Random grouping based resilient beamforming

This paper considers the resilient beamforming problem for a network of collaborative sensors in presence of faulty nodes. The main objective is to synchronize the signal phases at an intended destination and maximize the signal power. Towards this objective, we first propose a random grouping distributed beamforming (RG-DB) algorithm in the fault-free setup. For the RG-DB algorithm, each sensor classifies itself into one of two groups according to a random mechanism over a time horizon, during which a group of sensors control the phases of their transmissions, while the other group of sensors do not update their phases. This paper shows global convergence towards phase synchronization with probability one by applying the RG-DB algorithm. On the basis of the RG-DB algorithm, a random grouping based resilient distributed beamforming (RG-RDB) algorithm is then developed to solve the resilient beamforming problem in presence of faulty sensors. It is shown that the RG-RDB algorithm asymptotically makes the probability of selecting a faulty node for collective signal transmitting converge to zero, and thus solves the resilient beamforming problem by a subset of properly functioning sensors. Simulations are provided validating the algorithms developed in this paper. (c) 2020 Elsevier Ltd. All rights reserved.

Automated summary

This paper proposes algorithms to solve the resilient beamforming problem for a network of collaborative sensors in the presence of faulty nodes. By using the random grouping distributed beamforming and random grouping based resilient distributed beamforming algorithms, the issues of signal phase synchronization and maximizing signal power are addressed, with simulation results validating the algorithm performance.