Date of Award

Fall 2025

Document Type

Open Access Thesis

Department

Electrical Engineering

First Advisor

Alphan Şahin

Abstract

Non-coherent communication has emerged as a promising approach to address several challenges at the physical layer. A particular scheme called binary modulation on conjugate-reciprocal zeros (BMOCZ) uses the zeros (i.e, roots) of a polynomial to convey information bits. In this thesis, we strive to improve the reliability of BMOCZ in various scenarios. In particular, we utilize machine learning (ML) methods to determine the parameters for BMOCZ and improve upon the decoding performance. Moreover, we introduce a smooshed BMOCZ variant to combat typical impairments encountered within wireless communications, including timing offsets (TOs) for noncoherent orthogonal frequency division multiplexing (OFDM). Through numerical simulations, we show that the proposed methodologies achieve gains in bit error rate (BER) and block error rate (BLER) relative to conventional designs, thereby improving the robustness of BMOCZ for non-coherent wireless communication.

Rights

©2025, Anthony Joseph Perre

Share

COinS