Efficient Identification of IIR Systems in Sensor Nodes using Diffusion Particle Swarm Optimization for Wireless Sensor Networks
Keywords:
Least Mean Square, Particle Swarm Optimization, Mean Square Error, Infinite Impulse Response, Parameter EstimationAbstract
Most distributed estimation algorithms have traditionally been designed for stable systems such as Finite Impulse Response (FIR) systems. However, recognizing that real-world systems are not always stable, this paper proposes distributed estimation for Infinite Impulse Response (IIR) systems. It focuses on diffusion-based cooperation among adaptive nodes, which is crucial for handling system instability. This approach ensures adaptability to changes in network topology, maintaining good performance even in the face of link and node failures. Simulation results demonstrate that the proposed IIR DPSO (Infinite Impulse Response diffusion particle swarm optimization) algorithm achieves comparable Mean Square Error (MSE) to the conventional IIR ILMS (Infinite Impulse Response Incremental least mean square) algorithm. Moreover, the proposed algorithm exhibits robustness to link failures, making it suitable for large-scale networks and adaptable to changing network configurations.
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