Distributed Delay and Sum Beamformer in Regular Networks Based on Synchronous Randomized Gossip

In this paper, we review and propose an improvement on an earlier proposed distributed delay and sum beamformer (DDSB). In the original DDSB, each pair of neighboring nodes updates their estimates asynchronously, which may yield a relatively slow convergence, especially when the size of network is large. When multiple pairs of neighboring nodes update simultaneously, the algorithm converges potentially faster. We propose an improved synchronous DDSB in a regular network based on synchronous randomized gossip. Moreover, we provide a comparison of the convergence rate of the asynchronous DDSB with the original and with the improved synchronous DDSB. The simulation results show the faster convergence results and show that the DDSB using the different updating schemes converges to the centralized beamformer.