/lwc.2026.3720820

item.page.datauri

Link

Rights

Copyrights Note

Endorsement

Review

Supplemented By

Referenced By

Related Goal

0

Views

0

Downloads

View PlumX Details