TU Darmstadt / ULB / TUbiblio

Deterministic Identification for Molecular Communications Over the Poisson Channel

Salariseddigh, Mohammad Javad ; Jamali, Vahid ; Pereg, Uzi ; Boche, Holger ; Deppe, Christian ; Schober, Robert (2023)
Deterministic Identification for Molecular Communications Over the Poisson Channel.
In: IEEE Transactions on Molecular, Biological and Multi-Scale Communications, 9 (4)
doi: 10.1109/TMBMC.2023.3324487
Artikel, Bibliographie

Kurzbeschreibung (Abstract)

Various applications of molecular communications (MC) are event-triggered, and, as a consequence, the prevalent Shannon capacity may not be the right measure for performance assessment. Thus, in this paper, we motivate and establish the identification capacity as an alternative metric. In particular, we study deterministic identification (DI) for the discrete-time Poisson channel (DTPC), subject to an average and a peak molecule release rate constraint, which serves as a model for MC systems employing molecule counting receivers. It is established that the number of different messages that can be reliably identified for this channel scales as 2(nlogn)R , where n and R are the codeword length and coding rate, respectively. Lower and upper bounds on the DI capacity of the DTPC are developed. The obtained large capacity of the DI channel sheds light on the performance of natural DI systems such as natural olfaction, which are known for their extremely large chemical discriminatory power in biology. Furthermore, numerical results for the empirical miss-identification and false identification error rates are provided for finite length codes. This allows us to characterize the behaviour of the error rate for increasing codeword lengths, which complements our theoretically-derived scale for asymptotically large codeword lengths.

Typ des Eintrags: Artikel
Erschienen: 2023
Autor(en): Salariseddigh, Mohammad Javad ; Jamali, Vahid ; Pereg, Uzi ; Boche, Holger ; Deppe, Christian ; Schober, Robert
Art des Eintrags: Bibliographie
Titel: Deterministic Identification for Molecular Communications Over the Poisson Channel
Sprache: Englisch
Publikationsjahr: 13 Oktober 2023
Verlag: IEEE
Titel der Zeitschrift, Zeitung oder Schriftenreihe: IEEE Transactions on Molecular, Biological and Multi-Scale Communications
Jahrgang/Volume einer Zeitschrift: 9
(Heft-)Nummer: 4
DOI: 10.1109/TMBMC.2023.3324487
Kurzbeschreibung (Abstract):

Various applications of molecular communications (MC) are event-triggered, and, as a consequence, the prevalent Shannon capacity may not be the right measure for performance assessment. Thus, in this paper, we motivate and establish the identification capacity as an alternative metric. In particular, we study deterministic identification (DI) for the discrete-time Poisson channel (DTPC), subject to an average and a peak molecule release rate constraint, which serves as a model for MC systems employing molecule counting receivers. It is established that the number of different messages that can be reliably identified for this channel scales as 2(nlogn)R , where n and R are the codeword length and coding rate, respectively. Lower and upper bounds on the DI capacity of the DTPC are developed. The obtained large capacity of the DI channel sheds light on the performance of natural DI systems such as natural olfaction, which are known for their extremely large chemical discriminatory power in biology. Furthermore, numerical results for the empirical miss-identification and false identification error rates are provided for finite length codes. This allows us to characterize the behaviour of the error rate for increasing codeword lengths, which complements our theoretically-derived scale for asymptotically large codeword lengths.

Fachbereich(e)/-gebiet(e): 18 Fachbereich Elektrotechnik und Informationstechnik
18 Fachbereich Elektrotechnik und Informationstechnik > Resiliente Kommunikationssysteme (RCS)
LOEWE
LOEWE > LOEWE-Zentren
LOEWE > LOEWE-Zentren > emergenCITY
Hinterlegungsdatum: 20 Jun 2024 13:28
Letzte Änderung: 20 Jun 2024 14:02
PPN:
Export:
Suche nach Titel in: TUfind oder in Google
Frage zum Eintrag Frage zum Eintrag

Optionen (nur für Redakteure)
Redaktionelle Details anzeigen Redaktionelle Details anzeigen