Facilitating Wireless Communications through Intelligent Resource Management on Software-Defined Radios in Dynamic Spectrum Environments

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Virginia Tech


This dissertation provides theory and analysis on the impact resource management has on software-defined radio platforms by investigating the inherent trade-off between spectrum and processing effciencies with their relation to both the power consumed by the host processor and the complexity of the algorithm which it can support. The analysis demonstrates that considerable resource savings can be gained without compromising the resulting quality of service to the user, concentrating specifically on physical-layer signal processing elements commonly found in software definitions of single- and multi-carrier communications signals.

Novel synchronization techniques and estimators for unknown physical layer reference parameters are introduced which complement the energy-quality scalability of software-defined receivers. A new framing structure is proposed for single-carrier systems which enables fast synchronization of short packet bursts, applicable for use in dynamic spectrum access. The frame is embedded with information describing its own structure, permitting the receiver to automatically modify its software configuration, promoting full waveformfl‚exibility for adapting to quickly changing wireless channels. The synchronizer's acquisition time is reduced by exploiting cyclostationary properties in the preamble of transmitted framing structure, and the results are validated over the air in a wireless multi-path laboratory environment. Multi-carrier analysis is concentrated on synchronizing orthogonal frequency-division multiplexing (OFDM) using offset quadrature amplitude modulation (OFDM/OQAM) which is shown to have significant spectral compactness advantages over traditional OFDM. Demodulation of OFDM/OQAM is accomplished using computationally effcient polyphase analysis filterbanks, enabled by a novel approximate square-root Nyquist filter design based on the near-optimum Kaiser-Bessel window. Furthermore, recovery of sample timing and carrier frequency offsets are shown to be possible entirely in the frequency domain, enabling demodulation in the presence of strong interference signals while promoting heterogeneous signal coexistence in dynamic spectrum environments.

Resource management is accomplished through the introduction of a self-monitoring framework which permits system-level feedback to the radio at run time. The architecture permits the radio to monitor its own processor usage, demonstrating considerable savings in computation bandwidths on the tested platform. Resource management is assisted by supervised intelligent heuristic-based learning algorithms which use software-level feedback of the radio's active resource consumption to optimize energy and processing effciencies in dynamic spectrum environments. In particular, a case database-enabled cognitive engine is proposed which abstracts from the radio application by using specific knowledge of previous experience rather than relying on general knowledge within a specific problem domain.



software-defined radio, synchronization, cognitive engine, Cognitive radio networks, OFDM/OQAM