  In a wireless sensor network, multilevel quantization is necessary in order
to find a compromise between the smallest possible power consumption of the
sensors and the detection performance at the fusion center (FC). The general
methodology is using distance measures such as J-divergence and Bhattacharyya
distance in this quantization. This work proposes a different approach which is
based on maximizing the average output entropy of the sensors under both
hypotheses and utilizes it in a Neyman-Pearson criterion based distributed
detection scheme in order to detect a point source. The receiver operating
characteristics of the proposed maximum average entropy (MAE) method in
quantizing sensor outputs was obtained for multilevel quantization both when
the sensor outputs are available error-free at the FC and when non-coherent
M-ary frequency shift keying communication is used for transmitting MAE based
multilevel quantized sensor outputs over a Rayleigh fading channel. The
simulation studies show the success of the MAE both in the cases of isolated
error-free fusion and in the case where the effect of the wireless channel is
incorporated. As expected the performance gets better as the level of
quantization increases and with six-level quantization it approaches the
performance of non-quantized data transmission.
