A combined decision fusion and channel coding scheme for distributed fault-tolerant classification in wireless sensor networks

In this paper, we consider the distributed classification problem in wireless sensor networks. Local decisions made by local sensors, possibly in the presence of faults, are transmitted to a fusion center through fading channels. Classification performance could be degraded due to the errors caused by both sensor faults and fading channels. Integrating channel decoding into the distributed fault-tolerant classification fusion algorithm, we obtain a new fusion rule that combines both soft-decision decoding and local decision rules without introducing any redundancy. The soft decoding scheme is utilized to combat channel fading, while the distributed classification fusion structure using error correcting codes provides good sensor fault-tolerance capability. Asymptotic performance of the proposed approach is also investigated. Performance evaluation of the proposed approach with both sensor faults and fading channel impairments is carried out. These results show that the proposed approach outperforms the system employing the MAP fusion rule designed without regard to sensor faults and the multiclass equal gain combining fusion rule