학술논문

Beyond the Bound: A New Performance Perspective for Identification via Channels
Document Type
Periodical
Source
IEEE Journal on Selected Areas in Communications IEEE J. Select. Areas Commun. Selected Areas in Communications, IEEE Journal on. 41(8):2687-2706 Aug, 2023
Subject
Communication, Networking and Broadcast Technologies
Codes
Encoding
Robot kinematics
Tagging
Digital twins
Reed-Solomon codes
Upper bound
Error probability
false-positive identification
goal-oriented communication
identity verification
performance metrics
probabilistic performance
Language
ISSN
0733-8716
1558-0008
Abstract
Identification via channels (ID) is a goal-oriented (Post-Shannon) communications paradigm that verifies the matching of message (identity) pairs at source and sink. To date, ID research has focused on the upper bound $\lambda $ for the probability of a false-positive (FP) identity match, mainly through ID tagging codes that represent the identities through ID codeword sets consisting of position-tag tuples. We broaden the ID research scope by introducing novel ID performance metrics: the expected FP-error probability $\overline {p_{\mathrm {fp}}}$ which considers distance properties of ID codeword sets in conjunction with the probability for selecting ID pairs, the threshold probabilities $p_{\epsilon }$ that characterize quantiles of FP-probabilities, and the distance tail uplift ratio DiTUR giving the fraction of ID pairs whose distance is increased above the minimum distance (which corresponds to $\lambda $ ). We define a No-Code (NC) approach that directly conducts the ID operations with the messages (identities) without any additional coding as a baseline for ID. We investigate a concatenated Reed-Solomon ID code and a Reed-Muller ID code, and find that they do not always yield advantages over using no ID code. We analytically characterize the reduction of error-prone ID pairs through sending multiple tags. Overall, our insights point to investigating the distance distribution of ID codes and to incorporating the ID pair distributions of real ID systems in future ID research.