Eric C. Like

Date of Award


Document Type


Degree Name

Doctor of Philosophy (PhD)


Department of Electrical and Computer Engineering

First Advisor

Michael A. Temple, PhD


This work expands the applicability of the Spectrally Modulated, Spectrally Encoded (SMSE) framework by developing a waveform optimization process that enables intelligent waveform design. The resultant waveforms are capable of adapting to a spectrally diverse transmission channel while meeting coexistent constraints. SMSE waveform design is investigated with respect to two different forms of coexisting signal constraints, including those based on resultant interference levels and those based on resultant power spectrum shape. As demonstrated, the SMSE framework is well-suited for waveform optimization given its ability to allow independent design of spectral parameters. This utility is greatly enhanced when soft decision selection and dynamic assignment of SMSE design parameters are incorporated. Results show that by exploiting statistical knowledge of primary user spectral and temporal behavior, the inherent flexibility of the SMSE framework is effectively leveraged such that SMSE throughput (Bits/Sec) is maximized while limiting mutual coexistent interference to manageable levels.

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DTIC Accession Number