Joint Detection and Communication over Type-Sensitive Networks
Abstract
Due to the difficulty of decentralized inference with conditional dependent observations, and motivated by large-scale heterogeneous networks, we formulate a framework for decentralized detection with coupled observations. Each agent has a state, and the empirical distribution of all agents’ states or the type of network dictates the individual agents’ behavior. In particular, agents’ observations depend on both the underlying hypothesis as well as the empirical distribution of the agents’ states. Hence, our framework captures a high degree of coupling, in that an individual agent’s behavior depends on both the underlying hypothesis and the behavior of all other agents in the network. Considering this framework, the method of types, and a series of equicontinuity arguments, we derive the error exponent for the case in which all agents are identical and show that this error exponent depends on only a single empirical distribution. The analysis is extended to the multi-class case, and numerical results with state-dependent agent signaling and state-dependent channels highlight the utility of the proposed framework for analysis of highly coupled environments.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Sep 08, 2023
- Source ID
- 10.3390/e25091313
Entities
People
- Joni Shaska
- Urbashi Mitra
Organizations
- Army Research Office
- National Science Foundation
- Office of Naval Research
- Swedish Research Council
- United States Department of Energy
- University of Southern California