Decentralized detection over multiple-access channels

We study the decentralized detection problem in a general framework where arbitrary number of quantization levels at the local sensors are allowed, and transmission from the sensors to the fusion center is subject to both noise and interchannel interference. We treat both Bayesian and Neyman-Pearson approaches to the problem, and develop an iterative descent algorithm to design the optimal quantizers and fusion rule. Some numerical examples for both approaches are also presented.