Optimal Resource Allocation for Detection of a Gaussian Process Using a MAC in WSNs

We analyze a binary hypothesis testing problem built on a wireless sensor network (WSN) for detecting a stationary random process distributed both in space and time with a circularly-symmetric complex Gaussian distribution under the Neyman-Pearson (NP) framework. Using an analog scheme, the sensors transmit different linear combinations of their measurements through a multiple access channel (MAC) to reach the fusion center (FC), whose task is...