A1432
Title: Prediction compensation-based recursive estimation with uniform quantization and random access protocol
Authors: Jiaxing Li - Harbin University of Science and Technology (China)
Raquel Caballero-Aguila - Universidad de Jaen (Spain) [presenting]
Jun Hu - Harbin University of Science and Technology (China)
Josefa Linares-Perez - Universidad de Granada (Spain)
Abstract: The focus is on the recursive estimation problem for networked systems in the presence of uniform quantization and random access protocol with a prediction compensation strategy. The observations are quantized via the uniform quantizer to adapt to the digital transmission requirements. For the sake of improving communication efficiency and reducing resource consumption, the random access protocol is employed to schedule the obtained quantized observations, in which a prediction compensation strategy is utilized to mitigate the side effects of incomplete observations induced by the consideration of the random access protocol. Under the assumption that the evolution of the signal process is unknown and only the mathematical expectation and covariance of the signal process are given, a novel recursive least-squares linear estimation algorithm is proposed in light of an innovative approach. Finally, the validity of the developed recursive estimation algorithm is demonstrated by a numerical simulation experiment. In sum, the designed recursive estimation algorithm is beneficial for the development of signal processing in the context of networked environments, especially for cases including uniformly quantized observations and random access protocol.
