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Technical Program

Paper Detail

Paper IDD4-S5-T3.2
Paper Title Minimax Bounds for Blind Network Inference
Authors Nishant Mehrotra, Rice University, United States; Eric Graves, Ananthram Swami, U.S. Army Research Laboratory, United States; Ashutosh Sabharwal, Rice University, United States
Session D4-S5-T3: Network Inference
Chaired Session: Thursday, 15 July, 23:20 - 23:40
Engagement Session: Thursday, 15 July, 23:40 - 00:00
Abstract We take the first step towards understanding the fundamental limits of blind wireless network inference performed by a distributed network of single-antenna adversary nodes. The distributed adversary nodes are assumed to be blind to the protocol parameters as well as the modulation, coding and encryption schemes used by the network being monitored. Focusing on the special case of inferring the channel access probabilities of the monitored nodes, we derive minimax bounds for blind inference. We show that blind inference is possible with similar sample complexity (asymptotically) as non-blind inference given certain network connectivity conditions are satisfied.