4th International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications

Research Article

Coexistent intra-symbol SMSE waveform design: Variation in waveform update latency and update rate

  • @INPROCEEDINGS{10.1109/CROWNCOM.2009.5189329,
        author={Eric C. Like and Michael A. Temple},
        title={Coexistent intra-symbol SMSE waveform design: Variation in waveform update latency and update rate},
        proceedings={4th International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications},
        publisher={IEEE},
        proceedings_a={CROWNCOM},
        year={2009},
        month={8},
        keywords={},
        doi={10.1109/CROWNCOM.2009.5189329}
    }
    
  • Eric C. Like
    Michael A. Temple
    Year: 2009
    Coexistent intra-symbol SMSE waveform design: Variation in waveform update latency and update rate
    CROWNCOM
    IEEE
    DOI: 10.1109/CROWNCOM.2009.5189329
Eric C. Like1,2, Michael A. Temple1,2,*
  • 1: Department of Electrical and Computer Engineering, Air Force Institute of Technology
  • 2: Wright-Patterson AFB, OH 45433 USA
*Contact email: michael.temple@afit.edu

Abstract

The impact of variation in waveform update latency and update rate is investigated for Spectrally Modulated, Spectrally Encoded (SMSE) waveform designs in a coexistent environment containing multiple 802.11 Primary User (PU) systems. As previously demonstrated for no latency with a fixed update rate, the SMSE waveform design process can exploit statistical knowledge of PU spectral and temporal behavior to maximize SMSE system throughput (bits/second) while adhering to SMSE and PU bit error rate constraints with mutual coexistent interference limited to manageable levels. Building upon this previous work, a sensitivity analysis is conducted here through parametric variation in both waveform update latency and update rate. Relative to a spectrally-only adapted waveform, the spectrally-temporally adapted waveform provides significant performance improvement. Maximum improvement is achieved using statistic-based prediction of channel temporal conditions and appropriate updating of the SMSE waveform design.