Performance Bounds of estimators in molecular communications under structural constraints

Alireza Sadeghi, Siavash Ghavami, Georgios B. Giannakis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Parameter estimation is a key task in many aspects of communication systems including molecular communications (M C). The performance of parameter estimators involved in MC has been so far assessed using the Cramer-Rao lower bound (CRLB). However, for the discrete-amplitude parameters associated with the released "information molecules" in MC, pertinent regularity conditions do not hold, and consequently the CRLB does not exist. In this context, the present paper advocates the more general Hammersley-Chapman-Robinson lower bound (HCRLB), for MC parameter estimation. As a special case of practical importance, estimation of the number of released molecules, N, is investigated. A simple yet tight approximation of the HCRLB is developed by solving a non-convex optimization problem. A more accurate lower bound is also derived after accounting for the structural constraints inherent to the model under consideration. The resultant approach does not require the aforementioned regularity conditions to be satisfied.

Original languageEnglish (US)
Title of host publicationProceedings of the 4th ACM International Conference on Nanoscale Computing and Communication, NanoCom 2017
PublisherAssociation for Computing Machinery, Inc
ISBN (Electronic)9781450349314
DOIs
StatePublished - Sep 27 2017
Event4th ACM International Conference on Nanoscale Computing and Communication, NanoCom 2017 - Washington, United States
Duration: Sep 27 2017Sep 29 2017

Publication series

NameProceedings of the 4th ACM International Conference on Nanoscale Computing and Communication, NanoCom 2017

Other

Other4th ACM International Conference on Nanoscale Computing and Communication, NanoCom 2017
CountryUnited States
CityWashington
Period9/27/179/29/17

Keywords

  • Hammersley-Chapman-Robinson lower bound
  • Molecular communication
  • Parameter estimation

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