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In this study, energy-efficient deterministic adaptive beamforming algorithmsare proposed for distributed sensor/relay networks. Specifically, DBSA, D-QESA,D-QESA-E, and a hybrid algorithm, hybrid-QESA, that combines the benefits ofboth deterministic and random adaptive beamforming algorithms, are proposed.Rigorous convergence analyses are provided for all our proposed algorithms andconvergence to the global optimal solution is shown for all our proposedalgorithms. Through extensive numerical simulations, we demonstrate thatsuperior performance is achieved by our proposed DBSA and D-QESA over randomadaptive beamforming algorithms for static channels. Surprisingly, D-QESA isalso more robust against random node removal than random adaptive beamformingalgorithms. For time-varying channels, hybrid-QESA indeed achieves the bestperformance since it combines the benefits of both types of adaptivebeamforming algorithms. In summary, our proposed deterministic algorithmsdemonstrate superior performance both in terms of convergence time androbustness against channel and network uncertainties.

Energy-Efficient Deterministic Adaptive Beamforming Algorithms for Distributed Sensor/Relay Networks