Improved Multiband-Structured Subband Adaptive Filter Algorithm in Diffusion Distributed Networks

Adaptive algorithms play an important role in order to improve performance of diffusion distributed network. In comparison of diffusion Normalized least mean square algorithm, family of diffusion subband algorithms have faster convergence rate when the input signal is highly correlated. This paper solves the problem of distributed estimation in the diffusion networks based on improved multiband-structured subband adaptive filter (IMSAF) and diffusion improved multiband structured subband adaptive filter (DIMSAF) is established. In proposed algorithm, convergence behavior improved due to using several input projections instead of single vector of input data. In addition, when the projection order is increased, the convergence rate of the proposed algorithm improves. The validity of the DIMSAF in comparison of DLMS, DAPA, VSS-DAPA and DRLS algorithms is demonstrated by several computer simulations. The results show fastest convergence rate.