• Adaptive OFDM for Aeronautical Channels

      Moazzami, Farzad; Dean, Richard; Zegeye, Wondimu K.; Alam, Tasmeer; Morgan State University, Dept Electrical and Computer Engineering (International Foundation for Telemetering, 2019-10)
      Previous work modeled the cruise phase of an aeronautical channel and showed how the channel varied as a function of height, distance, and speed. What was apparent from that analysis was that the ``cruise" channel was remarkable stable and varied slowly and predictably over time. The steady state channel reflected a 2-ray multipath model which exhibits deep nulls in the spectrum which affects serial tone modems significantly. Further the application of parallel tone modulation improves performance except for that portion of the band which was degraded by the null. This points to the use of Adaptive OFDM (AOFDM) structure wherein tones are only sent in portions of the band which are strong and not areas where the signal is weak. This work develops a method for capturing a profile of the Signal to Distortion Ratio (SDR) for each tone for each frame and over time. It also develops a method for converting the SDR per tone to estimate the optimum QAM modulation scheme for each tone for application in Link Dependent Adaptive Radio (LDAR).
    • Multi-Stage Attack Detection Using Layered Hidden Markov Model Intrusion Detection System

      Moazzami, Farzad; Dean, Richard; Zegeye, Wondimu K.; Morgan State University, Dept Electrical and Computer Engineering (International Foundation for Telemetering, 2019-10)
      Intrusion Detection Systems (IDS) based on Artificial Intelligence can be deployed to protect telemetry networks against intruders. As security solutions which encrypt radio links do not accommodate the ever evolving network attacks and vulnerabilities, new defense mechanisms using machine learning and artificial intelligence can play a significant role for telemetry networks. This paper proposes a multi-layered Hidden Markov Model (HMM) IDS that addresses multi-stage attacks. This is due to the fact that intrusions are increasingly being launched through multiple phases instead of single stage intrusion. This layered model divides the problem space into smaller manageable pieces reducing the curse of dimensionality associated with HMMs. To verify the application of this model for real network, the NSL-KDD dataset is used to train and test the model.
    • Peak-to-Average Power Ratio (PAPR) Reduction for OFDM

      Moazzami, Farzad; Dean, Richard; Zegeye, Wondimu K.; Morgan State University, Dept Electrical and Computer Engineering (International Foundation for Telemetering, 2019-10)
      The telemetry community has been challenged in its search for additional spectrum for its aeronautical mission. With a fixed amount of spectrum the challenge becomes focused on increased spectrum efficiency. Today’s best solution for spectrum efficiency is Orthogonal Frequency Division Modulation (OFDM). This approach has proven effective with both cellular LTE as well as IEEE 802.11 wireless LAN systems. OFDM has seen limited use in telemetry systems in part due to issues related to high peak to average ratio of OFDM signals. This paper reviews approaches to resolving these issues and proposes a scheme for peak conditioning of OFDM signals to reduce the peak to average ratio. Results of preliminary experimental work are promising.