Steady-state analysis of a quantized average consensus algorithm using state-space description

Following our recently developed method we provide a proof of convergence of the average consensus algorithm with quantized communication links as proposed by Censi and Murray. Using a state-space framework for describing distributed algorithms, we can derive accurate bounds on the drift from the mean for algorithms with noisy links, either caused by an external noise or by quantization. We then test these bounds for several network topologies and compare with simulations.