Abstract-We study the detection error probability associated with a balanced binary relay tree, where the leaves of the tree correspond to N identical and independent sensors. The root of the tree represents a fusion center that makes the overall detection decision. Each of the other nodes in the tree are relay nodes that combine two binary messages to form a single output binary message. Only the leaves of the tree are sensors. In this way, the information from the sensors is aggregated into the fusion center via the intermediate relay nodes. In this context, we describe the evolution of Type I and Type II error probabilities of the binary data as it propagates from the leaves towards the root. Tight upper and lower bounds for the total error probability at the fusion center as functions of N are derived. These characterize how fast the total error probability converges to 0 with respect to N .
We study in REF the error probability convergence rate in balanced binary relay trees, where each nonleaf agent in this tree has two child agents and all the leaf agents are at the same distance from the root.
Error probability bounds for balanced binary relay trees
IEEE Conference on Decision and Control and European Control Conference
IEEE Conference on Decision and Control and European Control Conference
Mathematics Computer Science