Distributed Decision Fusion With M -ary Source Coding On Sensor Observation and Uncoded Data Transmission

Abstract

M -ary source coding scheme on sensor detection is able to improve the detection performance on the final decision made at the fusion center (FC). In this paper, a new $M$ -ary source coding scheme using analog transmission is proposed for distributed binary detection. In the scheme, the source coding is through the quantization process, but the output of the quantizer is transmitted directly without digitalizing and coding process. In the FC, the linear combiner detection rule is adopted to make the final decision. The problem of huge channel bandwidth demand can be avoided by using the considered Mary source coding scheme. The goal of the proposed scheme is to minimize the decision errors at the FC via optimizing the region allocation. The error performances using maximum-a-posteriori (MAP) and equal-gain-combining (EGC) fusion rules are analyzed. The proposed $M$ -ary source coding scheme is illustrated with numerical examples highlighting its significant improvement in error performance and enhanced information available at the FC when the transmission is via either additive white Gaussian noise (AWGN) or Rayleigh faded channel.