Precoding for Robust Decentralized Estimation in Coherent-MAC-Based Wireless Sensor Networks

This letter proposes novel precoding techniques for robust decentralized parameter estimation with only imperfect channel state information (CSI) in a coherent multiple access channel based wireless sensor network. For scalar parameter estimation, the proposed technique minimizes the worst case estimation error arising due to the channel uncertainties while ensuring the maximum gain at each receive antenna. For vector parameter estimation, since the general noisy measurement case is intractable, a robust precoder is developed for noiseless sensor measurements that eliminates the need for postprocessing at the fusion center while simultaneously minimizing the worst case estimation error. Simulation results show that the proposed techniques have a superior performance in comparison to imperfect CSI agnostic estimation techniques.

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