SMSE Waveform Design Using Soft Decision Selection and Dynamic Assignment of Subcarrier Modulation Order and Power

Abstract

Spectrally Modulated, Spectrally Encoded (SMSE) waveforms have demonstrated considerable practical utility and remain a viable alternative for Cognitive Radio (CR) -based Software Defined Radio (SDR) applications. As demonstrated in this paper, this utility is greatly enhanced when soft decision selection and dynamic assignment of SMSE design parameters is incorporated. This paper provides the analytical development for optimizing SMSE performance in a coexistent environment containing Primary User (PU) signals. Optimization is performed by exploiting statistical knowledge of PU spectral and temporal behavior, and independently selecting SMSE intra-symbol subcarrier power and modulation order using soft decision criteria. It is shown that SMSE system throughput can be maximized while adhering to SMSE and PU bit error rate (BER) constraints while limiting mutual coexistent interference to manageable levels. For proof-of-concept demonstration, simulation results are presented for SMSE coexistent scenarios containing DSSS and OFDM-based 802.11a PU signals. A sensitivity analysis is also provided to show performance changes resulting from variation in SMSE waveform update latency and update interval. Relative to a spectrally-only adapted waveform, the spectrally-temporally adapted SMSE waveform provides significant performance improvement. Maximum improvement is achieved using statistic-based prediction of PU channel temporal conditions and the appropriate SMSE waveform design update interval.