The Central Detection Officer problem: SALSA detector and performance guarantees

This paper formulates the Central Detection Officer (CDO) problem in which a central officer decides if some agents in a network observe data from an anomalous distribution compared to the majority. Since the data statistics are unknown in advance, the goal of the CDO is to identify the data pattern of each agent and detect the presence and locations of anomalies by polling the agents strategically. To solve the CDO problem in a Gaussian multiple access channel, the Sparsity-Aware Least Squares Anomaly (SALSA) detection scheme is proposed, which combines a type-based encoder for the agents data with a compressive network polling scheme. The performances of the proposed scheme are analyzed theoretically and demonstrated numerically.