Spectrally-Temporally Adapted Spectrally Modulated Spectrally Encoded (SMSE) Waveform Design for Coexistent CR-Based SDR Applications

Abstract

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.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2010
Accession Number
ADA516004

Entities

People

  • Eric C. Like

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force
  • Carrier Frequencies
  • Climate Change
  • Cognitive Radio
  • Communication Systems
  • Department Of Defense
  • Frequency Agility
  • Frequency Domain
  • Information Operations
  • Modulation
  • Multiple Access
  • Orthogonal Frequency Division Multiplexing
  • Power Spectra
  • Probability Distributions
  • Random Variables
  • Software Defined Radio
  • Waveforms

Fields of Study

  • Engineering

Readers

  • Neural Network Machine Learning.
  • Radio communications and signal processing.
  • Systems Analysis and Design