Performance analysis of quantized incremental LMS algorithm for distributed adaptive estimation

• DOI: 10.1016/j.sigpro.2010.02.019
• Publication Date: 2010-02-25T10:46:25Z
• Authors: Amir Rastegarnia; Mohammad Ali Tinati; Azam Khalili
• Keywords: 0202 electrical engineering, electronic engineering, information engineering; 02 engineering and technology

Recently distributed adaptive estimation algorithms have been proposed as a solution to the issue of linear estimation over distributed networks. In all previous works, the performance of such algorithms is considered only for infinite-precision arithmetic implementation. In this paper we study the performance of distributed incremental least mean square (DILMS) estimation algorithm when it is implemented in finite-precision arithmetic. To this aim, we first derive the quantized version of the DILMS algorithm. Then a spatial-temporal energy conservation argument is used to derive theoretical expressions that evaluate the steady-state performance of individual nodes in the network. Simulation results show that there is a good match between the theory and simulation.