A MOBILE WIRELESS CHANNEL DISPERSION STATE MODEL Enabling Cognitive Processing Situational Awareness

Communication traffic is vulnerable to timevariant wireless channel conditions such as: fading, time dispersive, or frequency dispersive distortion which can render nonadaptive communication processing ineffective. This paper surveys published wireless channel multistate hidden Markov models (HMM) revealing mature applications of HMMs and several approaches for modeling wireless channel parameters however none have been found that model channel dispersion and related conditions such as frequency selectivity and/or time selectivity. Therefore, a mobile wireless channel dispersion state model (DSM) is proposed to provide channel distortion awareness. The authors introduce a mobile wireless channel DSM linking time-variant non-dispersive, single, or dualdispersive channel states and signal to noise ratio (SNR) loss/distortion mitigation methods. If the DSM is coupled with a channel state recognition (CSR) process, channel distortion awareness is provided for cognitive processing. This enables near-real-time selections between appropriate SNR loss and inter-symbol interference (ISI)/interfrequency interference (IFI) mitigation methods. The effectiveness of the DSM coupled with a CSR algorithm is demonstrated by the application of reference waveform symbol streams to a recognition HMM. Simulation results agree with published standard HMM recognition accuracy in terms of sensitivity and specificity. The research results validate the utility of the DSM in time-variant mobile wireless channels and establishes a performance baseline for benchmarking future CSR algorithm research. KeywordsChannel State Recognition; Cognitive Radio; Dispersion State Model; Distortion Mitigation; Mobile Wireless Channel State Model; Mobile Wireless Channel Dispersion State Model; Mobile Wireless Channel Environmental Awareness; Mobile Wireless Channel Situational Awareness; Mobile Wireless Channel State Recognition; Software Defined Radio.